There’s a peculiar phenomenon in EdTech: companies are worth billions while their users learn … not all that much.

This isn’t a bug in the system. It’s the system working exactly as designed.

The gap between what learning feels like and what learning actually is has created an entire industry optimised for the wrong outcome.

Understanding this gap explains why your Duolingo streak doesn’t mean you can speak Japanese, why that $18,000 bootcamp didn’t land you a job, and why EdTech valuations keep climbing while educational outcomes flatline.

The Experience Economy Meets Education

Joseph Pine and James Gilmore’s seminal work on the experience economy revealed something crucial: people don’t buy products or services, they buy experiences. In entertainment, hospitality, and retail, this insight revolutionised business models.

EdTech took note. But education has a fatal quirk that makes the experience economy dangerous: the best learning experiences often feel terrible in the moment.

As cognitive scientist Daniel Willingham has extensively documented, effortful thinking is inherently unpleasant. The struggle that creates durable learning (what Robert and Elizabeth Bjork call “desirable difficulties”) feels like failure to the learner. Smooth, pleasant experiences that generate immediate satisfaction are precisely the conditions that undermine long-term retention and transfer.

This creates a toxic dynamic: EdTech companies can grow faster by making learning feel valuable rather than making it be valuable.

The Two-System Problem

Daniel Kahneman’s distinction between System 1 (fast, intuitive) and System 2 (slow, effortful) thinking illuminates why this gap persists. Learners use System 1 to evaluate whether they’re learning. It feels good, therefore I’m learning. It feels hard, therefore it’s not working.

But actual skill acquisition happens almost entirely in System 2. As Anders Ericsson’s research on deliberate practice demonstrates, expertise requires focused attention on weaknesses, immediate feedback, and repeated attempts to do things just beyond current capability. None of this feels good.

Learners, making System 1 judgments about System 2 processes, consistently mistake fluency for mastery. This is what Philip Guo at UC San Diego calls the “illusion of competence”: the deadly gap between feeling like you understand something and actually being able to apply it.

EdTech platforms can exploit this gap deliberately or accidentally, but the commercial incentive is identical: maximise perceived value while minimising the cost of delivering experienced value.

The Metrics That Betray Learning

Justin Reich at MIT has spent years studying why digital learning interventions consistently fail to scale learning outcomes despite scaling user bases beautifully. His conclusion is damning: EdTech companies measure what’s easy to measure, not what matters.

Engagement metrics like time on platform, completion rates, daily active users are the currency of venture capital and public markets. These metrics capture perceived value brilliantly. They say nothing about capability development.

As Ben Williamson at University of Edinburgh argues, the datafication of education has created what he calls “computational governance,” where platforms shape behaviour toward what can be measured rather than what should be learned. When retention depends on engagement rather than mastery, the rational business decision is to optimise for the former.

Neil Selwyn takes this further, arguing that EdTech’s obsession with efficiency and scale fundamentally misunderstands education as a human practice. Learning requires time, struggle, relationship, and failure.

None of these scale elegantly or show up in monthly active user charts.

The AI Acceleration

Large language models have turbocharged this problem. They can generate explanations so immediately satisfying that they create unprecedented perceived value while potentially destroying experienced value.

As Sherry Turkle warned in her work on technology and human connection, we’re increasingly vulnerable to substituting simulation for authentic experience. AI tutors can simulate the experience of understanding without requiring the cognitive effort that creates actual understanding.

Ethan Mollick at Wharton has been tracking this in real-time with students using ChatGPT. He observes that AI can make students feel more confident while making them less capable, what he calls “the delegation trap.” Students experience the value of having problems solved for them without experiencing the value of solving problems themselves.

The Valuation Paradox

Here’s where it gets darkly fascinating: the worse EdTech is at delivering experienced value, the faster it can grow, at least initially.

The jobs-to-be-done framework helps explain this. Learners aren’t hiring EdTech products to learn; they’re hiring them to feel like they’re learning. They’re hiring them to check a box, satisfy a social obligation, or reduce anxiety about falling behind.

Audrey Watters has been documenting this for over a decade. EdTech, she argues, is more about surveillance, credentialing, and the performance of learning than about learning itself. Platforms that deliver on the performance while skipping the learning capture more market share, not less.

The venture capital model amplifies this. A company with 50 million users learning nothing is worth more than a company with 50,000 users developing genuine capability.

The Retention Cliff

But here’s the problem: perceived value without experienced value has a shelf life.

BJ Fogg’s behaviour model shows that behaviour requires motivation, ability, and trigger in the same moment. EdTech companies are excellent at providing triggers (notifications, streaks, gamification). They’re decent at lowering ability barriers (smooth onboarding, bite-sized content). But they systematically fail to build real ability, which means motivation eventually dies.

This is why EdTech companies show spectacular growth curves followed by catastrophic retention problems. The gap between perceived and experienced value can be papered over with marketing, social proof, and sunk cost fallacy but only for so long.

The Signal Design Challenge

Herminia Ibarra’s work on professional identity offers an unexpected insight. People don’t change because they learn new information; they change because they get new evidence about who they are and what they can do.

This is the crux of the value gap: perceived value is about information and feeling. Experienced value is about identity and capability.

For experienced value to overtake perceived value as a growth driver, EdTech needs to make capability development visible and social. Learners need evidence they can share with themselves and others that they’ve genuinely changed.

The Accountability Moment

We’re approaching an inflection point. The industrial model of education (and by extension, EdTech) is finally colliding with the demands of a world that values creativity, adaptability, and authentic capability over credentials and completion certificates.

AI makes this collision inevitable and immediate. When anyone can generate a perfect essay or explanation, the credential economy collapses. The only thing that matters is what you can actually do.

This creates a ruthless market dynamic: EdTech companies can no longer hide behind information delivery as a proxy for learning. The gap between perceived and experienced value becomes obvious the moment learners try to apply what they “learned.”

The Path Forward

Several researchers offer provocative solutions:

Make transfer visible: Michelle Miller’s work on teaching and learning suggests that platforms should require learners to demonstrate capability in novel contexts, not just within the app’s controlled environment.

Embrace productive failure: Manu Kapur’s research shows that struggling with problems before receiving instruction produces deeper learning than smooth, scaffolded experiences. EdTech needs to reward struggle, not hide it.

Build social proof around capability: Reuben Lim’s work on badging and credentials suggests that social recognition needs to attach to demonstrated capability, not time spent or content consumed.

Align revenue with outcomes: John Hattie’s meta-analyses on learning effectiveness point toward a brutal truth: what works for learning often looks nothing like what scales commercially. Until business models reward actual capability development, the gap persists.

The Uncomfortable Truth

The EdTech decacorn that teaches nothing isn’t an accident.

It’s the logical endpoint of a system that rewards perceived value and can’t measure experienced value.

The companies that survive the next decade won’t be those with the smoothest AI tutors or the most engaging gamification. They’ll be the ones whose learners can demonstrably do things they previously could not and whose business models depend on that outcome.

The gap between perceived and experienced value is an arbitrage opportunity for founders and a moral hazard for society. AI eliminates the excuses for not closing it.

The question is whether we’ll choose to.

Kate Busby is Founder of Vibe Combinator, CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Linkedin. Subscribe to Substack to receive all articles on AI, edtech and impact accountability straight to your inbox.

Here’s what nobody except Gagan Biyani and I want to say out loud: most educational apps are optimized to make money, not to actually teach you anything.

You’ve probably felt this yourself. Download Duolingo, feel great for a week, then quietly forget Spanish exists. Sign up for that online course, watch three videos, never finish. The app celebrates your “7-day streak!” while you secretly know you can’t actually do the thing you’re supposedly learning.

This isn’t your fault. It’s Duolingo’s business model.

And AI is about to make this problem much, much worse.

Or, if we’re lucky, finally fix it.

The Billion-User Illusion

EdTech companies love to brag about scale. “One billion users!” they announce, as if that number means anything.

But here’s the thing: a billion people logging in and bouncing off your app doesn’t prove you’re changing lives. It proves you’re good at acquisition marketing.

Researchers like Audrey Watters and Neil Selwyn have been shouting from the rooftops for years: reach is not the same as learning. Engagement is not the same as skill development and enablement.

You can “feel productive” while learning absolutely nothing.

Education is uniquely vulnerable to this trap because you can’t tell if it’s working while you’re doing it. Skills take hours to build and weeks to stick.

By the time you realize that online course was useless, the company already has your money, your data and proudly sharing both with investors.

AI makes this problem turbo-charged. Large language models can generate perfect explanations, solve problems instantly, and create a beautiful illusion that you’re getting smarter, while you’re actually getting more dependent.

Here’s the twist: The very same AI could finally force the whole industry to get very honest with itself, very fast.

Why You Forget Everything You “Learned”

Cognitive science has known for decades that learning isn’t just exposure to information. Daniel Willingham put it bluntly: students don’t like school because thinking is hard, and what you learn in one context almost never transfers to another.

The research is brutal:

• Smooth explanations feel good but don’t stick (Robert and Elizabeth Bjork’s work on “desirable difficulties”)

• Repetition alone doesn’t create expertise. You need struggle, feedback that unblocks the blockers and clears the path, as well as fixing your mistakes (Anders Ericsson on “deliberate practice”)

• Ease is the enemy of mastery

From an EdTech business perspective, this is all a nightmare. Make learning hard, and users complain and quit. Make it easy, and users eventually realize they can’t actually do anything, then they quit anyway.

The fastest-growing EdTech products are often the most fragile ones. And then more fragile they are, the harder they optimize for metrics that have nothing to do with learner success.

AI doesn’t solve this problem. It exposes it in high definition.

Why You Actually Quit Learning Apps

Here’s the real reason you stopped using that language app: not because you couldn’t do it, but because your motivation died.

According to Self-Determination Theory, you stay motivated when three needs are met: autonomy (feeling in control), competence (feeling capable), and relatedness (feeling connected).

Most AI-powered learning tools accidentally destroy all three:

• They kill autonomy by making too many decisions for you

• They fake competence by hiding your struggles behind smooth AI assistance

• They replace human connection with bland robo-feedback

Richard Thaler’s work on nudges taught us something crucial: people respond to whatever gets rewarded, whether designers intend it or not. But as BJ Fogg points out, motivation alone won’t save you: you need ability and the right triggers working in sync.

This is where Angela Duckworth’s research on grit becomes painfully relevant. Perseverance matters, but only when the goal feels genuinely meaningful. When a learning app rewards speed over mastery, or completion over application, you’ll optimize for exactly that.

The moment you realize you can’t actually speak Spanish despite your 100-day streak? You’re gone.

AI can either automate disengagement, or help users detect their progress in real time.

The Breakthrough: Making Progress Measurable and Visceral

Here’s where things get interesting.

The biggest disconnect in EdTech is this: real learning is slow and invisible, but companies need to show fast, visible wins. AI can actually bridge that gap.

Instead of being your tutor, AI can be your progress tracker, the thing that shows you’re genuinely getting better at something real.

Well-designed AI systems can:

• Track actual skill growth over time, not just “lessons completed”

• Generate targeted practice that hits your weak spots

• Show you evidence of transfer: “You couldn’t do this last month. Now you can.”

• Help you reflect on how your thinking has changed

This isn’t personalisation for the sake of personalisation. This is making learning feel tangible and real.

When you can actually see yourself gaining abilities you can use outside the app, everything changes. You stay. You pay. You tell your friends.

AI can turn learning from “trust me, it works” into “holy shit, I can feel this working for me.”

The 4-Layer Test: How to Spot Real Learning

Want to know if an AI learning tool is legit? Ask these four questions:

1. Capability Gain

What can I do now that I couldn’t do before?

If you can’t answer this concretely, it’s not learning, it’s engagement theatre.

2. Progress Legibility

Do I understand how and why I’m improving?

AI should make your growth visible, not hide it behind smooth experiences.

3. Motivation Alignment

Do the short-term rewards match long-term mastery?

If ease replaces effort, you’ll quit eventually. Guaranteed.

4. Economic Sustainability

Does better learning drive the business, or do dark patterns?

If the company makes more money when you don’t learn, run.

Only when all four align do you get a learning product that actually works, and lasts.

The Dependency Trap

Critical scholars like Ben Williamson warn that AI in education is never neutral. These platforms shape what counts as knowledge, what counts as progress, what counts as success.

If AI systems optimise for engagement metrics instead of human capability and enablement, we’re building a generation of confident, dependent learners who collapse the moment you take their AI away.

This isn’t just a moral problem. It’s a business problem. Dependency destroys trust. Low-to-no trust kills long-term value.

The EdTech companies that survive will be those that treat learning outcomes as their competitive advantage, not a marketing tagline.

In a world drowning in AI, credibility becomes the rarest and most valuable currency.

The Bottom Line

The tension between making money and actually helping people learn is real. But there’s a simple alignment point:

EdTech companies only deserve to grow if learner success makes them grow, not paid ads, not viral loops, not engagement tricks.

AI eliminates all excuses. We can now measure, model, and surface learning in ways that were impossible before.

The question isn’t whether AI will be used. It’s what we’ll optimise for.

If we optimise for making learning easier, faster, and emptier, we’ll get scale without substance: a billion users who can’t do anything.

If we optimise for making progress tangible and even feel exciting in the moment, we might finally build an EdTech industry where making money and making lives better reinforce each other.

AI isn’t making learning more lucrative. It’s making EdTech accountable.

And it’s about damn time.

Kate Busby is Adjunct Professor of AI Marketing at ESEI International Business School, CoFounder of Quiet Edge and Fractional CMO and Board Advisor to edtech startups from Pre-Seed to Series B. Catch her on X and LinkedIn. To receive more articles exploring AI in EdTech, subscribe to Substack.

As someone who has been both an amazing manager (if I do say so myself) and a horrendous one (if some others had a say), I’ve come to realise there’s a fundamental misunderstanding on both sides of the aisle (employee and employer) in how skills matrices and competency charts are designed to guide career progression. It’s one I’ve fallen for myself too.

Over my decade of building and managing teams, I’ve built everything from extremely complicated scoring matrices to extremely simple personal development frameworks. Deep inside, I knew both were slightly missing the mark in terms of what I was trying to communicate on behalf of the company.

Like most of us, I grew up with standardised competency matrices and skills charts. Both my best and worst managers used them to manage my expectations. The same tools, presented from different perspectives, led to completely different experiences. Some were devastating. Some were genuinely enlightening.

How is it possible that a tool designed to standardise evaluation can create such wildly inconsistent outcomes?

My view is this: skills matrices try to turn promotions into a checklist. Promotions are not a checklist. Promotions are a scope change, and a risk decision.

How we got here:

Both businesses and employees want the same thing: certainty about the future.

In the search for certainty, in the form of a concrete, repeatable, scalable way to manage development and expectations, managers standardised performance into measurable goals and metrics.

Perform these tasks, accomplish these goals, and you will qualify to jump to the next level.

In return, employees receive a checklist (but not really a checklist 😉) of tasks and skills they can work towards to reach that next level.

It sounds fair. It sounds clean. It sounds like something you can run at scale. However, as all managers know, it’s not that simple.

Receiving a promotion isn’t a checkbox exercise. There’s nuance that can’t be captured cleanly. Some skills matter more than others. Some behaviours only matter when the pressure is on. Some people can do a task, but can’t yet own the consequences of that task.

So the chart grows. More categories are added. Scoring becomes more complicated. More edge cases are baked into the competency chart. Eventually, managers go down the rabbit hole trying to account for every permutation of skillsets that might matter.

And once you’re detailing out 20 skills and activities (and admitting that some are more important than others), communicating the system becomes a complicated explanation. It turns into endless permutations of “if I say this, then I should also say that…”, until the tool becomes something you maintain instead of something that actually helps.

So what now?

A new framework to role definition: A structure for both Employees and Employers to understand

First Principles:

If we’re going to build something better, we have to go back to first principles. As a manager, the first principles are pretty simple:

• To the employee: your job is to shepherd them and prepare them for the next level so they do not fail.

• To the company: your job is to shield the business from risk, and from the damage an unprepared employee can cause.

However, this is a two-way street.

Employees need to understand that even if they feel ready for a promotion, the company might not be ready to bet the business (or the team, or the client relationship) on that decision.

Employers need to understand the opposite is also true. They are beholden to the career progression of their employees. Otherwise, in today’s market of low corporate loyalty, employees will look out for their own career interests ahead of the company’s.

While the tension sucks, it’s a healthy way for two parties with overlapping, but not identical, interests stay aligned.

Stop defining roles by skills. Define them by scope change.

Roles should not be defined by the skills and competencies a person develops over time. They should be defined by the scope of work that changes as someone steps up.

If you want a structure that actually holds, the framework for “the next level” needs to answer two questions:

• For the employee: is the scope change big enough that you are likely to struggle if you take it on?

• For the employer: if you struggle, what risk profile is the business willing to accept for this new scope?

That’s it.

For the employee side, we factor in things like knowledge requirements, technical experience, judgement, and soft skills.

For the employer side, we factor in things like liability, standards, performance expectations, reputational cost, customer impact, and what happens if it goes wrong.

On the employee side the conversation is ‘can you handle it’. On the employer side, it’s ‘what happens if you can’t’.

The role, and the level within the role thus becomes a composite of those two components. Scope plus risk.

An Example

In my earlier years, I was a supremely confident project manager with all the blind confidence of someone in their 20s who had not yet experienced a major failure. I was also deadly with the written word.

With one well-thought and articulated paragraph, I could dismantle arguments, people, performance, and build an irrefutable case to support my situation. I was not afraid to weaponise that to achieve my own goals. To me, that was my strength, but to the company, that was a risk.

To me, I was a HI-PER, performing at the peak of individual performance, wielding persuasive arguments as my sword. To the company, I was a volatile risk who did not yet understand how to lead by example. That example being: not tearing people down to get your way.

(If you’ll notice, I’ve now redirected that energy of persuasion in other ways.)

A skills matrix would have rewarded me for “communication”, “stakeholder management”, “influence”, “ownership”. I could tick those boxes all day long.

But the scope change I was really asking for required something else: judgement under ambiguity, restraint, and leadership that didn’t rely on winning at any cost. The company wasn’t wrong to hesitate. They weren’t blocking me because I hadn’t “met the competencies”. They were hesitant because the risk profile of giving me more scope was higher than I understood at the time.

That’s the gap skills matrices consistently fail to communicate. They measure capability in isolation. Promotions are capability plus the consequence if the individual gets it wrong.

Mapping out scope change (the part that replaces the matrix)

Instead of saying “Here are the skills you need to demonstrate”, you say “Here is how the scope changes at the next level, and here is the risk the business is taking on by giving you that scope”.

Now you can have a real conversation.

• What is the new scope?

• What changes about decision-making?

• What changes about who gets impacted by your mistakes?

• What changes about what “good” looks like?

• What does the business need to believe to feel safe making the bet?

The replacement artefact: the Scope Ladder

If you take anything from this, it’s this: you don’t need a bigger, more detailed matrix. You need a clearer artefact.

The thing that replaces a skills matrix is not another spreadsheet. It’s a one-page “Scope Ladder” for each role.

It answers, plainly:

• What changes about the work at the next level

• What the business is taking on by giving you that scope

• What needs to be true for both sides to feel good about the bet

And it does one more important thing that competency charts rarely do. It makes the manager’s job visible too. Because “get promoted” should not be a scavenger hunt where the employee tries to guess what the company is nervous about.

What it looks like in practice

You create a Scope Ladder per role. Make it short, readable and able to fit on one page.

Each level has two parts:

1. Scope (what you now own)

2. Risk notes (what the company is protecting itself from, and how we reduce that risk)

That’s the core component of the document.

Then you add a third part that keeps it human:

1. Support (what the manager and company will do to help you succeed in that new scope)

If you want to be very honest, add a fourth:

1. If it goes wrong (what “going wrong” looks like, and what the plan is)

Most companies avoid this because it feels negative. I think it’s the opposite. It reduces fear, makes expectations clearer, and stops the weird mind-reading games that happen around promotions.

Why this solution works better than a matrix

A skills matrix forces you into arguing about whether someone is a “4” or a “5” on “stakeholder management”.

A Scope Ladder forces you into something more real:

• Are you already operating in the next scope, or are you still doing the current one really well?

• If we widen the scope, what changes about the consequences of your decisions?

• What proof would make the business comfortable making that move?

It also removes a common trap. People over-index on collecting skills, and under-index on demonstrating ownership. The ladder makes ownership the centre of gravity.

A simple template you can steal

You can put this in Notion, a Google Doc, whatever. The format matters less than the clarity.

ROLE: [ROLE NAME]
PURPOSE (1 SENTENCE): [PLAIN ENGLISH PURPOSE OF THE ROLE]

------------------------------------------------------------
LEVEL: [TITLE]
------------------------------------------------------------

A) SCOPE (WHAT YOU OWN)
- …
- …
- …

B) DECISION RIGHTS
- YOU DECIDE: …
- YOU RECOMMEND: …
- YOU ESCALATE: …

C) WHAT “GOOD” LOOKS LIKE
- …
- …

D) RISK NOTES (WHAT THE BUSINESS IS PROTECTING ITSELF FROM)
- …
- …

E) SUPPORT (WHAT YOU GET SO YOU DON’T FAIL)
- …
- …

------------------------------------------------------------
PROMOTION READINESS (PLAIN ENGLISH)
------------------------------------------------------------

SIGNS YOU’RE ALREADY OPERATING AT THE NEXT LEVEL
- …
- …

SIGNS YOU’RE NOT THERE YET
- …
- …

WHAT WE NEED TO SEE IN THE NEXT [4–8] WEEKS
- …
- …

WHAT I’M COMMITTING TO AS YOUR MANAGER
- …

Quick example: Product Manager to Senior Product Manager

This is a common one because, on paper, the skills often look the same. You’re still doing discovery, still writing docs, still shipping. The change is not “more PM”. The change is the scope you carry, and the consequences attached to it.

=============================================
QUICK EXAMPLE: Product Manager → Senior PM
=============================================

------------------------------------------------------------
LEVEL: Product Manager
------------------------------------------------------------

SCOPE (what you own)
- Own a defined problem space or well-bounded product area
- Translate goals into clear problems, options, and a plan the team can execute
- Run discovery with support, then turn learning into decisions
- Ship reliably, learn fast, keep stakeholders informed
- Maintain a healthy delivery rhythm with engineering + design

DECISION RIGHTS
- You decide: approach within an agreed direction
- You recommend: priorities with input from your lead
- You escalate: when trade-offs affect other teams or company-level goals

WHAT “GOOD” LOOKS LIKE
- The team knows what they’re doing and why
- Decisions are documented, progress is visible, surprises are limited
- Trade-offs are explained clearly, even when people disagree

RISK NOTES (if it goes wrong)
- Wasted cycles within one team
- A feature that misses the mark or needs major rework
- Stakeholder confidence drops because communication is unclear


------------------------------------------------------------
LEVEL: Senior Product Manager
------------------------------------------------------------

SCOPE (what you own)
- Own an outcome across a broader area, often spanning multiple teams or systems
- Define the shape of the work, not just the next set of tickets
- Drive alignment when there is no obvious single answer
- Make hard calls with incomplete information, and stand behind them
- Improve how the product function operates, not just what it ships
- Coach other PMs informally through examples, not authority

DECISION RIGHTS
- You decide: sequencing across a wider scope
- You set: the narrative leaders + teams can repeat accurately
- You trade off: customer value vs tech constraints vs business reality
- You escalate: less, because you can resolve more

WHAT “GOOD” LOOKS LIKE
- Clarity increases around you even when the situation is messy
- Multiple stakeholders stay aligned without constant hand-holding
- You can turn a fuzzy goal into a credible plan with decision points
- The work holds up over time, not just at launch

RISK NOTES (if it goes wrong)
- Misalignment across teams that becomes expensive to unwind
- Strategic drift that goes unnoticed until it’s costly to fix
- Loss of trust because decisions feel inconsistent
- A lot of activity that doesn’t move the outcome


------------------------------------------------------------
PROMOTION READINESS (plain English)
------------------------------------------------------------

SIGNS YOU’RE ALREADY OPERATING AT Senior PM
- You frame problems in a way that makes decisions easier for everyone else
- You manage conflicting stakeholders without escalating every time
- You surface risks early and adjust course before it becomes public
- Your plans survive contact with reality

SIGNS YOU’RE NOT THERE YET
- You need constant validation to make decisions
- You stay inside your team boundary when the outcome depends on others
- You default to delivery activity when the real issue is alignment / trade-offs
- Your roadmap shifts often because the narrative isn’t anchored

How you use it

You don’t pull this out at promotion time. You pull it out early.

In a 1:1, you literally sit side-by-side and answer:

• “Here is your current scope, are we aligned that this is what you own today?”

• “Here is the next scope, which parts are you already doing, which parts are you not doing yet?”

• “Which risks are the company most nervous about in that next scope?”

• “What would reduce that risk in a way that’s fair and observable?”

That turns the promotion conversation into something sane for both parties. It also protects the employee from the most demoralising outcome, which is thinking you’re doing everything right, then being told “not yet” with no real explanation.

Communicate Early

Using this framework, an employee can feel ready for the next level because they’ve “ticked all the boxes”, but the company might still say no. Not because the employee is bad, or because the company is playing politics, but because the scope change introduces a risk profile the business isn’t willing to accept yet.

The goal, then, is to communicate that early. Not at promotion time. Not after the employee has already emotionally promoted themselves. Early enough that the employee can actually build towards reducing that risk, rather than just collecting skills like badges.

The career conversation becomes a joint plan, not a negotiation

If you’re using scope and risk as the model, then the career conversation changes shape.

It stops being “convince me I deserve it”. It becomes “let’s make a plan that’s fair to you and safe for the business”.

Because here’s the part that’s often left unsaid: employees don’t just want the title. They want clarity that their career is going somewhere. They want to know what to aim at. They want to know the rules of the game they’re playing.

Likewise companies, whether they admit it or not, want to reduce uncertainty. They want to know that if they widen someone’s scope, they’re not about to create a performance issue that harms the team, the customer, and the manager who signed off on it.

So the agreement becomes simple:

• The employee gets clarity, support, and a real opportunity to demonstrate next-scope work.

• The company gets evidence, risk reduction, and a path that doesn’t rely on gut feel and politics.

And importantly, the manager stops hiding behind vague language.

If the real concern is “this role involves more cross-team trade-offs and you haven’t done that yet”, you can just say that.

If the real concern is “this role carries reputational risk and we need to see your judgement under pressure”, you can just say that.

That honesty, even when it stings a bit, tends to be received better than being fed a checklist that doesn’t match the decision that gets made.

How to not create another checklist

There is a real danger that the moment you propose using the new artefact above, companies will try to turn it into the same old thing.

This is not meant to become “Your Next Scope Ladder has 37 criteria”. If that’s what it becomes, it will suffer the same problem as before.

The replacement is not “more categories”. The replacement is a more honest form of proof.

The proof is: can you carry the next scope without the manager secretly doing the hard parts for you?

That’s what readiness looks like in practice.

Of course some of that will be output. But realistically speaking, most of it is judgement, prioritisation, and how you navigate ambiguity without melting down or causing collateral damage.

So instead of asking “have you demonstrated competency X”, the questions become:

• Are you already operating in parts of the next scope?

• Which parts are missing, and why?

• What would we need to see to feel comfortable widening that scope?

• What support and guardrails would make that fair?

This stops people from collecting skills like badges and starts focusing them on ownership. Ownership is where promotions actually live.

Scope trials: the fairest way to answer “am I ready?”

If you want a practical mechanism that doesn’t feel political, it’s this.

You run a scope trial.

Rather than propose a vague goal such as “act like a senior” or suggest a performative task of “take on more”. You create a defined, time-boxed scope bump with a safety net.

You agree, in writing, on four things:

• The scope bump: what is different from today, specifically?

• The outcome: what are we trying to move, not what are we trying to ship?

• The guardrails: what’s in bounds, what gets escalated, what support exists

• The time window: long enough to be real, short enough to be reversible

For PM to Senior PM, a scope trial might look like: owning a cross-team outcome, or leading a messy trade-off space where there is no happy path, or taking responsibility for a decision that has real downstream consequences.

The point is not to observe a perfect score. The point is whether the person can carry the weight of the scope without the whole system compensating for them.

And for the employee, this is where it becomes fair.

If you want me to operate at the next level, then give me access, decision rights, and the room to actually do it. Don’t ask me to prove myself while keeping me fenced in like it’s still my old scope.

That is where a lot of resentment is born. People are told to perform senior work while being blocked from doing senior work.

Promotions are lagging indicators

A promotion is not the moment someone becomes senior.

It’s the moment the company acknowledges they already are, because they’ve been carrying that scope in a way that’s safe enough to formalise.

If the Scope Ladder is honest, and if scope trials are real, then promotions become less dramatic and less emotional or some thing issued by the decree of some court case.

You’ve already done the work. You’ve already been calibrated. The title just catches up.

This also cuts the other way.

If someone has been carrying the next scope for months, moving outcomes, reducing risk, doing the hard parts that nobody wants to own, and the company still won’t acknowledge it… they will leave.

And they won’t leave because they’re disloyal. They’ll leave because they’re not stupid.

Where skills matrices still belong

To be clear, I’m not saying skills matrices are useless.

They’re fine for baseline expectations.

• onboarding

• training

• safety and compliance

• “can you do the job without breaking things”

• identifying broad gaps across a team

That’s where they shine.

They break when they’re used as the logic for promotion, because promotion is not a list of skills. It’s a change in scope, with consequences attached.

Matrices measure capability in isolation.

Promotions measure capability under responsibility.

Those are not the same thing.

What I wish I’d been told earlier

If I could go back and talk to my younger self, I wouldn’t tell him to create more tick boxes or more complex scoring algorithms.

I’d tell him to ask a different question.

“What scope am I asking for, and what is the company actually nervous about if you give it to me?”

Because once you know that, the path becomes clearer. Not easier, but clearer.

And if you’re a manager reading this, the most important thing that you need to know is that you can’t outsource this to a chart.

You have to do the work of making the scope explicit, making the risks explicit, and then supporting someone through the stretch in a way that doesn’t set them up to fail.

That’s what good management is. Not filling in cells in a spreadsheet.

6. Zoom in and get started: who is our beachhead persona and what is our wedge?

Every big company starts small. Your wedge into the market is what makes you defensible: it’s the first stronghold you use to expand later.

Without a wedge, you are just another competitor in a crowded market struggling for revenue.

Framework: The Beachhead Wedge

• Identify → Find a small, underserved segment with a pressing problem.
  
  

• Solve → Deliver a solution better than current alternatives in at least one clear way that prospects are crying out for.
  
  

• Expand → Use that success as a launchpad to adjacent segments or broader markets.
  
  

Classic problems

• Trying to win everyone on day 1.

• Launching a copycat product with no clear differentiation.

• Scaling before you’ve nailed one niche.
  
  

Risks of not fixing

• You drown in crowded markets with no differentiation.

• No one remembers your brand because you’re generic.

• Competitors outmaneuver or copy your product before you’ve gained traction.
  
  

Actionable playbook (do this week)

1. Identify 1 prospect niche (e.g., remote-first law firms, vegan meal prep influencers, micro-SaaS founders - go deep).
   

2. Validate demand: run 5–10 calls or interviews with this niche to uncover pain points and willingness to pay.
   

3. Build a landing page or MVP tailored to that persona.
   

4. Test signups with $100 in targeted ads or outreach.
   

5. Collect metrics: interest, clicks, signups, and feedback. Use this to refine USP and expand strategy.
   

Steal this prompt:

Act as a senior growth strategist for early-stage startups. My startup operates in [industry/niche], and I want to identify a niche segment where our product/service can deliver a 10x improvement over existing solutions. Please provide:

1. Beachhead persona – a detailed, high-potential target segment with clear pain points and motivations.

2. Unique Selling Proposition (USP) – a compelling message or value proposition that resonates strongly with this persona.

3. Step-by-step pilot plan – a low-budget validation strategy using [budget amount, e.g., $100] for targeted ads, outreach, or experiments. 

Include:
Specific actions to take
Expected costs and timelines
Metrics to track success

Additionally, suggest any overlooked angles or creative approaches to reach this persona and validate demand efficiently.

These companies figured it out:

B2B case study

Perplexity AI (2023) Instead of competing with ChatGPT head-on, Perplexity carved a wedge as the “answer engine.” Their beachhead persona? People frustrated with Google clutter. By focusing tightly on this niche, they earned traction, built a differentiated product, and grew a loyal base before taking on larger competitors.

B2C case study

Notion initially targeted knowledge workers and productivity geeks who were dissatisfied with existing note-taking tools. By building a product that solved their exact pain points (flexibility and modularity) they created evangelists. These users became a marketing engine through shared templates and community engagement, giving Notion a strong launchpad to expand to a broader audience of students, teams, and enterprises.

More B2B tips

• Target a single vertical or persona segment where value is obvious and measurable.

• Use a land-and-expand strategy within accounts: start small, then upsell or cross-sell once trust is established.

• Build case studies or references from early wins to expand into adjacent verticals.

• Measure early CAC vs. LTV in the niche before expanding to other segments.
  

More B2C tips

• Focus on early adopters or super-fans in a niche community.

• Leverage viral content or referral loops to wedge into larger audiences.
  Encourage word-of-mouth through shareable experiences or incentives (exclusive features, rewards, gamified elements).

• Monitor engagement metrics (shares, comments, repeat use) as your wedge signal.
  

TL;DR

Intuition and AI tools got you a functional product. At this point, vibes stop. Now you need a structured plan to build a growth motor.

So:

1. Figure out your startup’s current growth stage using our checklist.

2. Reverse-engineer goals: what revenue do you need and when, then work backwards to establish your plan.

3. Now work forward: get customer insights and sense check your plan from point 2

4. Budget and be scrappy. Follow point 6 and this rule becomes easier.

5. Be brave enough to use guerrilla tactics. Failing that, small low-cost experiments.

6. Get your foot in the door with a niche audience and best-in-class solution to their burning problem. Expand from there.

…And by layering AI as your growth copilot using our playbook promptly library, you’ll rapidly turn gut feeling into traction.

Kate Busby is CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Instagram. The images are extracted from X and created by MidJourney. No names and identifying details have been changed. Subscribe to Substack to receive all articles in the “Rules of Growth” series straight to your inbox.

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5. What scrappy growth moves feel authentic to this company?

You can’t outspend incumbents, but you can outsmart them.

Guerrilla growth focuses on low-cost, high-impact tactics that leverage communities, creativity, and micro-testing to generate momentum. The goal is visibility, engagement, and proof of traction before scaling spend.

There are hundreds of plays, but let’s look at three that are accessible and have long-term benefits:

Classic problems

• Believing paid search and social ads are the safest path to fast growth.

• Failing to craft a compelling story.

• Not showing up consistently in relevant communities.

Risks of not fixing

• You’ll remain invisible to your target audience.

• Bigger competitors dominate mindshare and market perception.

• Organic growth opportunities are lost forever.

Actionable playbook (do this week)

1. Post once daily in one niche community (Reddit, Discord, Twitter).

2. Draft a PR angle framed as “X is broken, we’re fixing it.”

3. Run $50 TikTok or Reddit ad tests on this creative.

Steal this prompt

Act as a growth marketing strategist specializing in authentic, low-budget startup growth. My startup operates in [industry/niche] and has the following brand identity: [describe tone, values, unique voice]. I want to grow using guerrilla marketing tactics that feel genuine and on-brand.

Please suggest 3–5 actionable growth moves across these areas:

Niche community engagement – ways to connect meaningfully with relevant audiences.

PR stunts – creative, attention-grabbing initiatives that align with our voice.

Micro-tests with minimal spend – small experiments that can validate ideas quickly.

For each tactic, include:

Estimated cost and effort
Potential impact or reach
How it ties to the brand identity
Any risks or considerations

Also, identify any unconventional or overlooked ideas that could work particularly well for a startup with our voice and values.

These companies figured it out

B2B case study

FlowAI, a seed-stage AI workflow automation startup, needed to stand out in a crowded SaaS landscape without a large marketing budget. Their product could automate repetitive tasks across Slack, Notion, and Google Workspace, but convincing early-stage startups to try an AI workflow tool was tough.

Low-cost, high-impact tactics:

1. Community-first growth:

   • FlowAI’s founders joined Hacker News, Indie Hackers, and Product Hunt communities, sharing small “automation hacks” powered by FlowAI.

   • Each post was technical, AI-coded, and detailed step-by-step, giving readers immediate value while subtly showcasing the product.
     

2. Micro-case studies & templates:
   

   • The team created free, shareable AI workflow templates (e.g., “Auto-prioritize Slack tasks using GPT-4” or “Generate meeting summaries in Notion with one click”).

   • Templates were distributed through GitHub Gists and AI/automation-focused newsletters, giving the product credibility among technically-minded founders.
     

3. Low-cost viral experiments:
   

   • $50–$100 tests on LinkedIn and Twitter targeted startup founders and engineers with short demos of AI automations.

   • Each post highlighted one AI trick or workflow snippet, encouraging users to replicate it and share their results.

Outcome:

• FlowAI grew from 0 to 5,000 active startup users in six months without a single paid growth campaign.

• Early adopters became product advocates, sharing micro-tutorials online that drove organic signups.

• Investors noticed the technical depth and community traction, making FlowAI a sought-after AI B2B SaaS startup at seed stage.

Key takeaway: Coded, AI-first B2B products can gain traction by embedding themselves in technical communities, offering tangible “micro wins” through templates and demos, and letting users evangelize the product organically.

B2C case study

Replika (2019–2023), the AI chatbot companion, needed to grow awareness in a crowded wellness and AI apps market. They leveraged clever, low-cost tactics to become viral among tech-savvy users.

• Tactic 1: Campus & creator ambassadors: Early users, particularly students and digital creators, shared AI-generated conversations and memes from Replika on TikTok, Instagram, and Discord. This drove organic curiosity and downloads.

• Tactic 2: Micro-viral content experiments: Small $100–$200 ad campaigns tested which AI-driven stories, like “My Replika wrote me a poem” or “My AI helped me learn empathy” went viral. Winners were then amplified by social shares.

• Tactic 3: Gamified engagement hooks: Features like AI streaks, conversation badges, and social sharing were low-cost ways to make users not only come back but post about their AI experiences.

Result: Replika grew a highly engaged community of early adopters, many of whom became micro-influencers, sharing the AI experience with zero large-scale ad spend. Their growth leveraged virality, community, and AI novelty—turning low-cost tactics into exponential reach.

More B2B tips

• Engage in LinkedIn communities, Slack groups, and industry forums

• Create mini PR stunts: case studies, thought leadership, or niche awards.

• Micro-test campaigns targeting specific verticals or account types.

More B2C tips

• Participate in subreddits, Discord servers, TikTok trends, or niche social spaces.

• Run humorous or viral PR stunts designed for organic shares.

• Test different creative angles on ads, emails, or social posts in small batches.

Kate Busby is CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Instagram. The images are extracted from X and created by MidJourney. No names and identifying details have been changed. Subscribe to Substack to receive all articles in the “Rules of Growth” series straight to your inbox.

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4. How can we make our $1 budget work like $10?

At the pre-seed stage, almost every founder feels the pinch: $1 seems like $0.

Your goal isn’t flashy campaigns, it’s leverage.

But how can every dollar, hour, and resource work 10x harder for the growth of your audience, customer base, revenue and customer lifetime value?

Let’s explore three solutions: automation, prioritization and runway extension.

Classic problems

- Burning $5k/month on paid ads too early.
- DIY-ing everything instead of leveraging AI and delegating to fractional support.
- Ignoring non-dilutive funding options.

Risks of not fixing

- You run out of cash before PMF.
- Burnout from trying to do everything manually.

Actionable plan (do this week)

1. Pick 1 paid channel and test with <$200. Track metrics carefully.

Choose metrics by type of test

1. Pick 1 paid channel and test with <$200. Track metrics carefully. Options:

2. Generate AI prompts to develop campaign copy, emails, or social posts. Aim for automation, not perfection.

3. Research 2 grants or accelerator programs and submit applications.
   
   

Steal this prompt

Act as a senior growth marketing consultant for early-stage startups. 

My startup operates in [industry/niche] and I have a limited marketing budget of [budget amount, e.g., $200] for [time frame, e.g., this month]. I want to maximize impact using AI, automation, and high-ROI growth tactics.

Please suggest strategies across three areas:

1. Paid channel experiments – small, cost-effective campaigns to test quickly.

2. AI tools for automation – ways to save time or scale marketing activities.

3. Alternative funding options – grants, competitions, or other non-dilutive funding sources suitable for a startup in my niche.

For each suggestion, include:

Expected cost or effort
Potential ROI or impact
Any caveats or risks

Also, suggest any overlooked opportunities or creative approaches I might explore given this budget and context.

These companies figured it out

B2B case study

SuperOps.ai (early days) SuperOps.ai started with minimal funds to launch a workflow automation SaaS. They focused on automating demos, customer onboarding, and reporting. Instead of paid ads, they leveraged LinkedIn outreach and co-marketing with complementary SaaS tools. This approach cut costs drastically, extended runway, and generated qualified leads before raising a seed round.

B2C case study

Lunchclub (relaunched 2023) Lunchclub relied on AI-driven matching to automate onboarding and outreach. Minimal spend went into testing paid campaigns, while organic buzz and viral loops carried adoption. By keeping operations lean, they extended runway and built a loyal user base before scaling.

More B2B tips

• Automate repetitive tasks: Use tools like HubSpot or Salesforce to automatically log customer interactions, set follow-up reminders, and segment leads. For reporting, connect your CRM or Google Analytics to dashboards (e.g., Data Studio, Looker) that refresh weekly or daily without manual work. Automate outreach emails with sequences in tools like Lemlist or Mailshake.
  

• Leverage free reach: Share expertise through webinars, speaking slots at industry events, or guest articles on partner blogs. Co-marketing partnerships—like joint webinars, whitepapers, or social posts with complementary companies—can expand your audience without paid ads.
  

• Apply for non-dilutive funding: Identify relevant grants, accelerator programs, or industry competitions. For example, tech startups can apply for government innovation grants, while SaaS businesses can pitch at growth-focused accelerators for cash or resources without giving up equity.
  

More B2C tips

• Automate marketing touchpoints: Schedule social media posts with Buffer or Later, automate email campaigns using Klaviyo or Mailchimp, and set up chatbots or community management tools to handle common customer inquiries.
  

• Encourage user-generated content: Run campaigns that invite customers to share photos, reviews, or stories using a branded hashtag. Incentivize sharing through small rewards, contests, or featuring customers on your channels to create viral loops.
  

• Boost reach without spending big: Explore micro-grants or contests to fund small campaigns, or collaborate with micro-influencers whose audience aligns with yours. Partner with local creators for content swaps, giveaways, or social challenges to amplify buzz organically.

Kate Busby is CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Instagram. The images are extracted from X and created by MidJourney. No names and identifying details have been changed. Subscribe to Substack to receive all articles in the “Rules of Growth” series straight to your inbox.

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Chapter 9 — Conclusion: Keep Selling Anyway

If you’ve made it this far, you’ve done more than most founders ever will. You’ve built something, talked to people about it, charged money for it, listened, adapted, and learned. You’ve stepped out of the comfort zone of building and into the unpredictable arena of selling.

And if at times it felt awkward, exhausting, or even mildly humiliating — good. That means you were doing it right.

Because selling, at its core, isn’t about tactics or scripts. It’s about learning how your work fits into the lives of other people. That’s the essence of entrepreneurship, understanding others so well that your product becomes a natural extension of their needs.

The Founder’s Paradox

There’s a funny thing that happens once founders start getting good at sales. They begin to see that sales and product aren’t opposites — they’re the same conversation, just happening from different sides.

Sales shows you why your product matters. Product is how you deliver that value.

When you treat them as two halves of the same system, you start to see your business as one continuous feedback loop: every sale informs what you build next, and every improvement you make opens new sales opportunities.

💡 Takeaway: Sales isn’t the opposite of building. It’s how building stays relevant.

The Myth of the “Real Seller”

By now, you’ve probably realized that you don’t need to transform into some extroverted, high-energy, suit-wearing closer to succeed. That’s a myth left over from another era — when “sales” meant pressure, charm, and manipulation.

In modern startups, the best sellers are the best listeners. They’re curious, analytical, and honest. They sound more like consultants than closers. And as a founder, you already have those skills — you’ve just been using them on code, design, or systems instead of people.

So if you ever catch yourself thinking, “I’m not a sales type,” remind yourself: you’ve been selling since the day you convinced someone to join your team, invest in your idea, or give your product a chance. You’ve been doing this all along — just under a different name.

💡 Takeaway: You don’t have to become a salesperson. You just have to stay a problem-solver.

Progress, Not Perfection

You won’t master every part of this overnight. Some weeks you’ll feel unstoppable; other weeks you’ll question everything. You’ll lose deals that seemed certain and win ones that seemed impossible.

That’s normal. Sales isn’t a straight line — it’s a series of experiments, each one teaching you something new about your market, your product, and yourself.

The real progress happens quietly, when you start recognizing patterns without even trying. When you instinctively know what questions to ask, what tone to take, when to push, and when to pause. That intuition is your reward for showing up and doing the work.

💡 Takeaway: Momentum beats mastery.

The Emotional Truth About Selling

Let’s be honest: selling can be emotionally draining. You’ll get ignored, misunderstood, and occasionally patronized. Some people will waste your time. Some will copy your ideas. But you’ll also meet people who get it — who see what you see, and get excited about where it could go. Those conversations will recharge you more than any funding round ever could.

At its best, selling is about connection. It’s one human saying to another, “I built this because I thought it might help you,” and the other replying, “Actually, yes — it does.”

That’s the moment all the rejection, awkward pauses, and early mornings make sense. It’s the moment your product stops being just yours and starts belonging to someone else, too.

💡 Takeaway: Selling is how your idea learns to live in the real world.

What to Expect Next

If your company succeeds, there will come a day when you’re no longer the one doing the demos or answering customer emails. Someone else will take over. That’s good — it means you’ve built something bigger than yourself.

But even when you’re not the one selling directly, you’ll always be selling indirectly. You’ll sell your vision to your team, your strategy to investors, your mission to partners. The skills you learned here — clarity, empathy, storytelling, persistence — will follow you everywhere.

So don’t think of this founder-led sales period as a temporary inconvenience. Think of it as your MBA in reality. It’s where you learned what no spreadsheet or accelerator could ever teach you: how markets actually behave when they meet your idea.

💡 Takeaway: Sales skills age well. You’ll use them for the rest of your career.

Looking Back: Your Founder Sales Roadmap

Let’s recap the journey you’ve just walked through:

1. Reality Check: You built it, but nobody came — so you went out and met them.
   
   

2. The Evangelical Phase: You embraced the chaos and did things that didn’t scale.
   
   

3. Mindset Makeover: You unlearned your product bias and started thinking like a listener.
   
   

4. Crafting Your Sales Story: You found words that made sense to real people.
   
   

5. Learning to Listen: You stopped pitching and started understanding.
   
   

6. Pricing Without Losing Your Mind: You learned to value your value.
   
   

7. Recording Everything: You turned random insights into repeatable knowledge.
   
   

8. Letting Go: You prepared someone else to carry the torch.
   
   

If you’ve done these things, you’re already far ahead of the curve. Most startups never make it this far because they avoid the uncomfortable parts. You didn’t.

💡 Takeaway: You don’t grow by scaling. You scale because you’ve grown.

Final Thoughts

Selling will always be a part of your job — not because you love it, but because it keeps you honest. It keeps you close to the people who matter most: your customers. It reminds you that every product, no matter how innovative, lives or dies by its ability to solve real problems for real humans.

So keep selling anyway. Not just for the revenue — for the understanding, the humility, and the empathy it builds.

Because in the end, that’s what great founders and great sellers have in common: they both spend their lives trying to make something — or someone — a little bit better than they were before.

💡 Final Takeaway: Sales isn’t a phase. It’s a mirror that reflects how well you understand the world you’re trying to change.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Chapter 8 — When to Let Go: From Founder-Led to First Sales Hire

If you’ve made it to this chapter, take a moment to appreciate how far you’ve come. You started as a technical founder who wasn’t sure how to sell. You’ve talked to real customers, refined your story, learned to listen, priced your product, and even built a small system to capture what you’ve learned.

Now, you might be wondering: How long do I have to keep doing this myself? When is it finally time to hire someone to take over sales?

It’s a good question — and an important one. Hire too soon, and you’ll waste precious time and money. Wait too long, and you’ll burn out doing a job you’re not supposed to do forever.

The trick is knowing when you’ve done enough to make sales teachable.

Why You Can’t Hire Yet (Probably)

Let’s start with the hard truth: most founders try to hire a salesperson far too early.

They think, “I’ll bring in someone who’s good at this so I can focus on the product again.” But if you haven’t already proven that your product can sell — at least in some repeatable way — you’re not hiring a salesperson, you’re hiring a translator for a language you don’t yet speak.

No salesperson, no matter how talented, can succeed in that situation. They’ll walk into uncertainty and guesswork, and when things don’t click, you’ll both end up frustrated.

💡 Takeaway: You can’t outsource what you haven’t understood.

The Three Signs You’re Ready

So when are you ready? Look for these three early indicators — they’re not perfect, but they’re surprisingly reliable.

1. You’re Hearing the Same Things Over and Over

Your customers are starting to sound familiar. The objections, the motivations, the triggers — they repeat. This means your market is starting to show patterns, and your message is resonating consistently enough that someone else could learn it.

2. You Can Describe Your Buyer Clearly

You no longer say, “It depends.” You can name your ideal customer profile with confidence — who they are, what they care about, and what drives them to act.

3. You Have a Documented Process

You’ve written down how you find leads, what your discovery calls look like, how you demo, how you follow up, and what pricing works. It doesn’t have to be pretty — it just has to be repeatable and actionable.

When those three signs align, congratulations: you’re ready to teach someone else how to do what you’ve been doing manually.

💡 Takeaway: You’re ready to hire when selling feels predictable — not chaotic.

The Wrong Reasons to Hire

Before you post that “Sales Lead” job, check your motivation.
Here are a few wrong reasons founders hire too early:

• “I hate selling.” (Understandable, but not fixable through delegation.)
  
  

• “We need to scale fast.” (Scale what, exactly? Unproven assumptions?)
  
  

• “Investors expect us to have a sales team.” (Investors expect results — not org charts.)
  
  

Hiring out of discomfort or pressure usually leads to bad fits. You’ll either hire someone too senior who expects structure you don’t have, or someone too junior who needs structure you can’t yet provide.

💡 Takeaway: Never hire a salesperson to solve an emotional problem.

The Right Kind of First Sales Hire

When the time is right, the kind of person you hire matters more than their title. Your first sales hire isn’t just a “closer.” They’re a builder — someone comfortable with ambiguity, testing hypotheses, and iterating fast.

Here’s what to look for:

• Curiosity: They ask “why” more than they pitch.
  
  

• Adaptability: They can handle the messiness of a product still evolving.
  
  

• Ownership: They take initiative and don’t wait for perfect processes.
  
  

• Feedback orientation: They enjoy being part of shaping the go-to-market, not just executing it.
  
  

Avoid people who need rigid systems or are used to selling from polished brand recognition. Early sales are raw and improvisational — you need someone who can thrive in that.

💡 Takeaway: Your first sales hire should be an explorer, not a bureaucrat.

How to Prepare Before Hiring

Before you hand over the keys, do your future self (and your future salesperson) a favor: organize your knowledge.

Here’s what you should have ready:

1. Your sales narrative — the story that consistently works.
   
   

2. A short customer profile — who to target, what problems they face, what words they use.
   
   

3. A lightweight playbook — steps for outreach, discovery, demo, and follow-up.
   
   

4. Examples of past calls or emails — real conversations that worked.
   
   

5. Pricing logic — why you charge what you do and what’s negotiable.
   
   

It doesn’t have to be a polished manual. It just needs to be enough for someone new to learn from your experience instead of starting from zero.

💡 Takeaway: Don’t hand off sales. Hand over understanding.

Avoiding the Founder Dropout Syndrome

When you hire your first salesperson, resist the temptation to vanish into product mode. You might think, “Finally, someone else can handle this.” Not yet. Your job shifts, but it doesn’t disappear.

You move from doing the selling to coaching the selling. Sit in on early calls. Review notes. Listen to recordings. Share insights. The goal isn’t to micromanage — it’s to transfer context.

Too many founders disappear after hiring their first rep, only to reappear months later asking why revenue hasn’t grown. Usually, it’s because they never finished the handoff.

💡 Takeaway: Hiring a salesperson doesn’t mean you stop selling. It means you start leading sales!

How to Know the Handoff Worked

You’ll know your transition from founder-led to scalable sales has succeeded when three things happen:

1. Deals close without you.
   The first time a deal closes and you weren’t in the meeting — that’s the signal you’ve created a repeatable process.
   
   

2. Language consistency.
   Your salesperson uses the same story, phrases, and positioning you developed — and it works.
   
   

3. Predictable metrics.
   You can look at the pipeline and roughly predict outcomes. No more wild swings or mystery deals.
   
   

That’s the moment you can finally take a breath. You’ve gone from improvisation to orchestration.

💡 Takeaway: You’ve succeeded when your absence doesn’t break the process.

What You’ll Still Need to Do

Even after you’ve hired your first salesperson, your job isn’t done. You’ll still be:

• Refining the product based on new feedback.
  
  

• Supporting key or strategic deals.
  
  

• Strengthening relationships with your earliest customers.
  
  

• Maintaining the culture of listening and learning that got you here.
  
  

Your role just shifts from frontline to foundation.

💡 Takeaway: The founder’s sales job never truly ends — it just evolves.

In Summary

Knowing when to let go is one of the hardest transitions in the founder’s journey. It’s not about ego; it’s about readiness.

To recap:

• Don’t hire until you’ve found repeatability.
  
  

• Look for patterns, not perfection.
  
  

• Hire for curiosity and adaptability, not polish.
  
  

• Hand over a system, not chaos.
  
  

• Stay involved until success repeats without you.
  
  

When that happens, you’ve officially graduated from “founder who sells” to “founder who built a company that sells.” And that’s one of the clearest signs of real traction.

💡 Final Takeaway: Letting go doesn’t mean stepping back — it means creating space for growth.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Listen up, dear marketers, because I’m only going to say this once: If you’re still asking ChatGPT to do everything from writing your brand strategy to generating Instagram captions to pulling competitive intelligence, you’re doing it wrong. Deeply, spectacularly wrong.

You wouldn’t ask your therapist, your bank manager, and your hungover intern the same question and expect equally useful answers, would you? (“Should I buy Bitcoin?” gets you three very different lectures.)

So why are you treating every AI model like it’s some interchangeable commodity?

Here’s the truth: The difference between a mediocre marketer and a brilliant one isn’t whether you use AI.

It’s whether you know which AI to use, when to use it, and more importantly, when to tell it to bugger off entirely.

Here’s everything you need to reach the stars.

Why This Actually Matters (And Why Your Career Depends On It)

Picture this: You’ve just used ChatGPT to draft a press release about your pharma client’s new product.

It’s eloquent, persuasive, absolutely brilliant.

You hit send. And then:

Three days later, you’re in a meeting explaining why your release claimed the drug “cures” something it only “treats,” and why you’re now facing legal action.

Or this:

You’ve asked ChatGPT to design brand assets. What you get back is bland, formulaic slop that every instinct in you screams not to share with another living soul.

The problem isn’t AI. The problem is you used a Formula One car to do your grocery shopping, then wondered why it didn’t fit in the parking space.

Every LLM has a personality, a specialty, and a dark side.

Learn, or get left behind.

The Restaurant Analogy That’ll Save Your Bacon

Think of LLMs like restaurants. You don’t go to McDonald’s for your anniversary dinner (do you?) and you don’t book Nobu for a on-the-go breakfast.

Context matters. Quality varies. Price points differ.

ChatGPT is a 3-Star Michelin restaurant — executive-friendly, intelligent approach, notoriously bad at bulk. This is your go-to for high-stakes strategic work: business strategy, topline summaries. When it’s Friday and your boss needs something brilliant by Monday, you reach for ChatGPT. When you need email variations by the hundreds, you absolutely do not touch it.

Claude is The Ritz — Elegant, precise, pathologically brand-safe. I use Claude to deliver anything that could get me fired: PR statements, regulated copy, internal communications that’ll be forwarded to the board. It’s witty without being risky, thorough without being reckless. It’s the LLM equivalent of having a very clever lawyer review your work before it goes out. The downside? It won’t give you visually striking campaign concepts or process enormous datasets at speed. Like the Ritz, it’s too exclusive to do any kind of mass production.

Gemini is Nobu — Stylish, visual, modern as hell, and they just dropped headline-worthy new features with Gemini 3.0 Pro. Brilliant for creating presentation decks, quick assets for nurturing client relationships, anything that needs to look as good as it reads. When you’re pitching and aesthetics matter, Gemini delivers. But don’t ask it to write your 40-page content strategy. That’s not what it’s built for.

Mistral and DeepSeek are Shake Shack and McDonald’s — Fast, consistent, scalable. These are your lo-fi, reliable workhorses for bulk production: ad variations, automated email sequences, social media captions at volume. They’re reliable, efficient, and absolutely not where you go for your breakthrough creative idea.

Grok is KFC — Real-time, edgy, culturally tuned in. When you need to know what’s trending on social media right now, the last conspiracy theory, or you’re building a reactive campaign around a cultural moment, Grok is your weapon. But keep it away from anything requiring regulatory approval or brand polish. It’s quick and dirty by design.

Perplexity is Sukiyabashi Jiro (of “Jiro Dreams of Sushi” fame)— Looks plain and ordinary from the outside, but the product quality is world-class. This is your research powerhouse. When you need deep factual research, market intelligence, competitive analysis, or trend validation with actual sources, Perplexity is unmatched. It’s not going to wow you with creative brilliance or come up with your next big campaign idea, but when you need to know the Truth about your market, it’s the most reliable tool in your arsenal.

The Hallucination Problem (Or: Why That Brilliant Answer Might Be Built On Lies)

Here’s what nobody tells you in the webinars: All LLMs hallucinate. Every single one.

They make things up with the confidence of a consultant who’s never worked in your category.

ChatGPT is moderately likely to invent statistics, cite studies that don’t exist, or confidently assert trends that are complete fiction. It’s creative and persuasive, which makes its lies particularly dangerous. Always fact-check.

Claude hallucinates less because it’s been trained to be cautious. It’s the safest bet for anything where accuracy matters more than creativity. But “less likely” doesn’t mean “never.”

Perplexity has low hallucination rates because it actually cites sources, but here’s the catch: if the source is rubbish, you get well-referenced rubbish. Garbage in, garbage out, just with footnotes.

Mistral and LLaMA have higher hallucination rates for factual content. They’re brilliant for pattern-based work and repetitive tasks, but terrible for anything requiring deep domain expertise or current market data.

The visual AIs like MidJourney and DALL-E hallucinate in a different way: they’ll create products that don’t exist, people who aren’t real, brand elements that were never designed. Which paradoxically is perfect for creative work.

The rule: The more creative the LLM, the more likely it is to bullshit you. Plan accordingly.

The Playbook: What To Use When

Let me make this dead simple for you.

For strategic brilliance: ChatGPT. Campaign strategy, positioning, storytelling, anything going to the C-suite. Just fact-check the data points.

For brand-safe precision: Claude. PR, regulated copy, internal comms, anything that could blow up in your face if a word is wrong.

For visual impact: Gemini for polished presentations, MidJourney for jaw-dropping creative, DALL-E for quick professional graphics (it’s not free). Pick based on whether you need “safe corporate sleek” or “stop-scrolling wowness.”

For bulk production: Mistral or DeepSeek. Email sequences, ad variations, social captions at scale. Efficiency over artistry.

For real-time trends: Grok. Social listening, reactive campaigns, cultural moment-jacking. Speed over safety.

For data and dashboards: Cohere. Structured reporting, multi-source summaries, KPI dashboards. Built for business intelligence, not creative flair.

For research and validation: Perplexity. Market intelligence, competitive analysis, trend validation with sources. Excellent for due diligence, rubbish for ideation.

The Mistakes You’re Already Making

Mistake #1: Using ChatGPT for everything. You’re wasting time and money using a Michelin-starred chef to make toast. Scale your tools to your tasks.

Mistake #2: Trusting visual AI for accuracy. MidJourney will create a stunning image of your product that looks nothing like your actual product. Use it for concepts and mood, not for specs.

Mistake #3: Not fact-checking persuasive content. The more confident and well-written the output, the more you should verify it. Eloquence is not evidence.

Mistake #4: Ignoring brand safety. Using Grok to write your pharmaceutical company’s press release is career suicide. Match the tool to the risk level.

Mistake #5: Forgetting that humans still matter. Every output needs a human who understands the brand, the market, and the stakes. AI is a tool, not a replacement for taste, audience empathy and leadership.

The Bottom Line

Here’s what separates competent marketers from brilliant ones in 2025: Knowing which tool does what, and having the discipline to use the right one for each job.

ChatGPT for strategy. Claude for safety. Gemini for visual storytelling. Mistral for scale. Grok for trends. Cohere for data. Perplexity for research.

Match the tool to the task, fact-check everything that matters, and never forget that the human in the loop is still the most important part of the equation.

Because here’s the thing:

Most of your competition still thinks AI is just ChatGPT.

Most of them are using sledgehammers for brain surgery and wondering why the results are messy.

Most of them haven’t bothered to learn the difference between tools, let alone master when to use each one.

But you? You’re reading this. You’re learning this. You’re building a capability that most senior marketers don’t even know exists yet.

That’s not mediocre. That’s smart. And in a world where everyone has access to the same technology, being smart about how you use it is your unfair advantage.

Kate Busby is CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Instagram. The images are extracted from X and created by MidJourney. No names and identifying details have been changed. Subscribe to Substack to receive all articles in the “Rules of Growth” series straight to your inbox. Save this article. Share it. Use it. And for God’s sake, stop asking ChatGPT to do your data dashboards.

Chapter 7 — Record Everything (Because You’ll Forget Everything)

If you’ve been following along, you’ve done a lot already. You’ve talked to potential customers, tested your story, adjusted your pricing, and survived the early emotional rollercoaster of selling.

Now you’re learning at a pace you probably haven’t experienced since you started building the product. And that’s great — except for one problem: you’re going to forget most of it.

Not because you’re careless, but because founder-led sales are messy and fast. You’re switching between conversations, product decisions, investor meetings, and delivery. In the middle of that chaos, it’s easy to lose track of the small but critical insights that will later define your go-to-market strategy.

That’s why this chapter is about one simple rule: record everything.

The Founder’s Memory Trap

When founders start selling, they often make the same mistake: they trust their memory. They think, “I’ll remember what that customer said,” or “That was a great objection, I’ll note it later.” And then — they don’t.

The next time they face a similar conversation, they repeat the same mistake, ask the same question, and miss the same signals.

Your brain is built for creativity, not documentation. But in sales, forgetting is expensive. Every insight you fail to capture today is an obstacle you’ll have to rediscover tomorrow.

💡 Takeaway: Your conversations are data. Treat them like assets.

Why Recording Matters

Documenting what you learn is not busywork — it’s the foundation of repeatability. It’s how you turn random wins into a playbook, and how you prepare your future team to succeed without guessing.

Here’s what systematic note-taking gives you:

• Patterns: You start seeing recurring objections, interests, and buyer types.
  
  

• Clarity: You understand which messages resonate and which confuse.
  
  

• Proof: You can back your instincts with evidence when discussing strategy.
  
  

• Scalability: You create material that will later help you onboard your first salesperson or marketing hire.
  
  

In short, recording your process turns your personal learning curve into a company asset.

💡 Takeaway: Good notes are the bridge between founder-led sales and scalable growth.

What to Capture

You don’t even need a CRM to get started. In fact, keeping it lightweight will help you actually do it. Start by tracking these essentials for every conversation:

1. Who you spoke to: Name, company, role, and how you found them.
   
   

2. Their problem: In their own words, what’s painful or inefficient.
   
   

3. Their current solution: What they’re doing today to cope.
   
   

4. Their reaction: What caught their attention, confused them, or made them skeptical.
   
   

5. Next steps: What you agreed to do — and by when.
   
   

Optionally, add:

• Objections: What they hesitated about and how you responded.
  
  

• Keywords: Phrases they used to describe the problem (these are gold for future messaging).
  
  

• Deal status: Even a simple “Active / Waiting / Lost” helps spot trends later.
  
  

You can keep this in a spreadsheet, a Notion page, or even a Google Doc. The tool doesn’t matter — the habit does.

💡 Takeaway: Don’t aim for perfection. Aim for consistency.

How to Take Notes Without Breaking the Flow

Taking notes during a call can feel awkward at first. You might worry it looks unprofessional or distracting. Here’s the secret: most people appreciate it. It shows you’re paying attention.

Just let them know:

“I might take a few notes while we talk so I don’t miss anything important.”

Then write down phrases, not paragraphs. Focus on what’s emotionally charged — things they emphasize, repeat, or complain about. Those moments reveal what truly matters.

After the call, spend five minutes adding context: what you learned, what surprised you, and what you want to test next.

💡 Takeaway: The five minutes after a call are worth more than the call itself.

Building a Simple Learning Loop

Once you have notes from a few dozen conversations, patterns will start emerging. That’s when things get interesting.

Here’s a simple weekly ritual to turn your notes into insight:

1. Review: Read through your notes once a week.
   
   

2. Tag: Highlight recurring themes — repeated objections, similar outcomes, phrases customers use.
   
   

3. Summarize: Write a short reflection: “This week I learned that X matters more than Y.”
   
   

4. Adjust: Change something in your next round of conversations — your pitch, your pricing, or your targeting — and test it.
   
   

Over time, this process will create a living document of your startup’s evolution. You’ll literally see how your understanding of the market matures.

💡 Takeaway: Learning compounds only if you capture it.

Tools That Make It Easier

You don’t need enterprise software to stay organized.
Start small with what you already use:

• Spreadsheets: Simple, flexible, and fast to update.
  
  

• Notion: Great for combining notes, tasks, and reflections.
  
  

• Granola: It records all the conversation for you and extracts a summary.
  
  

Later, as your pipeline grows, you can migrate this data into a CRM like HubSpot, or Salesforce. But for now, the goal is to build a habit, not a system.

💡 Takeaway: Tools don’t build discipline. You do.

The Story Hidden in Your Data

As your notes accumulate, you’ll begin to see the bigger picture emerge. Patterns will appear that no single conversation could reveal:

• Which customer profiles close faster.
  
  

• Which objections disappear when you frame the problem differently.
  
  

• Which channels consistently bring warmer leads.
  
  

• Which words trigger interest — and which trigger resistance.
  
  

This is when founder-led sales stops feeling like guesswork. You’re not just reacting anymore — you’re learning deliberately.

And that’s the moment your go-to-market strategy starts to take shape organically.

💡 Takeaway: Every data point is a clue. Collect enough, and the map appears.

Preparing for Your Future Sales Hire

Everything you’re documenting now will eventually make someone else’s job easier — and save you months of onboarding pain.

When you finally bring in your first salesperson or business developer, you’ll have:

• A record of what your best conversations looked like.
  
  

• A list of tested objections and effective responses.
  
  

• Clear examples of customer language.
  
  

• A pricing history and rationale.
  
  

That’s not just documentation — that’s your first sales playbook.

Most startups skip this part and wonder why their first sales hire struggles. They’re missing the raw material that turns “founder intuition” into a teachable process.

💡 Takeaway: Your notes today are your future team’s training manual.

Common Mistakes to Avoid

A few traps to watch out for as you start recording your sales process:

• Over-documenting: Don’t turn it into a novel. Keep it simple and actionable.
  
  

• Ignoring context: Numbers matter, but so does tone. Capture how people said things.
  
  

• Losing discipline: One missed entry becomes two, then ten. Keep the habit alive.
  
  

• Treating notes as archives: Review them often — they’re tools for learning, not storage.
  
  

💡 Takeaway: The best notes are the ones you actually use.

In Summary

Recording everything might sound tedious, but it’s what separates guesswork from insight. This is how you turn random founder experience into structured company knowledge — and how you prepare to scale without losing the lessons of your early hustle.

To recap:

• Write things down — always.
  
  

• Capture patterns, language, and emotions, not just facts.
  
  

• Review regularly and refine your approach.
  
  

• Use simple tools until complexity becomes necessary.
  
  

• Treat your notes as the foundation of your playbook.
  
  

You’ll thank yourself later. Because when your future sales hire asks,

“How do our best customers usually describe their problem?”
you won’t have to guess — you’ll have the answer right there, in your own words and theirs.

💡 Final Takeaway: Documentation turns intuition into strategy.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Chapter 6 — Pricing Without Losing Your Mind

If you’ve made it this far, congratulations — you’ve built something, talked to real customers, and started to learn how to sell. Now comes the part that makes even experienced founders sweat: deciding how much to charge for it.

Pricing feels uncomfortable because it sits at the intersection of logic and emotion. You can build your product with spreadsheets and frameworks, but when it’s time to talk about money, something inside you might freeze. And that’s normal. It’s not just about numbers — it’s about value, confidence, and fear.

Why Pricing Feels So Hard

When you’re early-stage, you don’t have benchmarks, reference points, or data. You’re not sure what’s “fair.” You’re terrified of charging too much and losing the deal — but you’re equally afraid of charging too little and looking cheap.

Underneath it all is a quiet imposter voice whispering:

“Who am I to ask for that much?”

That’s the wrong question. The right question is:

“What is this worth to the person buying it?”

Your price isn’t a reflection of your self-worth. It’s a reflection of the impact your product creates.

💡 Takeaway: Price the value you deliver, not the hours you’ve spent.

The Three Pillars of Early Pricing

In the beginning, your pricing won’t be perfect — and it doesn’t need to be. What matters is that it’s anchored in logic, tested in reality, and communicated with confidence.

Here’s a simple framework to think about early pricing:

1. Comparables: What do your customers currently pay to solve this problem (even if it’s with a bad solution)?
   
   

2. Impact: How much money, time, or pain do you help them save or gain?
   
   

3. Positioning: Where do you want to sit in the market — the cheaper, faster option or the premium, more capable one?
   
   

Those three inputs give you a range. Within that range, your job is to pick a number and test it — not to find the mythical “perfect price.”

💡 Takeaway: Early pricing is a hypothesis, not a verdict.

Start Simple

When you’re early, your goal isn’t to optimize revenue. It’s to learn what customers are willing to pay and why. That means your first pricing model should be simple enough to explain in one sentence. If you can’t describe it clearly, it’s too complicated.

Avoid the temptation to offer 10 pricing tiers or endless “enterprise” customizations. Those will come later. Right now, you just need to answer one question:

“Can I charge money for this — and can I do it again?”

💡 Takeaway: A confusing price is worse than a low one.

The Fear of Asking

Let’s address the elephant in the room: saying your price out loud.

You’ll know you’re about to do it when your heart rate doubles and your voice gets slightly higher. It’s fine. It happens to everyone the first few times.

Here’s the trick: say your price calmly, then stop talking. Don’t justify it. Don’t start discounting mid-sentence. Don’t explain your cost structure or your roadmap. State it, then wait.

That pause after you say the number will feel eternal. Resist the urge to fill it. If the other person is interested, they’ll respond. If they hesitate, that’s your chance to learn, not to panic.

💡 Takeaway: Say the price. Then shut up.

Discounts: The Startup Drug

Discounts are like caffeine. One cup sharpens your focus; five cups make you anxious and jittery.

A small discount to get your first few customers on board is fine. But if you start using discounts as your default tactic, you’re signaling that your price — and your confidence — are negotiable.

Every time you discount, you’re training your market to expect it. And the customers you attract that way are often the least loyal ones.

Instead of cutting price, focus on adding value. If someone says, “That’s too expensive,” respond with:

“Help me understand what you’re comparing it to.”
That question will tell you whether you have a pricing problem or a communication problem. Usually, it’s the latter.

💡 Takeaway: Discounts solve anxiety, not objections.

When to Charge Less (and When to Say No)

There are times when it makes sense to lower your price — but only if you’re getting something valuable in return. For example:

• A pilot project that gives you public results or testimonials.
  
  

• An early adopter willing to act as a design partner.
  
  

• A customer in a strategic vertical you want to understand.
  
  

In those cases, you’re not discounting — you’re trading value. Just make sure that trade is explicit and limited in time.

If someone simply wants your product cheap because “you’re new,” it’s okay to say no. Early customers set the tone for your brand. The wrong customer at the wrong price can slow you down more than losing the deal ever would.

💡 Takeaway: You can’t build a premium brand on bargain-basement habits.

Finding Your First Price

Here’s a practical way to set your first price without getting stuck in analysis paralysis:

1. Write down what you think your product is worth to a typical customer.
   
   

2. Cut that in half. That’s your comfort zone.
   
   

3. Double it. That’s your courage zone.
   
   

4. Start somewhere in between — then test both sides.
   
   

The truth will emerge quickly.
If everyone says “yes” instantly, you’re too cheap.
If everyone says “no” without discussion, you’re too high.
If you get a mix of reactions and a few customers ask thoughtful questions — congratulations, you’re probably in the right range.

💡 Takeaway: If nobody flinches at your price, it’s too low.

Price and Positioning Go Hand in Hand

Your price isn’t just a number — it’s a signal. It tells the world where to place you in their mental map.

If you’re significantly cheaper than everyone else, people will assume your product is simpler, riskier, or less capable — even if it’s not. If you’re much more expensive, they’ll expect a clear reason: exceptional results, white-glove service, or unique functionality.

The goal isn’t to undercut; it’s to align price with perception. If your product creates real value, your price should reflect that confidently.

💡 Takeaway: Cheap is a strategy — just make sure it’s yours. In other words: if you’re going to compete on price, do it on purpose — not by accident or insecurity.

Communicating Value Simply

When discussing pricing, avoid jargon like “ROI” or “synergy.” Instead, talk in human terms:

• “You’ll save 10 hours a week.”
  
  

• “You’ll reduce failed transactions by 30%.”
  
  

• “You’ll onboard new users in half the time.”
  
  

People understand time and results. They don’t care about “efficiency metrics.”

If you can link your price to a clear, specific outcome, it no longer feels arbitrary — it feels fair.

💡 Takeaway: The clearer the value, the calmer the pricing conversation.

When to Raise Prices

As you gain customers, confidence, and results, revisit your pricing regularly. If your product has improved, your reputation has grown, or your customers are getting significant value, it’s time to adjust.

Founders often wait too long to raise prices out of fear — fear of losing customers or breaking momentum. But underpricing is a silent killer. It eats your margins, your motivation, and your ability to invest in growth.

Raising prices doesn’t mean being reckless. It means aligning your price with the reality of your value.

💡 Takeaway: You can’t scale sustainably on yesterday’s pricing.

In Summary

Pricing is emotional before it’s rational. It’s as much about psychology as it is about math. Your goal isn’t to get it perfect — it’s to get it moving.

To recap:

• Price for value, not effort.
  
  

• Keep it simple and testable.
  
  

• State your price with confidence — and silence.
  
  

• Trade value, don’t give discounts.
  
  

• Treat pricing as a living experiment.
  
  

You’ll know you’ve reached maturity in your pricing when you stop apologizing for it. When you can say, calmly and clearly, “This is what it costs,” and the prospect nods — even if they say no — you’ve crossed an invisible line.

Because pricing, at its core, is just a reflection of one thing: belief in your own value.

💡 Final Takeaway: Your price tells the world how seriously to take you. So set it like you mean it.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Chapter 5 — Learning to Listen (and Shut Up)

By now, you’ve accepted that you have to sell, started doing the work that doesn’t scale, and built a clearer story about what you offer. Now comes the hardest part for most founders — especially technical ones: learning to listen.

This might sound simple, even obvious. But in practice, it’s one of the hardest habits to build. Most founders love to talk about their product. After all, it’s the result of their hard work, late nights, and conviction. The temptation to explain everything — every feature, every design decision, every “why” — can be overwhelming.

But the truth is this: the more you talk, the less you learn.

Why Founders Struggle to Listen

The challenge isn’t ego (well, not only that). It’s energy. You’ve been living inside your product for so long that you naturally want to share its brilliance with others. You want them to see what you see.

The problem is that customers rarely follow that path. They’re not there to admire your creation; they’re there to solve their own problems. And if you spend too much time pitching, you’ll miss the cues that tell you what those problems really are.

In early-stage selling, talking is tempting, but listening is leverage.

💡 Takeaway: You already know your product. What you don’t know — and need to learn — is your customer.

The Goal of Every Conversation

The purpose of an early sales conversation isn’t to impress someone. It’s to learn something.

You’re trying to uncover:

• What problems they actually have.
  
  

• How they describe those problems.
  
  

• How they’ve tried to solve them before.
  
  

• What would make them care enough to take action now.
  
  

Every question you ask should bring you closer to understanding whether your product fits into their world — and how.

Approach it like an investigation. You’re not there to perform. You’re there to collect clues.

💡 Takeaway: Your job isn’t to convince — it’s to understand.

How to Ask Questions That Actually Work

There’s an art to asking good discovery questions. Too vague, and you’ll get useless answers. Too specific, and you’ll bias the response. The sweet spot is open, clear, and neutral.

Here are some examples that work well:

• “Can you walk me through how you handle this today?”
  
  

• “What’s the most frustrating part of that process?”
  
  

• “If you could wave a magic wand, what would you want to fix first?”
  
  

• “Who else is affected when this doesn’t work?”
  
  

• “What happens if nothing changes in the next few months?”
  
  

Notice what these questions have in common: they’re curious, not leading. They create space for the other person to talk — and for you to listen.

💡 Takeaway: Ask questions that make people think, not defend.

The Power of Silence

Silence is uncomfortable — which is exactly why it works.

When you pause after asking a question, the other person will often fill the space with what they really think. Those extra few seconds are where the truth lives — the part they didn’t plan to say.

Train yourself not to rush in. Let the silence do some of the work. You’ll be amazed how often the most valuable insight comes right after you stop talking.

💡 Takeaway: Silence is not awkward. It’s your most underrated tool.

Listening for Emotion, Not Just Information

Good sellers don’t just hear words; they notice energy. When someone’s tone changes, when they hesitate, when they repeat a phrase — that’s your signal. Those moments often point to something deeper than what’s being said!

If a prospect casually mentions, “Yeah, that’s always been a bit of a pain,” stop and explore it. That’s not a throwaway comment — it’s an open door. Ask, “Tell me more about that.”

Behind every emotional cue is a problem that matters. And problems that matter are where deals begin.

💡 Takeaway: Where emotion appears, opportunity lives.

Don’t Be a Therapist — Be a Translator

Listening doesn’t mean turning every call into a therapy session. Your goal isn’t to nod sympathetically while your prospect vents. It’s to translate what you hear into actionable insights that shape how you position your solution.

As they describe their struggles, try to frame their words into your structure:

• What’s the root cause of this pain?
  
  

• How urgent is it?
  
  

• What have you already tried?
  
  

Once you can articulate their problem better than they can, they’ll start to see you as a trusted guide rather than a vendor. That’s when selling starts to feel less like persuasion and more like partnership.

💡 Takeaway: You earn trust by showing understanding, not by showing off.

Taking Notes (Properly)

In early-stage sales, your notes are worth more than your CRM. Every conversation teaches you something — not just about that one prospect, but about your market as a whole. So write it down.

Don’t just capture facts. Capture phrasing. The words your customers use to describe their pain are often more powerful than anything you could invent. Use those same words later in your pitch, your website, and your deck. They’ll instantly sound more natural, because they’ll come directly from your audience.

💡 Takeaway: Your customers are writing your messaging for you. Listen carefully.

When to Talk About Your Product

Here’s one of the biggest surprises for most founders: the best time to talk about your product is later than you think.

If you start pitching too early, you risk missing the context. Instead, wait until you’ve fully understood the customer’s problem. Only then connect it to what you’ve built.

You’ll notice the shift — when they start asking you questions like:

• “How would that work for us?”
  
  

• “Can you show me how that looks?”

That’s your invitation to talk about the product. You’ve earned the right to pitch because you’ve listened first.

💡 Takeaway: Pitch when they’re curious, not when you’re eager.

Listening as a Competitive Advantage

Most companies don’t listen well. They talk in slogans, automate every interaction, and call it “engagement.” That’s why real listening feels rare — and valuable.

When you truly listen to customers, you stand out. You learn faster, you adapt better, and you build stronger relationships. People remember who paid attention.

Even later, when you hire a sales team, this culture of listening will remain one of your biggest differentiators. It will influence how you design, market, and grow.

💡 Takeaway: In a noisy market, the best way to be heard is to listen.

In Summary

Listening sounds easy, but it’s the foundation of everything else you’ll do in sales. When you stop talking and start observing, you’ll uncover insights that no data dashboard could ever show you.

To recap:

• The less you talk, the more you learn.
  
  

• Ask open, neutral questions.
  
  

• Use silence strategically.
  
  

• Listen for emotion as much as facts.
  
  

• Capture customer language and reuse it.
  
  

• Pitch only after you understand the problem.
  
  

You’ll know you’re getting good at this when customers start saying things like:

“That’s exactly what I’ve been struggling with.”
or
“You just described our situation perfectly.”

At that moment, you’re not selling anymore — you’re connecting.
And connection is where all great sales begin.

💡 Final Takeaway: Listening is the shortest path to relevance — and relevance is what makes people buy.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Chapter 4 — Crafting Your Sales Story

You’ve accepted that you have to sell. You’ve started talking to people, listening, and learning. Now comes the next big challenge: explaining what you do in a way that makes sense to someone who doesn’t live inside your head.

Technical founders often struggle here. You know your product better than anyone, but that knowledge can work against you. You’ve spent months (maybe years) thinking about features, design decisions, and integrations — all the intricate details that make your product unique. But customers don’t buy details. They buy outcomes.

This chapter is about learning to speak their language. Not the language of frameworks, APIs, or product specs — but the language of value.

The Problem with Explaining What You Do

Ask a technical founder what their startup does, and you’ll often get something like this:

“We’ve developed a machine-learning platform that optimizes edge computing workflows by integrating predictive analytics across IoT ecosystems.”

Now, ask the same founder what problem it solves, and there’s a pause.

It’s not that the founder doesn’t know — it’s that they’re explaining the how, not the why.
Customers don’t wake up thinking about predictive analytics or IoT ecosystems. They wake up thinking, “My operations are too slow,” or “Our costs keep rising.”

So your job isn’t to explain how clever your product is. It’s to connect the dots between your cleverness and their daily headaches.

💡 Takeaway: If your customer has to ask, “So what does that mean for me?”, you’re not done crafting your story yet.

From Product to Problem

The easiest way to build a sales story that works is to flip your perspective. Instead of starting with your product, start with your customer’s world.

Ask yourself:

• What’s the pain they feel most acutely?
  
  

• What’s frustrating them about the way things work today?
  
  

• What do they want more of — or less of?
  
  

Once you understand that, your product becomes the bridge between their problem and a better future.

Let’s take an example. Suppose your startup has built a new analytics dashboard for industrial machines. You could say:

“We use AI to collect and analyze sensor data in real time.”

Or you could say:

“We help plant managers spot machine failures before they happen, so they can avoid costly downtime.”

One describes technology. The other describes impact. Guess which one your customer cares about?

💡 Takeaway: Customers don’t buy features. They buy better versions of themselves.

The Simple Story Framework

You don’t need a marketing degree to tell a compelling story. You just need structure.
Here’s a simple, founder-friendly framework that works across almost any product:

1. The Problem: What’s broken or painful in your customer’s world?
   
   

2. The Impact: What happens if they do nothing?
   
   

3. The Shift: What’s changed that makes your solution relevant now?
   
   

4. The Solution: How do you fix it — simply and clearly?
   
   

5. The Proof: What evidence do you have that it works?
   
   

6. The Payoff: What’s the benefit — time saved, money earned, frustration avoided?
   
   

This structure works because it mirrors how humans process stories: we respond to tension, change, and resolution. Your customer should recognize themselves in the story you tell — not as a spectator, but as the protagonist.

💡 Takeaway: You’re not the hero of the story — your customer is. You’re the guide who helps them win.

Learning to Speak Human

One of the hardest habits to break for technical founders is speaking in abstract or overly precise terms. Precision is great for debugging, but terrible for storytelling.

For example:

• Instead of “data normalization,” say “getting your data to speak the same language.”
  
  

• Instead of “predictive maintenance,” say “fixing things before they break.”
  
  

• Instead of “automated onboarding workflows,” say “getting new users up and running in minutes.”
  
  

Clarity beats sophistication every time. Your audience isn’t dumb — they’re just busy. The clearer you are, the faster they understand the value.

💡 Takeaway: If a smart 12-year-old can’t explain what you do after hearing it once, you’re not being clear enough.

How to Test Your Story

You’ll know your story works when you start hearing the same reaction again and again — “That makes sense.” Until then, treat every conversation as an experiment.

Here’s how to test and refine your narrative:

1. Record what lands. Notice which parts of your explanation make people nod or lean forward.
   
   

2. Watch for confusion. If someone furrows their brow or asks “Wait, how does that work?”, that’s your cue to simplify.
   
   

3. Listen for echoes. When customers start describing your product in their own words — and those words sound like your pitch — you’ve nailed it.
   
   

The best stories evolve. Don’t get attached to your first version. You’ll rewrite it many times as you learn more about your customers’ priorities and language.

💡 Takeaway: Your story isn’t written in slides. It’s written in conversations.

Using Stories, Not Stats

Founders often overestimate the persuasive power of numbers. They’ll pack their pitch with percentages, benchmarks, and metrics. While those are useful later, they rarely move people at the start. Numbers tell us what happens, words tell us what those numbers really mean.

Humans make decisions emotionally first and rationally second. That means a real customer story — a concrete example of someone who solved a painful problem using your product — is far more powerful than a slide full of data points.

For example:

“One of our customers used to spend two days a week compiling reports manually. With our platform, they do it in under an hour.”

That’s not a case study; that’s a picture. And pictures stick.

💡 Takeaway: Stories create memory. Stats only confirm belief.

The Role of Proof

Even in early-stage selling, you’ll need some form of proof to make your story credible.
That proof doesn’t have to be a long list of logos or a published case study. It can be as simple as:

• A testimonial from an early user.
  
  

• A pilot result, even if it’s small.
  
  

• A before-and-after metric you measured yourself.
  
  

The goal isn’t to impress — it’s to reassure. Your prospects need to feel that someone else has tried this before and benefited. It’s social validation, not statistical significance.

💡 Takeaway: Proof builds trust faster than polish.

Evolving Your Story Over Time

Your sales story isn’t static — it evolves as your company grows and your market matures.
In the beginning, it’s about vision and possibility. Later, it becomes about results and scale.

At first, you might say:

“We’re helping small teams automate what used to take days.”

Later, you might say:

“We help organizations save hundreds of hours each month by automating their workflows.”

The difference is subtle but important. The first speaks to early adopters who are willing to take a chance; the second speaks to pragmatic buyers who want evidence. You’ll shift naturally from one to the other as your proof points grow.

💡 Takeaway: Early stories sell belief. Later stories sell results.

In Summary

Crafting your sales story is about empathy, not eloquence. You’re not trying to sound impressive — you’re trying to sound relevant.

When you speak in your customer’s language, they stop seeing your product as a novelty and start seeing it as a solution. That’s when real traction begins.

To recap:

• Lead with problems, not features.
  
  

• Speak in clear, concrete terms.
  
  

• Make your customer the hero.
  
  

• Use stories to make the value tangible.
  
  

• Keep testing and refining as you go.
  
  

Remember: a good story doesn’t just explain what you do — it helps others believe in it. And belief, more than logic or features, is what turns interest into action.

💡 Final Takeaway: The best sales story is the one your customers start telling for you.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Chapter 3 — Mindset Makeover: Unlearning Everything You Know

Selling for the first time as a founder isn’t just about learning new skills — it’s about unlearning old habits.

The mindset that makes you a great builder can make you a terrible salesperson. You’re used to solving problems logically, optimizing systems, and aiming for precision. Sales, on the other hand, is gloriously imprecise. It lives in the world of human emotion, imperfect communication, and unpredictable timing.

That’s not bad news — it’s just different physics. To succeed in this phase, you have to shift how you think.

Here are some of the key mental adjustments that will help you navigate this transition from builder to seller.

1. From Scarcity to Plenty

Most founders start out treating every lead like it’s the last one on Earth. They hold onto conversations that clearly aren’t going anywhere, just in case. They send follow-up after follow-up, even when the other side has gone silent. They treat every prospect like a once-in-a-lifetime opportunity.

But this scarcity mindset does more harm than good. It drains your energy, and stops you from focusing on the opportunities that actually matter.

Here’s the truth: in most markets, there are plenty of potential customers. If one conversation isn’t progressing, it’s not a failure — it’s information. The goal isn’t to close every deal; it’s to identify which deals are worth pursuing now and which ones can wait.

Adopt a mindset of abundance: “If not this one, then the next.” That doesn’t mean being careless — it means being selective. Respect your time as much as you respect your prospect’s.

💡 Takeaway: The world is full of potential customers. Spend your time with the ones who want to spend theirs with you.

2. From Perfection to Activity

As a founder, you’ve probably been told to “think before you act.” In product development, that’s wise advice. In sales, it’s a trap.

If you overthink every email, every demo, and every message, you’ll spend more time preparing than actually selling. Early sales are a game of volume and momentum — the more conversations you have, the faster you learn.

You don’t need the perfect pitch or the perfect shiny Sales Deck. You need…ten imperfect conversations that teach you something new.

This is not an excuse for sloppiness, but a call to action. Stop polishing; start talking.

Send the email. Make the call. Run the demo. Then adjust based on what you learn. You can’t iterate on silence.

💡 Takeaway: Progress beats perfection. Activity is your best teacher.

3. From Politeness to Directness

In everyday life, we often dance around uncomfortable topics to stay polite. We hint, we suggest, we avoid being too forward. In sales, that doesn’t work.

You have limited time, and so do your prospects. Your job is to get to the truth — quickly, respectfully, and clearly. That means asking direct questions:

• “Is this a real priority for you right now?”
  
  

• “Who else would be involved in the decision?”
  
  

• “If this problem remains unsolved, what happens next quarter?”
  
  

These are not pushy questions. They’re professional ones. They show that you respect the other person’s time and want to understand whether it makes sense to keep talking.

Being direct also means being confident enough to ask for the sale when the time comes. Not with pressure, but with clarity: “I think we can solve this for you — should we move forward?”

💡 Takeaway: Clarity is kindness. Be direct, not pushy.

4. From Deep Relationships to Many Light Ones

When you’re used to working in small, tight-knit teams, you naturally invest deeply in relationships. Sales requires a different rhythm. You’ll be having dozens of conversations at once, often with people you’ve only just met.

At first, this can feel shallow — like you’re speed-dating for business. But this is how pipelines are built. Each relationship starts as a small spark; only a few will grow into meaningful partnerships. Your job is to light many matches and see which ones catch.

To stay organized, keep notes. Track who you spoke with, what they said, and what the next step is. Over time, you’ll build a living map of your market — one conversation at a time.

💡 Takeaway: In early sales, depth comes later. Start wide.

5. From Fear to Expertise

If you’ve never sold before, your first few conversations will probably feel awkward. You’ll worry about saying the wrong thing, asking the wrong question, or looking inexperienced. That’s normal — and temporary.

Embrace the suck: the antidote to fear is expertise. The more you understand your customer’s world, the more confident you’ll become in speaking their language. Read what they read. Follow the conversations they’re having online. Learn about the challenges that shape their day.

You don’t need to know everything. You just need to know enough to be helpful. Over time, this builds authority — not because you’re pretending to be an expert, but because you genuinely understand the terrain.

When you speak from expertise, confidence follows naturally.

💡 Takeaway: Fear fades as knowledge grows.

6. From Privacy to Transparency

In most jobs, your work is relatively private. You write code, design features, or analyze data quietly until you’re ready to show the result. In sales, everything is visible — and immediate.

Your calls, your emails, your metrics, your wins and losses — all of it can be tracked, shared, and scrutinized. For a founder, this can feel exposing at first. But transparency isn’t the enemy; it’s an accelerator.

Recording what you do and sharing what you learn helps the entire organization grow. It also builds accountability — for yourself and, eventually, for your future team.

Start documenting early: notes from calls, reasons for wins and losses, customer objections, and recurring themes. These records will later become gold when you’re onboarding your first salesperson or refining your pitch.

💡 Takeaway: Transparency turns individual learning into organizational knowledge.

7. From Art to Math

When people think of sales, they imagine charisma and persuasion. While those help, sales at its core is a numbers game. There’s art in the conversation, but the engine that drives it is math.

You’ll need to start thinking in terms of ratios:

• How many emails or calls lead to a meeting?
  
  

• How many meetings turn into proposals?
  
  

• How many proposals close?
  
  

These ratios tell you where to focus. If your close rate is high but meetings are rare, you have a lead generation problem. If you book lots of meetings but rarely close, your narrative might be off.

Tracking these numbers doesn’t make you robotic; it makes you effective. And the earlier you start, the more clarity you’ll have when you eventually build a team.

💡 Takeaway: Sales is a system. Learn the math, not just the story.

8. From Ego to Learning

Finally — and perhaps most importantly — selling as a founder requires humility. You will get things wrong. Often. You’ll misjudge interest, stumble through demos, and hear “no” more times than you’d like.

That’s not failure; that’s data. Every “no” teaches you something about what your market values, how people make decisions, and how your product fits (or doesn’t yet fit) into their world.

Approach sales as an ongoing experiment. Be curious, take notes, and resist the urge to defend your product when someone criticizes it. Listen instead — because that criticism is usually a map to your next iteration.

💡 Takeaway: Ego resists feedback. Learning depends on it.

Putting It All Together

The transition from founder to seller isn’t about personality; it’s about perspective. You’re learning a new way to solve problems — not through code or design, but through conversation, empathy, and iteration.

When you adopt these new mindsets, selling stops feeling like a foreign language. It becomes another form of problem-solving — one that connects the dots between your work and the world it’s meant to serve.

You’ll notice the shift when:

• You stop trying to convince and start trying to understand.
  
  

• You stop fearing rejection and start craving feedback.
  
  

• You stop optimizing for perfection and start optimizing for movement.
  
  

That’s when you’ll realize that sales isn’t a separate discipline after all — it’s just another way of building.

💡 Final Takeaway: To sell well, you don’t need to change who you are — you just need to update your mental software.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Chapter 2 — The Evangelical Phase: Doing Things That Don’t Scale

If the first realisation is accepting that nobody will come just because you built it, this chapter is about what to do next — the part where you roll up your sleeves and start talking to the market one conversation at a time.

This is where most founders hesitate. You’ve already done the hard part (or so you think): you’ve built the product, maybe launched it, maybe even posted about it on LinkedIn. But customers aren’t appearing out of thin air, and suddenly, you’re faced with the task of selling — directly, manually, person by person.

It feels unscalable because it is. And that’s exactly what makes it valuable.

Why “Unscalable” Is the Right Strategy (For Now)

Early-stage sales are inherently inefficient. You’ll chase leads that go nowhere, run demos that don’t convert, and spend hours on conversations that don’t result in revenue. It will feel like you’re wasting time — but you’re not. You’re collecting the raw material that every future sales process will be built on.

This is what I call the evangelical phase: the period when you’re personally spreading the gospel of your product to people who don’t yet know they need it. You’re not scaling; you’re exploring. You’re identifying which parts of your story resonate and which ones fall flat. You’re listening for patterns, language, and emotions — the kind of insights that no spreadsheet can give you.

At this point, your most important KPI isn’t ARR. It’s learning velocity.

💡 Takeaway: If it feels unscalable, you’re probably doing it right.

The Founder’s Fieldwork

Think of this phase as your market’s equivalent of field research.
You’re not behind a dashboard looking at metrics — you’re out in the wild, talking to humans.

That means picking up the phone, scheduling calls, walking into offices, or sending cold emails that you write yourself. It’s slow and personal. But this is how you learn the nuances of your buyers’ reality — their workflow, their pain points, their motivations, and the language they actually use.

A few examples of what this might look like in practice:

• Spending an afternoon with a potential customer just to understand how they currently solve the problem.
  
  

• Offering to run a free or low-cost pilot in exchange for honest feedback.
  
  

• Writing every follow-up manually because each conversation reveals new insight.
  
  

• Keeping a personal spreadsheet of every interaction and what you learned.
  
  

This is the kind of work that would never make economic sense at scale — but it’s how every successful sales motion begins.

💡 Takeaway: Before you can automate anything, you have to understand it deeply.

The Trap of Imitating Big Companies

One of the most common mistakes founders make at this stage is trying to look “professional” too soon. They copy what established companies do — automated outreach, rigid funnels, metrics dashboards — and end up skipping the learning they actually need.

Here’s the problem: those big-company tactics work after you’ve figured out who you’re selling to and why. At this stage, you’re still in search mode, not execution mode. You don’t need scale; you need clarity.

So resist the urge to:

• Build a complex CRM before you’ve closed your first handful of deals.
  
  

• Hire an SDR to “fill your pipeline.”
  
  

• Buy expensive marketing automation tools.
  
  

None of that will help until you’ve had enough real conversations to know what kind of leads you actually want.

Instead, keep it manual, messy, and personal. The unscalable things you do now will later become the foundation for the scalable processes that follow.

💡 Takeaway: Don’t copy mature companies. They’re optimizing for efficiency. You’re optimizing for discovery.

The Value of Proximity

In this phase, proximity to your customers is everything. The more direct your contact, the faster you’ll learn.

Go visit them. Sit in their office. Watch them use your product. See what confuses them, what excites them, what they ignore. These observations are worth far more than a polished survey or a product analytics report. They give you real-world context — the kind that helps you refine not only your sales pitch but also your roadmap and priorities.

When possible, do live demos instead of sending links. Don’t rely on a pitch deck to do the talking. Ask questions, take notes, and treat every interaction as a data point in your ongoing experiment.

Yes, it takes time. Yes, it feels inefficient. But there’s no faster path to understanding your customer than sitting next to them while they try to use what you’ve built.

💡 Takeaway: Real insight comes from proximity, not analytics.

Manual Work as an Investment

Many founders see unscalable work as wasted effort. In reality, it’s an investment — in knowledge, credibility, and relationships.

When you personally onboard a customer or build a custom workaround for them, you’re not just being “nice.” You’re creating a feedback loop that feeds directly into your product and positioning. You’re also signaling that you care enough to learn, which builds trust and advocacy.

Later, when your company scales, you’ll have playbooks for how to replicate these experiences through processes and people. But for now, you’re writing those playbooks yourself.

💡 Takeaway: Every unscalable action you take now writes the manual for your future team.

Balancing Passion and Discipline

During this phase, enthusiasm can be both your strength and your trap. It’s natural to be excited about your product — you’ve spent months or years building it. But too much enthusiasm can make you talk when you should be listening.

Customers don’t care how clever your code is or how advanced your algorithms are. They care about what your product does for them. That’s why your primary role now isn’t to pitch, but to listen deeply — to understand their pain better than they can describe it.

Approach each conversation like a journalist investigating a story: ask open questions, follow curiosity, and let silence do some of the work. Your goal is not to get them to say “yes.” It’s to uncover what would make them say “yes” — now or later.

💡 Takeaway: Passion opens doors; listening keeps them open.

Doing the Work Yourself

There’s no shortcut for this phase. If you try to outsource it, you’ll end up with filtered feedback — and filtered feedback is worse than none at all.

When you, as the founder, handle the first sales conversations, you hear the raw truth. You learn what customers really think — not what they tell an intermediary. You start noticing subtle cues, recurring words, and emotional triggers that will later shape your brand, your messaging, and your roadmap.

You’ll also develop empathy for the people you’re trying to serve, and that empathy will become a competitive advantage long after you’ve hired a sales team.

💡 Takeaway: Outsource tasks, not understanding.

Redefining Success During This Phase

It’s important to reset your expectations. You won’t be “closing deals” every week, and that’s fine. Success here isn’t measured in revenue — it’s measured in insight.

Ask yourself:

• What did I learn about my market this week that I didn’t know before?
  
  

• What messaging triggered interest, and what fell flat?
  
  

• Which prospects leaned in, and why?
  
  

If you can consistently answer those questions, you’re progressing faster than you think. The goal isn’t volume — it’s clarity. You’re mapping the terrain before building the highway.

Over time, these small wins compound. You’ll start to recognize familiar patterns: the customer segments that get it right away, the ones that never will, and the conversations that consistently lead to next steps. That’s when you’ll know you’re ready to start thinking about scale.

💡 Takeaway: Progress at this stage is measured in clarity, not cash.

In Summary

The evangelical phase is not glamorous. It’s not efficient. It won’t look impressive on a slide deck. But it’s where real traction begins.

By doing things that don’t scale, you’re learning faster than your competitors. You’re building a deeper understanding of your market and forming the habits that will shape how your company grows.

And most importantly, you’re earning the right to scale later — because you’ll actually know what you’re scaling.

So embrace the mess. Take every call, follow every lead, and treat every conversation as a lesson. This isn’t busywork; it’s the groundwork for everything that comes next.

💡 Final Takeaway: You have to do the work that doesn’t scale before you can build the business that does.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Introduction

Over the last few months, I’ve been mentoring startups in incubation and acceleration programs.

Most of these teams are led by brilliant technical founders who have built something genuinely impressive. Their products are solid, sometimes even remarkable. But when we start talking about what comes next, it quickly becomes clear that their biggest challenge isn’t about refining the product—it’s about learning how to sell it.

The programs I support are generally designed to help founders prepare investor materials: pitch decks, executive summaries, financial models. Yet, more often than not, the real work should start much earlier—with understanding how to take their product to market and talk to real customers.

That’s why I often end up shifting the conversation from “How do we raise money?” to “How do we make money?” In other words: how do we sell?

I’ve come to believe that for most early-stage startups, especially those led by technical founders, the first sales motions are crucial. It’s where assumptions are tested, narratives are challenged, and reality replaces theory. And while it might feel uncomfortable, it’s also where a startup truly begins to understand its market—and itself.

This article was born out of that experience. You can think of it as a roadmap for founders before their first sales hire—a practical guide you can come back to whenever you need direction while navigating your first customer conversations, experiments, and deals.

If you’re a technical co-founder with limited time, limited budget, and limited selling experience, this is written for you. You don’t need to become a professional salesperson. You just need to learn how to lead the first sales motions until the company is ready to scale that function.

The goal here is to make the process of selling less mysterious, less intimidating, and—occasionally—almost enjoyable.

Let’s Be Honest About Sales

If you’re new to sales, your perception of it might be shaped by clichés: pushy people, forced smiles, and endless follow-ups. The truth is, early-stage selling looks nothing like that.

At this stage, sales is not about closing deals—it’s about learning. It’s about discovering who your customers really are, what they struggle with, and how your product fits into their world. Each conversation becomes an opportunity to refine your message and your product at the same time.

That’s why, before hiring anyone to sell for you, you need to do it yourself.

As a founder, at this stage you’re the bridge between what’s being built and what the market actually needs. You can’t skip this step. If you hire someone too early, hand them a product still in motion, you’ll likely watch both struggle to make progress. It’s not that the hired salesperson is bad—it’s that you haven’t yet learned how the product should be sold.

So, if you’re still refining your value proposition, identifying your ICP, or searching for product-market fit, selling isn’t a job you can delegate. It’s part of your own discovery process.

The Good News

If sales feels like a foreign language, you’re not alone—and it’s not an innate talent. It’s simply another skill you can learn.

You’ve already learned to code, design, build, or lead a team. Selling is just another domain of problem-solving, one that requires curiosity, empathy, and structure more than charisma or persuasion.

You’ll learn to ask better questions, listen carefully, and interpret what customers mean—not just what they say. You’ll make mistakes, and that’s fine. Each one will teach you something about your market, your product, or yourself.

What My Article Series Will Help You Do

This guide will walk you through what early-stage selling really looks like—from the first awkward calls to the moment you start to see repeatable patterns. Along the way, we’ll cover:

• How to adopt the right mindset for founder-led sales.
  
  

• How to build your first sales narrative—a story customers actually care about.
  
  

• How to talk less and listen better, turning conversations into insights.
  
  

• How to price your product without losing confidence or giving it away.
  
  

• How to record and systematize what you learn so future hires can build on it.
  
  

• And finally, how to recognize the early signs that it might be time to bring in your first salesperson—when the process starts feeling more repeatable than experimental.
  
  

This isn’t a crash course in sales tactics or negotiation techniques. It’s more of a field guide for navigating uncertainty, based on what founders actually go through in the early go-to-market phase.

If you’re still figuring out who your customers are, how to talk to them, or what value they truly see in your product—this article is for you.

Think of it as a conversation with someone who’s seen this journey already and wants to help you avoid the most painful mistakes.

You don’t need to love selling. You just need to understand it enough to make it work for you.

So, let’s begin—step by step.

Chapter 1 — Reality Check: You Built It, But They Won’t Come

Let’s start with the uncomfortable truth: nobody cares that you built something amazing.

Not yet, at least.

The harsh reality for most first-time founders is that building a great product and getting people to buy it are two entirely different things. The “if you build it, they will come” mindset might work in the movies, it rarely works in business.

Early-stage sales — what I call the evangelical phase — looks nothing like the polished, professionalized version you might see in large companies. It’s messy, personal, and highly experimental. You’ll do things that don’t scale, that can’t be automated, and that often feel inefficient or uncomfortable. But that’s precisely the point.

At this stage, you’re not scaling success; you’re discovering what success looks like.

The Founder-Led Sales Myth

Many founders assume that once their product is ready, the next logical step is to “hire someone for sales.” That assumption can be dangerous — and often fatal for early-stage companies.

Professional salespeople are great at executing a proven process. They need a clear value proposition, a defined customer profile, and a pitch that’s already been tested in the wild. But if you’re still trying to figure out who your customers are, why they need what you’ve built, and what they’re willing to pay for it, there’s nothing to execute yet.

You don’t need a closer — you need a translator between your product and the market.
And right now, you are that translator.

Founder-led selling isn’t about becoming a “salesperson.” It’s about gathering direct, unfiltered information from your potential customers. It’s about learning what works, what doesn’t, and what you still need to build. Every conversation you have now becomes the foundation of your future sales process.

💡 Takeaway: You can’t outsource understanding. Founder-led sales aren’t optional; they’re the foundation of everything that follows.

Why This Phase Feels So Strange

If your background is technical, selling might feel awkward at first — even unnatural. You’re used to logic, clean feedback loops, and measurable results. Sales offers none of that.

You’ll have conversations that seem promising and then die out. Prospects will say “this sounds great” and never reply again. People will ask for more information and then ghost you. It’s easy to take it personally, but this chaos is actually data.

Every “no” tells you something valuable. Every “not now” reveals a hidden constraint. Even silence has meaning — it shows you what doesn’t resonate.

Your goal in these early sales conversations isn’t to convince or close. It’s to discover alignment — to find the people whose world makes more sense once your product exists in it.

💡 Takeaway: Early sales are less about persuasion and more about discovery.

What This Stage Really Looks Like

This first phase of selling is, by nature, unscalable. You’ll do things that would never make sense later on — visiting a potential client just for a short demo, building a one-off prototype for feedback, or manually collecting leads one by one.

And that’s fine. In fact, it’s necessary.

You’re not optimizing for efficiency yet. You’re optimizing for learning — compressing the distance between your assumptions and the market’s reality.

Think of it like field research: you’re in discovery mode, observing how real people react to what you’ve built. Every small conversation, demo, or trial helps you test a hypothesis about your product and your value proposition.

💡 Takeaway: Early sales are product research with invoices attached.

The Danger of Hiring Too Early

It’s tempting to think that a professional salesperson could do this faster or better than you. In reality, hiring too early can set you back months.

Imagine you bring in an experienced seller from a larger company. They’re used to working with clear playbooks, mature products, and defined metrics. When they join your startup, they find a moving target: the product changes weekly, the pitch evolves daily, and nobody really knows who the ideal customer is.

They start reaching out to prospects, but can’t quite explain the problem your product solves. They get feedback you don’t know how to interpret. Deals stall, nobody’s sure why, and frustration builds on both sides. Eventually, they leave — and you’re left thinking, “Maybe the market isn’t ready,” when the real issue was that you weren’t ready to scale.

Until your narrative, audience, and early proof points are clear, no one else can sell effectively for you.

Your Early Sales Job Description

In these first months, your “sales” work isn’t about closing deals. It’s about understanding the landscape.
Think of yourself as part detective, part product manager, part anthropologist.

Here’s what the job really entails:

1. Exploration: Identify who might benefit from what you’ve built, and why.
   
   

2. Conversation: Reach out, ask thoughtful questions, and test different ways of framing the problem.
   
   

3. Observation: Listen for patterns — what resonates, what confuses, what excites people.
   
   

4. Iteration: Adjust your product, your story, or both, based on what you’ve learned.
   
   

That’s it. No scripts, no funnels, no dashboards. Just you, your curiosity, and your willingness to learn.

💡 Takeaway: Founder-led sales are structured curiosity in action.

The Emotional Rollercoaster

Let’s be honest: selling something you’ve built can be emotionally draining. When a prospect says “not interested,” it can feel like they’re rejecting you. They’re not. They’re rejecting the version of your story that didn’t quite click.

The key is to stay analytical, not defensive. Treat rejection as feedback. Just like debugging code, you’re identifying where the error is — in your messaging, your targeting, or your assumptions.

Some of your early conversations will be energizing. Others will be frustrating. A few will leave you wondering if you’re cut out for this. But over time, you’ll develop instincts: which prospects are worth pursuing, which objections actually hide curiosity, and which “no” really means “not yet.”

That intuition is one of the most valuable assets you’ll ever develop as a founder.

What Progress Looks Like

In this stage, success isn’t about revenue targets. It’s about gaining speed and clarity.

Ask yourself:

• Am I starting to recognize which types of customers react positively to my message?
  
  

• Can I explain what I do in a way that makes sense to someone outside my field?
  
  

• Do I understand which objections come up repeatedly, and why?
  
  

If you can answer yes to those, you’re on the right track. The deals you close are nice milestones, but the real win is pattern recognition. Once you start seeing the same signals repeat — similar profiles, similar needs, similar objections — that’s when you know you’re approaching something that can be scaled.

In Summary

You can’t delegate understanding your customers. You can’t automate empathy and relationship-building. And you can’t skip this phase by hiring someone else to do it for you.

In these early months, selling is learning. Every conversation is an experiment, and every outcome — good or bad — brings you closer to clarity.

When prospects start echoing your message back to you, when objections become predictable, when your product finally seems to “click” with a specific type of customer — that’s the moment you’ll know you’re ready to take the next step.

Until then, keep showing up, keep listening, and keep learning.
Because nobody will ever care about your product as much as you do — and that’s exactly why you’re the right person to sell it right now.

💡 Takeaway: Before you scale revenue, scale understanding.

Massimiliano Pani is a Sales and Customer Success expert and Founding Member of Quiet Edge, based in Mallorca, Spain. With nearly a decade of experience spanning the full sales spectrum—from business development to enterprise sales—he now focuses on helping technical founders navigate their first sales motions. Follow him on LinkedIn.

Once your personas are defined, the next GTM unlock is ruthless funnel narrowing: prioritizing the small slice of accounts that are in-market now, reachable through trust-rich paths, and engaged with intent signals you can act on quickly.

Success comes from focusing your outreach where fit × intent × timing × trust are strongest.

1) From personas to ICPs — and why narrowing matters

Personas describe who you speak to inside a company; an Ideal Customer Profile (ICP) describes which companies you should speak to in the first place (industry, size, tech stack, geography, etc.). In B2B, both are complementary: ICPs drive account selection and prioritization; personas drive messaging and conversation design.

Critically, large deals are rarely decided by one person. Gartner finds typical buying groups of 6–10 decision makers, each armed with independent research — which is precisely why funnel narrowing and multi-threading matter more than ever.

But in this context, the key thing to remember is that only a small share of your ICP is “in-market” at any given time. Leading ABM/intent platforms estimate ~5–10% of ICP accounts are actively buying right now, making prioritization essential to GTM efficiency.

2) The four components of effective funnel narrowing

To turn your ICP into revenue quickly, operationalize these four components:

• Speed — connect fast when signals spike. (Modern buyers spend limited time with vendors; delays matter.)

• Fit — pursue accounts that match your ICP and personas tightly.

• Trust — leverage warm paths (referrals, mutual connections) to boost attention and reply rates.

• Timing (Intent) — act when accounts show buying signals (topic research, review site activity, repeated visits).

3) Tactics that actually narrow the funnel (and why they work)

A) Activate your (extended) network to create trust-rich entry points

Warm pathways beat cold outreach on both speed and conversion.

After years in the field, I’m still struck by how much faster deals close when there’s an existing connection or a trusted referral compared to a pure cold approach — inbound or outbound — even when the value proposition is a perfect fit.

Activating your network may only cover the first three components of funnel narrowing, but the speed and ease of those connections make it indispensable.

LinkedIn recommends leading with common connections — which can raise appointment likelihood by ~70% — and turning cold calls into “warm calls” through social insights. Benchmarks on LinkedIn/omnichannel outreach also show higher DM reply rates than cold email when you “warm” prospects first (engage their posts, reference mutual context, etc.).

Vendor studies vary, but multiple analyses report warm outreach yielding 2×–4× reply rates versus cold — a pragmatic reason to mine alumni, ex-clients, partners, and 2nd-degree connections systematically.

How to operationalize : make a habit of the 30-second “elevator pitch” everywhere with your ex-colleagues, friends or relatives — including old contacts you haven’t spoken to in 15 years, map mutuals via TeamLink and ask for intros. One of them might become your next reference customer.

B) Use intent data to find the 5–10% who are in-market now

Modern ABM platforms (Demandbase, 6sense, Bombora) aggregate first-, second- and third-party signals to reveal which accounts are researching your category, comparing vendors, or spiking on relevant keywords. That enables you to prioritize outreach based on timing, not just fit — and to tailor your messaging to the buyer’s journey stage, fully aligning with the fourth component: Timing and Intent.

Published case evidence and platform studies show intent-driven GTM can shorten cycles and improve conversion by engaging accounts already mid-journey (e.g., “Consideration”/“Decision”).

C) Run targeted outbound email — with realistic benchmarks

Cold email still works, but only with tight ICP filters, clean lists, and useful offers. 2025 benchmarks typically show 1–5% reply rates on cold email (top performers hit 8–12% by narrowing lists and personalizing), while multi-channel sequences outperform email alone. Plan volumes accordingly and score responses fast.

Analyses across millions of emails report average replies in the ~5% range, with personalization and careful follow-ups lifting results. Keep expectations grounded; focus on quality, intent and fit.

D) Events with the right audience are still pipeline engines

In-person events/trade shows remain strong lead channels when your audience is specific and your follow-up is disciplined. Industry stats highlight exhibitors’ focus on lead quality and decision-maker engagement, and event ROI practices emphasize tracking pipeline and velocity, not just badge scans.

Plan KPIs around qualified leads, stage movement, and post-show meetings — not just footfall or swag. [nparallel.com]

E) LinkedIn Groups and Sales Navigator — use with care

Groups can be helpful for warm outreach: join relevant groups, engage authentically, and reference the group in your connection request. If you export member data with third-party tools, mind legal/TOS boundaries: scraping publicly available data can be lawful in some jurisdictions, but LinkedIn’s terms restrict automation and you risk account action if you overstep. Proceed responsibly.

Sales Navigator itself offers powerful lists, shared lists, and “buyer intent” style recommendations — but there are limits (e.g., interface constraints, view caps) and no native “competitor followers list.” Build precise ICP searches and use Shared Lists to collaborate, rather than chasing hacks that violate TOS.

4) A practical FIT × INTENT × TRUST × SPEED playbook (you can implement tomorrow)

1. Decide your ICP and buying committee: Define the firmographic filters and 2–3 core personas you’ll engage per account (e.g., CMO + CIO + Procurement) to multi-thread from the start.

2. Stand up a simple lead scoring model: Combine fit (ICP match), behavioral intent (web/review/keyword signals), and engagement (opens, replies, meetings). ML-based scoring can outperform manual rules when data volume grows.

3. Route by trust first: Prioritize outreach paths with mutual connections/referrals; treat “warm” lanes as SLA-driven (same-day outreach).

4. Trigger sequences on intent spikes: When an account hits a threshold (e.g., multiple visits to pricing/integration pages, review site comparisons), launch a tailored cadence referencing the signal.

5. Instrument events for pipeline, not just leads: Track stage-movement, meeting set rates, and post-event conversion — then feed all contacts back into your scoring model.

6. Measure what matters: Focus on cost per qualified lead (CPL), opportunity conversion rate, pipeline velocity, and win rate by source. Use these to re-weight your scoring and channel mix quarterly.

5) What this means for founders and GTM leaders

In your first 12–24 months to a post-PMF business, resist the urge to “spray and pray.”

Direct 60–70% of your selling time to warm paths + intent-qualified accounts; keep cold outbound limited to tightly curated micro-lists. Expect that, at any given time, most of your ICP is not buying — and design your operations to identify and move on the few who are.

As your data grows, consider augmenting manual scoring with predictive models to prioritize leads more accurately and reduce CAC. Pair this with a strict, shared SLA across marketing and sales to touch intent spikes within hours, not days.

Narrowing the funnel is your unfair advantage

Targeting the right persona is table stakes; narrowing the funnel is where efficiency — and early revenue — happens. Build a GTM engine that:

• Finds in-market accounts (intent),

• Filters ruthlessly by ICP fit,

• Flows through trusted pathways first, and

• Fires with speed when signals appear.

Do this consistently and you’ll compress sales cycles, lift conversion rates, and build repeatable pipeline without ballooning spend — because you’re investing where timing and trust converge, not where interest is merely hypothetical.

References (curated)

• Personas vs ICPs — definitions & use cases:
  LakeB2B: ICP vs Buyer Persona · ExpertBeacon: ICPs vs Buyer Personas

• Buying committees & journey:
  Gartner: New B2B Buying Journey (6–10 decision makers; limited vendor time) · Madison Logic: Rise of the Buying Committee

• In-market share & intent data:
  6sense: Only 5–10% of ICP buying now; journey stage insights · Demandbase: What is ABM Intent Data + use cases · Bombora: Harnessing Intent Data for ABM · ZenABM: Intent-based ABM tools & 5% TAM in market · Zavops: ABM tools & cycle reduction

• Warm vs cold outreach benchmarks:
  LinkedIn Sales Solutions: Warm calls & common connections (+70% appointment likelihood) · Expandi: State of LinkedIn Outreach 2025 · LeadCRM: Warm vs Cold Outreach · LinkedFusion: Warm vs Cold reply rates

• Cold email benchmarks:
  Martal Group: 2025 B2B cold email stats (1–5% replies; multi-channel lifts) · Belkins: 16.5M emails analysis (reply ~5.8%) · Aerosend: 2025 reply rates (1–5% healthy) · BuiltForB2B: Top campaigns 8–12% replies

• Events & ROI:
  Cvent: Trade show statistics (lead quality, decision-maker engagement) · Bizzabo: Measuring trade show ROI for pipeline · nParallel: KPIs for trade show effectiveness

• LinkedIn Groups & scraping/legal:
  PhantomBuster: Is LinkedIn scraping legal? (hiQ context & TOS cautions) · Lobstr.io: Legal overview & best practices · PhantomBuster workflow: Group members to outreach

• Sales Navigator features & limits:
  LinkedIn Help: Sales Navigator Lists, Shared Lists, recommendations · Outbound System: Practical SN limits & search hygiene

• Lead scoring models:
  LeadOps: Building fit+intent scoring that works · Frontiers in AI (2025): ML lead scoring outperforms rules-based

3. If we work forward from customer insights to revenue goal, what are we required to do?

Now flip the lens forward.

Once you know the reach, leads and purchases you need to hit your revenue goal, validate your assumptions with real customers.

Not once, not twice, but on an ongoing basis. Weekly, monthly, quarterly? It’s your call based on your resources and the pace of change in your industry.

Framework:

1. Talk → Gather Signals

Conduct interviews, surveys, or in-app prompts.

Goal: Identify what your customers truly think, feel, and do.
Key question: What uncertainties or gaps am I trying to uncover at this stage?

2. Cluster → Make Sense of Patterns

Use AI (or manual analysis) to group responses into themes, personas, or behavior patterns.

Goal: Find meaningful patterns that reveal opportunities or friction points.
Key question: Which insights suggest concrete areas to improve or test next?

3. Test → Validate Hypotheses

Run small experiments on messaging, channels, or product tweaks.

Goal: Learn what actually influences behavior or engagement.
Key question: What improvement am I targeting, and how will I measure success?

4. Refine → Focus and Iterate

Double down on what works, discard what doesn’t, and iterate quickly.

Goal: Convert insights into actionable improvements.
Key question: Does this change move the needle on the gap I identified earlier?

Purpose of the Loop:

• Not every insight needs to be viewed through this lens; this is a troubleshooting and optimization framework.

• Helps fill gaps between customer understanding and actionable improvements that aren’t resolved by talking or clustering alone.

• Encourages testing and refining with a clear signal: “Did this change actually improve the experience or outcome?”

Risks of not doing this:

• Talking to the wrong market on the wrong channel → months wasted.

• Conversion rates stay flat → revenue stalls.

• Generic branding → hard to compete or retain users.

Actionable playbook (do this week)

1. Gather insights to improve your marketing positioning. DM 10–15 users to ask:

   • What problem does this product solve?

   • How would you explain this product to a friend?

   • What would you do if this product disappeared?
     

More guidance on this here.

Paste the anonymised responses into ChatGPT accompanied by the prompt below.

Steal this prompt

I have collected [number] customer interviews/responses from my target audience in [industry/niche]. The transcripts are provided below, with clear start and end markers for each:

###transcript 1 begins### [Insert full transcript of interview/response 1 here] ###transcript 1 ends###

###transcript 2 begins### [Insert full transcript of interview/response 2 here] ###transcript 2 ends###

###transcript 3 begins### [Insert full transcript of interview/response 3 here] ###transcript 3 ends###

Task:

1. Cluster these responses into [number] personas.

2. For each persona, identify:

   • Key pain points

   • Desired outcomes

   • Language/phrases I should use in marketing
     

3. Suggest micro-tests or messaging experiments to validate these insights with minimal spend.
   

4. Present your output in a structured, easy-to-read format.
   

Notes: Ensure that all insights are derived strictly from the transcripts provided, respecting the defined transcript boundaries.

2. Launch $500 micro-tests on top 2–3 messaging hypotheses.

3. Track engagement, click-through, and conversions → refine.

4. Start to build a picture of your early customer or adopter by filling in the data in this infographic:

B2B Tips

• When conducting interviews, ensure your reach out to all members of the “buying committee” (decision-makers, gatekeepers, end users).

• If you cannot get Zoom time with some or any of these folks, search for related topics on forums like Reddit and Quora, look at competitor reviews on Trustpilot and Google, and even ask LLMs to serve up insights.

• Map competitors by feature set, pricing, and service quality.

• Test messaging with account-based campaigns, personalized demos, or pilot programs.

B2C Tips

• Segment users by behavioral data, psychographics, and lifestyle relevance.

• Track social trends, micro-influencers, and community discussions.

• Test messaging with small paid campaigns, landing pages, or app notifications.

More from “Rules of Growth”

Read it now:

1. Where are we in the growth journey today?

2. If we reverse-engineer from (i) revenue goal to (ii) reach required, what would the funnel be?

Coming soon:

4. How can we make our $1 budget work like $10?
5. What scrappy growth moves feel authentic to our company?
6. Let’s zoom in and execute: who is our beachhead persona and our wedge?

Kate Busby is CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Instagram. The images are extracted from X and created by MidJourney. No names and identifying details have been changed. Subscribe to Substack to receive all articles in the “Rules of Growth” series straight to your inbox.

🤝 Want to work together? ⏩ Check out the options and let me know how we can join forces.

2. If we reverse-engineer from (i) revenue goal to (ii) reach required, what would the funnel be?

Growing an audience of customers isn’t vibes, it’s math.

Too many founders set “grow fast” as their goal, without any knowledge of the obstacles they might face and the time required to overcome them.

We are not going to aim for the moon without building a rocket.

Let’s work backward from your revenue goal to understand the inputs required. This is the only equation you need:

The Reverse Growth Equation (RGE)

Let’s break this down:

Lots of theory here, so let’s apply it to your business.

Actionable Playbook (Do This Week)

1. Set your survival goal
   Example: $10k new MRR per month in 6 months. (Focus on growth per month, not total revenue.)
   

2. Translate goal into leads (simplified)

Using RGE:

Leads needed per month = New MRR target / (Avg revenue per customer × Conversion rate)

Example: $10k ÷ $50 ÷ 0.05 = 4,000 leads/month.

⚠️ Note: This is a simplification. Realistically, your MRR compounds over time as cohorts retain revenue. For precise total MRR projections, a spreadsheet model can help account for retention and cohort growth.

3. Audit your current reach
   Check signups, demos, calls—where are you now versus your target?
   

4. Identify the gap
   How many additional leads or conversions do you need to hit your growth goal?
   

5. Run 3 quick experiments
   Focus on the biggest levers that can close the gap. Track results and iterate quickly

Pro Tip: Get ideas for experiments using the prompt below.

Steal this prompt (and get a prompting masterclass here)

Act as a senior growth and funnel strategist for early-stage startups.

My goal is to reach [revenue target, e.g., $10,000 MRR] in [time frame, e.g., 6 months].

My product/service is priced at [price per unit or subscription], and our current conversion rate is [current conversion %].

Please provide:

Lead/Signup Requirements: calculate the number of leads or signups needed per month to reach the revenue goal.

Estimated Marketing Budget: approximate spend needed for an unknown brand to achieve sufficient category reach.

Funnel Bottlenecks: identify the most critical points in our current funnel limiting growth.

Scrappy Experiments: suggest 3 low-cost, high-impact experiments to improve performance.

For each recommendation, include:

- Key assumptions 
- Expected effort, cost, potential impact
- Any creative or unconventional tactics that could stretch budget efficiency. 

Also, suggest any overlooked opportunities or alternative approaches to accelerate revenue growth.

These companies already figured it out:

B2B case study

When Jasper launched its AI copywriting platform, the founders didn’t just chase hype: they worked backward from their first-year revenue target. Their math: $1M ARR in year one. At $99/mo pricing, they needed ~850 paying users. With an average free-to-paid conversion rate of ~5%, they reverse-engineered a requirement of ~17,000 trial signups. Instead of blowing money on ads, they focused on:

• Partnering with influencers and affiliate marketers in copywriting and marketing circles

• Building a free Facebook community that funneled warm leads

• Optimizing onboarding flows so new users generated first outputs in minutes

By tracking signups vs. required volume weekly, they spotted gaps early. The discipline worked, Jasper hit $40M ARR within two years. Their RGE discipline helped them scale responsibly, ensuring every channel was tied back to funnel math.

Lesson: B2B founders can’t rely on vibes, they need growth rooted in unit economics and funnel math. “Spend and see” isn’t a strategy; it’s a gamble that ends in luck or a crash. Jasper’s discipline in tracking conversion rates and lead requirements gave them a repeatable, defensible path to scale, and a blueprint worth emulating.


B2C case study

Stardust Analytics (2025) is a small Shopify-focused analytics tool that was vibe coded on Lovable. The startup recently raised about €1.7M (pre-seed) after winning a Lovable contest and demonstrating early product interest. Investors were attracted by fast build cycles, clear ROI for Shopify merchants, early traction/pilots and strong maker/community visibility.

So how’d they get their initial traction?

Stardust reverse-engineered their targets by treating a narrow set of Shopify merchants as the product, mapping each store’s purchase funnel, isolating the single KPI that most constrained growth (traffic→conversion, checkout dropoff, average order value, etc.), and instrumenting quick experiments and diagnostics to prove lift; built in seven months on Lovable, they launched fast into the Lovable maker community and a Lovable contest to get beta testers, ran founder-led paid pilots with 10–50 stores to collect ROI case studies, optimized onboarding via a Shopify app listing and step-by-step diagnostic flows, and grew by publishing concrete case studies, forging small agency/integration partnerships, and using referral and maker-channel virality to keep CAC low, iterating off pilot feedback until conversion economics looked repeatable, which then convinced early investors to write the pre-seed check.

Lesson: Beginning with the revenue goal allowed Stardust to design messaging experiments, persona targeting, and product nudges that directly drove conversions.

B2B Metrics & Growth Tips

1. Factor in longer sales cycles and multiple touchpoints
   

   • B2B deals often take months or even years to close, with multiple decision-makers involved.

   • Early-stage founders or new product teams should map the buyer journey to understand where touchpoints occur (emails, demos, calls, content) and plan for incremental engagement at each stage.
     

2. Consider LTV/CAC per account and pipeline velocity
   

   • LTV (Lifetime Value) estimates the total revenue you can expect from a customer over the life of their relationship with your product. For new products, LTV may be uncertain because churn rates aren’t established yet—start with assumptions and refine over time.

   • CAC (Customer Acquisition Cost) includes sales and marketing expenses directly tied to acquiring a customer, but be mindful: not all expenses count (exclude unrelated overhead, but include outbound campaigns, sales salaries, tools, and content creation).

   • Pipeline velocity measures how quickly opportunities move from lead to closed-won. Track it to forecast revenue and identify bottlenecks.
     
     

3. Model pricing scenarios for enterprise contracts, tiers, and discounts
   

   • Enterprise deals often include negotiations, volume discounts, and custom contracts.

   • Simulate different pricing models to understand revenue impact, margin sensitivity, and potential churn risk.
     

Caveat: For brand-new products, treat all metrics as provisional. The goal is to build a repeatable framework, not perfectly predict outcomes from day one.

B2C Metrics & Growth Tips

1. Think high-volume, low-ticket economics
   

   • B2C growth often depends on reaching many users with low-cost offerings (subscriptions, in-app purchases, small physical products).

   • Focus on unit economics: what margin per user is sustainable given acquisition costs?
     

2. Map conversion rates across funnels
   

   • Track every step of the user journey, from signup to onboarding to free-to-paid upgrades.

   • Even small percentage improvements at each stage can compound significantly across thousands of users.
     

3. Incorporate viral loops and referral multipliers
   

   • Many B2C products grow faster when users invite others or trigger network effects. Example: Keila Shaheen’s story of how a TikTok influencer review sparked 1 million sales of her “The Shadow Work Journal” in under a year.

   • Factor the potential impact of referrals into acquisition forecasts—e.g., each new user might bring in 0.2–0.5 additional users on average.
     

Caveat: For new products, historical churn and engagement rates won’t exist. Start with educated assumptions, track data closely, and iterate quickly.

Word to the wise: the answers to question 2 and question 3 go hand in hand.

Don’t bring your reverse-engineered revenue plan to the table until you’ve completed question 3, which covers product-market fit.

And without product–market fit, even the best revenue plan won’t save you.

More from “Rules of Growth”

Read it now:

1. Where are we in the growth journey today?

3. If we work forward from (i) customer insights to (ii) revenue goal, what are we required to do?

Coming soon:

4. How can we make our $1 budget work like $10?
5. What scrappy growth moves feel authentic to our company?
6. Let’s zoom in and execute: who is our beachhead persona and our wedge?

Kate Busby is CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Instagram. The images are extracted from X and created by MidJourney. No names and identifying details have been changed. Subscribe to Substack to receive all articles in the “Rules of Growth” series straight to your inbox.

🤝 Want to work together? ⏩ Check out the options and let me know how we can join forces.

Design Founders, you have dreamt up a product idea, whispered it into an LLM, and just like that, it’s live. You’re officially a vibe coder. Now it’s time to get paid.

“Rules of Growth” ask the six most important questions to land your first customers on a lean budget without burning yourself (or your future team) out.

As you test, what are you looking for? This: one repeatable, scalable go-to-market motion that will drive your growth for the next 3-6 months.

Pause: don’t fall into the trap of vibing your way to an expensive marketing fuck up i.e. a product that does not sell. I do not want this for you.

Be warned: competition is intensifying. You will always discover new competitors as time passes. Vibe coding and AI in general are flooding the market with new products.

And when building is this cheap and easy, only founders who master the rules of growth will quickly reach their first revenue milestone.

I’m Kate, Fractional CMO for edtech startups, and whenever I begin a role, I use these six questions to challenge myself and the teams I’m supporting. They are a compilation of the best lessons I’ve learned from my mentors and hands-on experience.

Time for six big reveals. Vamos →

The Six Questions:

1. Where are we in the growth journey today?

2. If we reverse-engineer from (i) revenue goal to (ii) reach required, what would the funnel be?

3. If we work forward from (i) customer insights to (ii) revenue goal, what are we required to do?

4. How can we make our $1 budget work like $10?

5. What scrappy growth moves feel authentic to our company?

6. Let’s zoom in and execute: who is our beachhead persona and our wedge?

Big reveal Number #1:

1. Where are we in the growth journey today?

Too many companies mistake a handful of paying users for proof of demand. They pour money into ads only to slam into a wall when growth stalls.

Before chasing scale, get honest about where your product really is. Early users aren’t validation. True validation comes from repeatable revenue and clear product–market fit.

Let’s figure out where your vibe-coded startup is right now.

Four main growth stages

1. Idea → You / your tiny team is hustling to see if anyone cares.

2. Validation → Hustle ends. There is a steady stream of interest beyond “friends, family, fools.”

3. Traction → Some users are paying once. Others are paying again and again. This latter group should be growing month by month, not dying off.

4. Scaling → Marketing and Sales channels are now working to reach a key milestone without inflating costs, which could be:
   

   1. the thing we built is now self-sustainable (Break Even)

   2. the thing we built is making money (Profitability)

   3. the thing we built is really taking off (Scaling)

Let’s go deeper:

Use this table as a reference.

Now you’ve got the theory, let’s move to action.

Actionable playbook (do this week)

1. Open a doc → create 4 columns: Idea, Validation, Traction, Scaling.

2. Using the diagnostic tips in the table above, write down where you feel you sit today. It’s completely normal if you find yourself spanning two stages.

Now, feed the list into ChatGPT with this prompt:“Based only on the signals in this list (and not on any assumptions beyond it), what’s the single most important growth priority I should focus on?”

Tip 👉 Adding ‘based only on the signals in this list’ helps the model stick to the provided inputs instead of pulling in outside guesses.

These companies already figured it out:

B2B case study

Butter started as a tiny remote startup focused on one specific thing: a specialized virtual workshop platform for facilitators of interactive trainings and live collaborative sessions who were deeply frustrated with Zoom.

Although the company had raised about $440,000 through grants, venture debt and equity from Morph Capital, they did not rush into broad promotion. Instead, Butter’s founders spent their early months speaking 1:1 with meeting facilitators to understand whether problems like “Zoom fatigue” were big enough to represent a real opportunity. They consistently heard that facilitators needed more cohesive and human experiences than Zoom could offer. This feedback shaped Butter’s positioning as “laser focused on workshops” with “delightful design” that “supports facilitators in delivering a more human experience.” (Source: TechCrunch.)

Early adopters led to growing traction (both organic and paid) because the problem was widespread, underserved by competitors and the numbers of facilitators was large enough to get scale.

By April 2021, the company raised a $2.75 million seed round (later extended to $3.2M) led by Project A and several angel investors. And in 2024, Butter announced that it was joining powerhouse Miro, bringing its facilitation expertise and workflows into Miro’s broader visual collaboration ecosystem, sealing their growth. (Source: Butter blog.)

B2C case study

Gamma secured seed funding in 2021 and launched its public beta in 2022, but its real breakthrough came not from new investor money, but from zeroing in on an unsolved problem for a specific, high-potential audience. While tools like PowerPoint and Notion were built for people who already knew what they wanted to say, Gamma noticed a growing wave of professionals struggling with the blank page problem: the paralysis of starting a presentation from scratch. This segment, knowledge workers who needed to communicate ideas quickly but lacked time, design skills, or structure was huge, underserved, and hungry for help.

By embedding AI capabilities in early 2023, Gamma became the first presentation platform to generate a ready-to-edit draft from a single prompt, a never-seen before approach, turning “blank page” friction into an instant starting point. (Source: JPMorgan Chase) The result was a user-activation breakthrough: within nine months, Gamma grew to around 10 million users. Retention rose sharply as those same users kept returning to refine and share AI-generated decks, and monetization followed organically.

By 2025, Gamma had scaled to 50 million users and $50 million in ARR with a team of just 30 people, remaining profitable from early 2024 onward. Its growth was powered almost entirely by product-led adoption, word-of-mouth, and a crystal-clear focus on a single, underserved audience rather than broad marketing spend.

When Gamma raised its $12 million Series A in May 2024 (led by Accel), it wasn’t to chase growth — it was to sustain momentum already proven by a wedge audience whose unmet need had turned into a mainstream movement. (Source: FinSMEs)

How to Think About Growth Stages

Different types of AI-first startups grow at different speeds.

For example, an AI recruiter (B2B, long sales cycle) will grow very differently than an AI design tool (B2C, instant value).

That’s why it helps to map growth by vertical (industry), by who the buyer is, and by how mature your idea is.

B2B Growth Stages (selling to businesses)

When you know you’ve hit traction

You’ve reached Traction when you can track the full sales cycle (lead → conversation → closed deal) with enough consistency to forecast growth.

Key metrics to watch

• MRR (Monthly Recurring Revenue):
  The total predictable subscription revenue you generate each month.
  How to calculate: Add up all active paying subscriptions for a given month.

• Churn:
  The % of customers (or revenue) you lose each month.
  How to calculate customer churn: (Customers lost ÷ Customers at start of month) × 100.
  How to calculate revenue churn: (MRR lost ÷ MRR at start of month) × 100.

• Qualified Leads:
  Leads that actually match your buyer profile and show intent (not just a random signup).
  

⚠️ Warning: If new accounts are coming in but many are canceling quickly, you’re not really in traction yet — you’re still between the Idea and Validation stages.

B2C Growth Stages (selling to consumers)

Shorter cycles, different signals

For consumer products, raw revenue can spike early but that doesn’t mean you’ve found product-market fit. What matters is whether people keep using you and invite others in.

The “User-First” approach

Instead of fixating on DAUs (Daily Active Users) alone, focus on whether users can do the task they came for. Depending on your product, the right metric might be:

• DAU / WAU / MAU → Daily, Weekly, or Monthly Active Users

• Signup conversions → % of new users who actually start using the product

• Task completions → e.g., number of documents created, rides booked, files shared
  

The idea: your early build cycles should obsess over helping users succeed at their core task, whatever that looks like.

Key metrics to watch

• Retention: Do users come back after day 1, week 1, or month 1?

• Referral loops: Do users invite others to join?

• Virality signals: Social shares, reshares, content engagement.
  

Community adoption

Momentum often starts in small groups. If one cohort of users adopts you and spreads the word to another, you’re moving from Validation into Traction.

Five more big reveals in “Rules of Growth” series:

2. If we reverse-engineer from (i) revenue goal to (ii) reach required, what would the funnel be?

3. If we work forward from (i) customer insights to (ii) revenue goal, what are we required to do?

4. How can we make our $1 budget work like $10?

5. What scrappy growth moves feel authentic to our company?

6. Let’s zoom in and execute: who is our beachhead persona and our wedge?

Kate Busby is CoFounder of Quiet Edge and a Fractional CMO based in Barcelona, Spain, catch her on X and Instagram. The images are extracted from X and created by MidJourney. No names and identifying details have been changed. Subscribe to Substack to receive all articles in the “Rules of Growth” series straight to your inbox.