That sounds like an advantage until you realise it also makes it easier to waste time and money on the wrong idea.

, partner at MGV Capital and founder of Alpha Bytes, where he writes about startups, investing, technology, and building companies, has seen that from both the operator and the investor side.

In this guest piece, he writes about why founders need better filters now that building is cheap and exploration matters more than ever. 👇🏻

The real skill is choosing what to build

We’re idea machines by nature. That’s never really been an issue.

The problem is that most ideas, even the good ones, aren’t always worth building.

They could be worth exploring. That distinction matters more now than it used to.

The filter is gone

In the old world, scarcity did the filtering for you.

If an idea needed six months and serious capital to prototype, you stress-tested it before writing the first line of code.

You asked hard questions early because the cost of being wrong was enormous. Time, capital, and effort were brutal filters, but honest ones.

That world is disappearing quickly. AI has collapsed the cost of execution in ways that would’ve sounded absurd even a few years ago.

You can spin up an MVP in a weekend and get something usable in front of people almost immediately. The friction that used to kill bad ideas early has gone.

That sounds like progress, and in many ways it is. But it also makes it easier to waste time building the wrong thing.

The bottleneck has changed. It’s no longer “can we build this?” It’s “should we build this, and should we build it now?”

Exploring is not building

After being on both sides of the fence as an entrepreneur and an investor, I’ve noticed there’s a stage between having an idea and shipping it.

That stage is exploration. It’s where you test an idea before putting real resources behind it. No code. No hires. No capital. Just the cheapest due diligence you can do.

The problem is that exploration is messy by nature. Ideas sit in your head, in random notes, in voice memos that make no sense the next morning.

That’s where a system helps. Instead of relying on gut instinct, it gives you a repeatable way to capture, evaluate, and either park or promote ideas.

The goal is to sequence ideas and finding the ones that are actually right for you.

Some ideas are good on paper and still wrong for the person trying to build them because they don’t match their experience, skills, or ambition.

A simple way to do it

I’ve been running a version of this for a while, and it’s changed how I think about new projects. Here’s the framework stripped back to the essentials:

1️⃣ Capture everything. Write every idea down. No filtering. A note, a voice memo, whatever works. The point is to get it out of your head. Unsorted ideas create cognitive load. A log helps with that.

2️⃣ Let it sit. I usually do 72 hours. Some people do 48 hours, some a week. What matters is that you don’t act on it within 24 hours. Excitement is a bad filter. The ideas that still feel interesting after the dopamine fades are the ones worth exploring.

3️⃣ Score, but do not judge. For the ideas that survive, run them through four questions. Does this solve a real problem I can explain in one sentence? Do I have a unique angle or unfair advantage? Is there any sign of demand, even anecdotal? Could I explain this to a stranger in 60 seconds? Anything below your threshold gets parked.

4️⃣ Explore on paper. For ideas that pass the filter, do a focused two- to four-hour research sprint before you build anything. Map the competitive landscape, look at existing solutions, and find communities already talking about the problem. AI can help you synthesise information, but it shouldn’t make the decision for you.

5️⃣ Define the kill criteria. Before you go any further, write down the specific conditions under which you’d stop pursuing the idea. If you can’t articulate what would make you walk away, you’re probably not being honest about the opportunity.

6️⃣ Keep a live repository. The ideas that survive aren’t a to-do list. Revisit them monthly. Look for recurring themes, overlapping audiences, and complementary concepts. Sometimes the best product isn’t a single idea in the log, but the overlap between several of them.

7️⃣ Promote one. Park the rest. When you’re ready to commit real resources, pick one idea and move it into formal validation. Build a landing page, set up interviews, create a waitlist, or talk about it publicly. The rest stay parked.

The trap you need to see coming

This system has a failure mode, and it’s a seductive one. Too much exploration without commitment is just procrastination.

The system is there to help you decide. If you’ve been exploring the same idea for six months without moving it into validation, that’s probably your answer.

There’s also the temptation to get attached to having a rich idea log without ever acting on it.

The log is there to help you move. To stop it turning into a trophy case, set a cadence, quarterly at minimum, where you force a promote-or-park decision on your top ideas.

AI can make this trap worse. Because it can generate research, competitive analysis, and prototype mockups on demand, it’s easy to confuse activity with progress. A lot of output can still mean very little progress.

The real advantage now

Humans will keep generating ideas. That part isn’t changing.

What’s changed is the cost of acting on them, and with it, the cost of acting on the wrong ones.

In the AI economy, speed alone won’t be enough. The difference is knowing what deserves real commitment and what should stay in exploration.

👤 Barry Winata is a partner at MGV Capital and writes Alpha Bytes. Before moving into investing, he spent nearly a decade as an operator across engineering, growth, recruiting, product, operations, and sales, helping startups grow into successful companies, including businesses acquired by Verizon and others backed by investors such as SoftBank, Intel, and Samsung. Connect with Barry on LinkedIn.

Alpha Bytes

The pragmatist's anti-hype guide on AI and its impact on you, your career, business, culture & society.

By Barry Winata

He works closely with companies going through the process, and the pattern is consistent. Founders focus on the pitch, the deck, the story they want to tell. Investors are reading something else entirely.

The decision starts forming long before the meeting. Your traction, your positioning, how clearly you explain the problem, how you show up in the market. Those signals carry more weight than any polished slide.

That’s where a lot of founders get caught out. They treat fundraising like a moment instead of a process, and by the time they’re pitching, most of the work that actually matters has already happened or hasn’t.

In this episode, we get into how investors really make decisions, why fundraising is closer to sales than storytelling, when not to raise, and how to build the kind of trust that makes people want to back you before you even ask.

🔗 Find James on LinkedIn

📙 James is offering Millennial Masters readers his best selling book, The Investable Entrepreneur, free of charge via his website.

Key takeaways

1️⃣ Fundraising starts before you ask for money

By the time you’re in the room, most of the decision is already forming. Investors are looking at how you show up, what you’ve built, and whether the story holds together outside the pitch. If your positioning is unclear or the signals are weak, no deck fixes that. The real work happens earlier, in how the business presents itself over time.

2️⃣ A pitch doesn’t carry as much weight as you think

Founders spend weeks polishing slides and rehearsing answers. It helps, but it’s not what tips the decision. Investors are checking whether the business makes sense on its own terms. If the numbers, traction, and narrative don’t line up, a clean pitch just makes the gap easier to spot.

3️⃣ Fundraising is closer to sales than storytelling

You’re not just explaining an idea, you’re helping someone get comfortable making a decision. That means understanding what they care about, what risk looks like from their side, and how your business fits into that. Founders who treat fundraising like a performance often miss the commercial side of what’s actually happening.

4️⃣ Trust builds long before the deal

People back founders they believe can figure things out. That comes from how you think, how you communicate, and how consistently you show up over time. It’s built in conversations, updates, and the way you handle pressure, not just in one meeting. When that trust is there, the process moves differently.

5️⃣ Not every business should raise

James is clear that funding only makes sense if you’re building for a much bigger outcome. If the business is really a lifestyle business, or you only need money because cashflow is tight, investment can be the wrong answer. A smaller, profitable company may give you more control and a better life than forcing yourself into a venture-scale path.

In this episode

00:00 Introduction to James Church

02:32 From graphic design to investment consulting

05:25 Understanding the high-performance founder

12:41 The art of investor engagement

17:12 The journey of fundraising

23:38 Timing your fundraising efforts

35:51 Overcoming shyness and building confidence

44:06 Networking and using existing connections

49:33 Understanding angel investors and their expectations

52:49 Navigating dilution and equity distribution

01:02:41 When not to raise funds

⚡️ More startups & fundraising:

I’ve seen it and I’ve done it, usually when you’re stretched and trying to keep too many things moving at once.

Marketing feels vague and product feels too technical, so you bring in outside help to “handle it”.

That can seem sensible, like you’re finally out of the weeds. Sometimes it is.

A lot of the time, though, you’re using outside help to avoid learning a function you still need to understand.

That’s where the trouble starts. You hand away part of the business before you understand it well enough to judge it or spot when it’s going wrong. 👇🏻

You skipped the hard bit

Melissa Kwan ran into this twice. She kept hiring agencies to do the hard work she didn’t want to do, then got poor results because she didn’t even know the basics of marketing.

She never really took that on because she told herself it wasn’t for her. In the end, she put “the most important revenue role” in someone else’s hands.

If the function is still a black box to you, you don’t really know what you’re buying.

You don’t know how to write the brief, how to interview for the role, or whether the person in front of you is excellent, average, or just saying the right words.

Melissa realised that “you cannot hire someone to do a good job if you don’t even know how to interview for them… It’s not that they’re not good. It’s that I don’t know how to direct them.”

You think you’re fixing a capability gap. What you often create is a visibility gap.

A product doesn’t stay finished

Melissa ran into the same problem again when it came to product. The issue was never just agencies. It was handing away a core function.

She hired a dev shop that was meant to cover everything: PM, developers, technical lead, the lot. The deal was milestone-based. It sounded sensible, but the product didn’t really work, the shop kept burning time, and the moment real users arrived the gaps started opening everywhere.

Once a product is live, it keeps breaking, changing, and needs fast decisions. A dev shop isn’t built for that kind of urgency. “A dev shop will never be able to fix that. They’ll be like, yeah, maybe next week.”

A project can be outsourced. A live product usually cannot be treated like one.

If what you’re handing away needs constant judgement, fast iteration, and real ownership, you cannot afford to have all of that understanding sitting outside the company.

Agencies optimise for the incentive

Gary Das found a similar issue in his marketing spend. He was paying marketing companies to get leads for his mortgage business, and all they cared about was getting leads because that was the metric they were paid on.

They weren’t bothered if anyone answered the phone, if those leads became appointments, or if they ever turned into clients.

That isn’t a moral failure. It’s an incentive structure. Outside help usually optimises for the metric it gets paid on, and that metric can sit one step away from what actually matters.

If you don’t understand the function well enough to see that gap, you can burn a lot of time and money while everyone involved still claims the work is performing.

You can outsource execution, but you still have to own the result.

You still need a clear view

Damon Flowers gets to the practical fix. If you’re hiring for something technical and you don’t have the background to judge it, bring in someone independent who does.

Tap your network and get somebody to shadow the work, review it, or tell you whether what’s being built is what should be built.

You don’t need to become the world expert in every function. You just need enough understanding to know what good looks like. If you don’t have that yet, you need someone close enough to the business who does.

The damage starts when you lose visibility. When something gets blindly handed off, you start losing sight of the pipeline, the cost, and the key metrics that tell you whether the engine is healthy or leaking.

The problem is outside help plus founder blindness. Melissa found the fix almost by accident. The outsourced dev team kept burning through time and money without getting the product working, so David, who had been her boyfriend for seven years, stepped in pro bono to help her get unstuck.

Once she saw what he could do, it made no sense to keep paying an external agency for poor results. She brought him in as CTO and co-founder, sorted the equity, and now he runs the remote engineering team in Vietnam.

That also gave Melissa room to focus on what she needed to own herself. She could bring marketing in-house, rework the messaging and positioning, and stop outsourcing a critical part of the business she had already spent years avoiding.

Some knowledge needs to stay inside

“Do you want to have your own army, or do you want to pay mercenaries?”

Yannik Schrade’s point is that you need to think hard about what your moat actually is. If the team’s skill set and knowledge of how to solve the problem are part of that moat, building that expertise internally matters.

That’s why he’s in favour of having your own team, where the capability compounds inside the business instead of leaking out through outsourced relationships.

A lot of founders miss this because they treat everything as a resourcing problem. Some tasks are just execution. Others are where your edge starts to form.

If the function shapes revenue, product quality, or how the business learns, handing it away too early can do real damage. It can stop the company from building its own judgement.

Where outsourcing actually works

Liam White is a good example of where outsourcing does make sense. He realised that if his sauces business wanted to stay lean, it made more sense to find a manufacturer and keep the internal focus on sales, marketing, and product. The manufacturer had expertise it would’ve taken years to build in house, and outsourcing let them scale faster.

Harvey Armstrong and Sam Holmes are beer lovers, not beer makers. They work with professionals on producing Prime Time, keep control of the brand, and use outside expertise to scale without pretending they need to own every technical detail from day one.

Joe Averill makes the same point with fractional talent. A startup may not have the money for a full-time CFO. Fractional support gave him access to higher-level capability without the full-time cost.

So this is not an anti-outsourcing argument. It works when you are buying specialist help or capacity you do not need to keep inside the business. It breaks down when you use it to avoid understanding a core function.

The rule that matters

If the work is core to revenue, product quality, customer understanding, or your future moat, you need enough understanding to judge it.

That doesn’t mean doing everything yourself forever. It means not handing away the part of the business you still don’t know how to see clearly.

The expensive mistake isn’t paying too much. It’s handing away a function before you know how to see it clearly.

That’s why AI feels so powerful to solo founders, consultants, and service businesses right now.

The catch is that when everyone has access to it, the advantage shrinks fast.

of Unpromptable is back with a guest piece on what actually keeps a business distinctive once the tools are no longer the story. 👇🏻

The new AI moat is harder to fake

A year ago, saying “we use AI in our workflow” turned heads. Today, it feels like every service business is running some flavour of ChatGPT, Claude, or a no-code workflow bolted together over a weekend.

The differentiator disappeared. “We use AI” now carries the same weight as “we use email.” It’s the baseline. And if your competitive advantage was speed or cost, AI just handed that same advantage to everyone else in your market.

The uncomfortable truth for most digital business owners is that the only durable advantage left is becoming the kind of business that AI can’t replicate.

I call this unpromptability. It’s the part most people miss when they talk about AI advantage.

Blending in gets expensive

Most businesses haven’t felt the full weight of this shift yet. They’re still riding the early efficiency gains, with faster turnarounds and lower overhead.

The gains are real, but they’re also temporary, because every competitor has access to the same tools. Speed used to matter when it was rare. Once it becomes baseline, it stops carrying much pricing power.

You can’t differentiate. When everyone’s output starts looking and sounding alike, your prospects can’t tell you apart from the next option in their inbox. You become interchangeable. And interchangeable businesses don’t command attention, loyalty, or premium pricing.

You race to the bottom. Without meaningful business differentiation, the only lever left is price. You start undercutting. Your competitors undercut back. Margins thin. The work gets commoditised even if the service behind it is good. AI didn’t cause this dynamic, but it accelerated it by a decade.

Your clients hold all the leverage. When everything looks the same, buyers default to convenience. They shop around faster, switch providers more easily, and negotiate harder. The relationship you thought was solid becomes transactional overnight. They’re loyal to the outcome, and if someone else can deliver it cheaper or faster, they will.

This is the AI commodification trap. The way out is becoming harder to replace.

That usually starts with diagnosing the real bottleneck properly. A lot of businesses think the problem is speed, so they use AI to push out more work. Then they end up with faster average output and the same strategic weakness underneath it.

The advantage now is knowing where the tools actually help, and where they just make the sameness worse.

What competitors can’t copy

What makes a business harder to replace is not the tool stack. It’s the part competitors can’t easily copy: a clear point of view, real relationships, useful assets, and proof that the work delivers.

Marketing matters differently once everyone has access to the same tools. It stops being about promotion and starts becoming proof. The businesses that hold up are the ones whose work carries enough specificity that it cannot be mistaken for the next polished option in the market.

The clearer your thinking and the more visible your body of work, the harder it is to become interchangeable on price alone.

Relationships matter because AI can imitate your tone, but it can’t build rapport, trust, or the kind of connection that turns one client into a long-term buyer or referrer.

Proof matters more too. In a market full of polished claims, case studies, repeat clients, and visible outcomes do more to separate a business than another clever line about AI ever will.

That is the real skill here. AI made building easy. Building something people trust, remember, and come back to is still the harder part.

👤 James Presbitero Jr. is the founder of Unpromptable, where he helps founders and service businesses build AI systems that make them impossible to replace. If you want to know where your business stands on the irreplaceability spectrum, take the free AI Readiness Diagnostic. It takes 3 minutes and gives you a clear picture of where to start.

Unpromptable.

Helping founders, creatives, and professionals become irreplaceable in the Age of AI || Subscribe: forever free 2x deep dives, community events, and free Active Prompt Vault (+ more AI & marketing tools).

By James Presbitero

He’s the founder of Arcium, building privacy infrastructure at a time when AI is making software easier to build, easier to copy, and more exposed than most people realise.

Yannik said that if your edge lives in the product, the knowledge, and the way the team works together, you can’t keep giving that away and expect to build a real moat.

In this episode, we get into in-house teams versus outsourced work, privacy as a competitive advantage, how AI is changing software, and why founder taste matters more than technical skill on its own.

🔗 Find Yannik on LinkedIn

Key takeaways

1️⃣ What you need to own should stay close

If the thing that makes your company good lives in the product, the systems, and the way your team works, you don’t want too much of that sitting outside the business. Yannik made a strong case for building a small in-house team that understands the mission and gets better over time, because that knowledge compounds. Renting help can solve a short-term problem, but it doesn’t build much that stays with you.

2️⃣ Privacy can become part of the moat

Instead of treating privacy like a legal box to tick, make it part of the offer. If your product helps people do something useful without giving away more data than they need to, that becomes a real advantage. More people are starting to care where their information goes and what other systems it touches. That creates room for companies that take it seriously.

3️⃣ AI has made software easier to copy

The tools are getting cheaper, faster, and easier to use. That sounds good until you realise it also means more rushed products, cloned features, and weak points under the surface. Yannik’s wider point is that AI lowers the barrier to building, and it gives more people the chance to build badly. Founders need to think harder about what they rely on and where new risks are creeping in.

4️⃣ Taste matters more than technical skill

The founder doesn’t need to be the best engineer. They need to know what should exist, what’s worth building, what feels right for the product, and what will make sense to the customer. That’s where taste starts to matter more. It’s what holds the whole thing together once the business gets more complex.

5️⃣ Put yourself where luck can find you

You need to spend more time in high-entropy situations, the kind where something useful can happen that you couldn’t have mapped out in advance. That might be a conference, a meeting, or something you nearly skipped. Plenty of good things in business come from putting yourself in enough real situations for chance to do its part.

In this episode

00:00 Meet Yannik Schrade

02:04 From apps to privacy infrastructure

09:26 Why the old model stopped working

18:14 Building Arcium around privacy

25:44 Where financial systems go next

27:01 What healthcare gets wrong about data

27:46 The basics behind computational primitives

28:42 AI, ethics, and privacy pressure

29:39 Whether privacy can support a business model

30:39 Funding privacy technology with VC money

31:48 Fixing data silos in healthcare

33:39 Why everyday apps should worry you

36:05 Messaging apps and what secure really means

39:38 Convenience versus privacy in AI tools

41:38 Building a team that keeps the edge

43:37 Putting yourself where luck can happen

There’s a point where underpaying yourself stops being discipline and starts affecting the person making the company’s most important decisions. That’s when the founder becomes the weakest part of the business.

I heard it put in different ways by Millennial Masters guests, and most of them treated it as part of the deal. I did that for too many years, until I realised what it was costing.

Melissa Kwan also used to think founders should get paid last and least. After years of doing exactly that, she changed her mind. “The biggest variable to success is the founder,” she told me, and “if you are constantly in survival mode… you cannot make good decisions for your company.” The real issue is what that does to the founder.

Before eWebinar, she described almost ten years of “pure suffering”, paying herself barely enough to get by well into her 30s, living with multiple roommates, picking the cheapest thing on the menu, or meeting friends after they’d already eaten because she couldn’t afford dinner with them. That’s what bootstrapping often looks like in real life.

It’s easy to package that kind of sacrifice as part of the job. It sounds different when you look at what people are actually giving up.

James Fleming went from a highly paid executive job to selling his watches while his wife sold off her gold just to keep the marketing going. He had days when he didn’t know how he was going to put fuel in the car to get to meetings. Emma Mills ended up remortgaging her house to sort out cash flow after getting too optimistic about what the business could support.

Tyler Dunagin pulled money out of his savings and retirement account and paid himself a pittance for the year. Andrew Steele pointed to another version of the same problem: founder pay that’s too low or too erratic can leave you unable to get a mortgage at all.

People blur the line between lean and self-destructive when they talk about “lean”. The word sounds smart and controlled. The reality is often much uglier.

Yota Trom says scarcity leaks. If you’re operating from that mindset, people feel it, even if you never say it outright. Her question stings: who wants to be part of a culture like that? She pushed it further by asking how you can be generous with other people if you’re not generous with yourself. That moves the conversation out of personal finance and into company culture.

The overlooked bit is what chronic money stress does while you’re still trying to lead well. It can show up as caution that looks sensible but is really fear. It can make you more defensive, tighter with people, more hesitant to hire, slower to spend where it matters, more transactional, and less trusting.

It also pulls you into short-term thinking. When money stress is constant, you start solving for immediate relief instead of better long-term decisions. You might call it prudence, but the team experiences it as pressure. And the people you most want around you usually don’t stay long in a culture shaped by private financial panic.

Damon Flowers pointed to another part people tend to leave out. Founder money stress is lonely. You can’t really take it to staff because then they start wondering whether they should look for another job. You can’t fully take it home either. So you end up carrying it in your own head, and it gets heavier. That isolation matters because people don’t make their clearest decisions when the financial pressure is constant and private.

Peter Watson made the case for taking less and keeping more inside the business. Founders should work out the minimum they can live on, then take that, and leave the rest in the company. That can give a business breathing room. It can leave you with more room to survive, invest, and move when opportunities appear. Some founders do win that way.

But Peter also shows the trade-off. Even later, after the business had improved, he was still pricing purchases against an old £5-an-hour wage. He describes how hard it is to “unlock” that after years of living so frugally. Extreme discipline can help a founder survive. It can also rewire their relationship with money in ways that don’t disappear once survival is no longer the issue.

A founder taking less for a while can be rational. A founder who stays so underpaid that they become distracted, anxious, reactive, isolated, resentful, or mentally worn down is no longer helping the company.

That was Melissa’s point. If you’re constantly in survival mode, you cannot make good decisions for your company. Once the strain starts affecting judgement, it’s already affecting the business.

None of this means founders need luxury first, or that every business can pay market-rate salaries from the start. It also doesn’t mean frugality is fake or that every rough period is a mistake.

It means the founder should not be the part of the business quietly breaking while everyone pretends it’s discipline.

The founder doesn’t need comfort first. They need enough stability to think clearly, lead properly, and keep building. Without that, the business pays for it.

Related Millennial Masters conversations

You push hard, things move, users show up, the dashboard looks alive, and it all feels like proof you’re getting somewhere.

That’s where founders start lying to themselves. Not because the numbers are fake, but because they are reading the wrong ones.

You can end up building confidence off the wrong signals and run the business into the ground without realising it until much later.

That’s why I invited to write this. He’s the founder of Inkjin, Europe’s tattoo marketplace, and has built startups across adtech and crypto.

What he gets into here is one of the easiest traps founders fall into early: mistaking movement for traction. 👇🏻

You have movement, not traction

The dashboard can look healthy and still tell you the wrong story. I’ve had to learn that for myself more than once.

Signups keep going up. Engagement is “solid.” Retention is just good enough to keep you optimistic. So you proceed: extend the roadmap, hire the next team member, raise the next round of funding. Three months later, growth has stalled, your burn is up, and you still feel no more certain.

The data wasn’t broken. The problem was what you thought it meant.

Motion can look like traction

Most startup dashboards are built around activity: who came, how long they stayed, how often they came back. A user can look, like, and come back, but still not be committed to you. This isn’t traction, it’s a warmup.

This gets worse when a startup has early momentum. Your first users came through word of mouth, a well-placed tweet, or your own relentless and very personal efforts to drag potential customers through every barrier the product had to offer.

That momentum is real, and it matters. But it’s also borrowed: from your marketing, your distribution, and your own effort as a founder. It only lasts as long as you keep pushing it.

The dashboard can be distracting because it never asks the harder question: Does anyone care enough about this product to make a serious investment in it?

The signal you actually want

Users will write to you to complain that the product is broken. They’ll ask for features that remove friction from their daily lives.

When something doesn’t work, they work around it instead of leaving. They email after you go quiet. They keep using it while they wait for a response.

The better metric is inconvenience. Would users be truly inconvenienced if you disappeared from their lives today? Not annoyed. Inconvenienced.

We misread our own product

Inkjin, our startup, helped users discover and connect directly with tattoo artists. We had very solid retention numbers. Users were spending a lot of time in the app, coming back repeatedly, looking through tattoo designs and artist bios.

They were doing what they needed to do, but the real decision-making was happening beyond the app: contacting artists, discussing designs, making final agreements.

Inkjin was helping people get there, but it hadn’t become the owner of commitment. The dashboard measured consideration at scale. It could not measure where the decision was made.

The harder signal came from artist feedback. When we asked artists who had contacted them and who had actually gone on to get tattooed, the answer was clear: we estimated that 20 to 30 monthly bookings were coming from Inkjin discovery and being completed outside Inkjin. The decisions were being made. We just weren’t tracking them.

So we changed our stance. We stripped down the dashboard. We stopped asking how many people were using it. We started asking who made a significant decision, who zeroed in on an artist and committed to an action, and who came back to that same decision two or three times. We changed how we tracked what counted.

The real traction test

Look at the past 30 days and, without hand-waving, answer three questions:

• Who actually acted on purchase intent?

• Who returned to the same decision a few times?

• Who could not do it without you?

If you can’t answer those clearly, that’s the signal. You aren’t measuring traction. You’re measuring motion. I run this test on our own product, and it makes me uncomfortable every single time.

If a company you’re evaluating cites daily active users, time on site, signups, a growing waitlist, or media mentions, you’re looking at motion.

Ask instead: who is dependent on this? Who gets upset when it breaks? What do users do tomorrow if this disappears?

If the answers are vague, the traction is borrowed. If the answers are specific, with named users or a concrete alternative, you’re getting closer to something real.

What this mistake costs

Founders who mistake motion for traction start making expensive decisions too early.

They add headcount, stretch the roadmap, and spend money as if demand is already there. It isn’t. The product still has attention, activity, and maybe even growth. What it doesn’t have yet is enough commitment to support those decisions.

Then the story turns defensive. “We had users but they didn’t convert. We just need more time. It’s a little early.” By then, the spend is already in the business and the runway is running out.

That’s how you end up building for demand that was never really there.

👤 Ilias Hatzis is the founder and CEO of Inkjin, Europe’s tattoo marketplace, and writes The Leap of Faith, where he shares what building startups has taught him about traction, growth, and the mistakes that compound. Connect with Ilias on LinkedIn.

The Leap of Faith

Thoughts and things I've learned building tech startups.

By Ilias Hatzis | Entrepreneur

Melissa Kwan has spent years building, selling, and starting again. By the time she launched eWebinar, she had a much clearer idea of what she wanted this time and what she was no longer willing to compromise on.

For a while, it looked like it was working. Then growth slowed, old habits started creeping back in, and she realised the problem was not just effort or execution. It started earlier.

Sometimes the market does not understand the problem the way you think it does, and no amount of pushing fixes that until the positioning gets clearer.

In this episode, we get into lifestyle by design, founder drift, weak positioning, pricing, hiring, burnout, and the cost of staying too long in a business that no longer fits.

🔗 Find Melissa on LinkedIn and Substack

Key takeaways

1️⃣ A business can outgrow the life you wanted

Melissa’s story is a good reminder that a business can be working and still be taking you in the wrong direction. What she wanted was freedom, flexibility, and a business that fit her life. Over time, parts of the company started pulling her back into a version of work she didn’t want to return to. Growth on its own doesn’t tell you whether the business is still taking you where you meant to go.

2️⃣ Weak positioning makes everything harder

When the market doesn’t quite get what you are, everything around it gets harder. Sales gets heavier. Marketing gets less clear. The team ends up spending too much time explaining something that should make sense much faster. Melissa’s point with purple ocean is that you don’t always need a completely new category. You need the right people to understand why your product matters and why they should choose it.

3️⃣ More effort will not fix a message problem

When growth slows, the instinct is usually to push harder. Melissa’s experience points to something more uncomfortable. Sometimes the real issue is that the message is off, the market is reading the product differently, or the offer is landing in the wrong place. At that point, more activity just burns energy. You need to get closer to the actual commercial problem before adding more effort.

4️⃣ Founder drift happens slowly

Sometimes founders end up in roles they were never meant to keep doing. It rarely happens all at once. You make one compromise, then another, then suddenly your week is full of things that don’t suit your strengths or the life you were trying to build. That’s what makes drift dangerous. It doesn’t feel dramatic while it’s happening. It just leaves you running a business that feels heavier than it should.

5️⃣ Staying too long has a real cost

Melissa was very clear on the cost of hanging on when something is no longer right. Founders often frame that as resilience, patience, or commitment. The longer you stay in the wrong setup, the more energy it eats and the harder it becomes to see clearly. That applies to offers, pricing, hiring, positioning, and the shape of the company itself. Knowing when something no longer fits is part of building well, not failure.

In this episode

00:00 Meet Melissa Kwan

01:50 Leaving corporate behind

03:14 Building a business from zero

07:21 Turning services into a product

09:38 Bootstrapping, debt, and profitability

12:40 Finding a model that fits

15:38 What “lifestyle business” really means

18:55 Choosing a problem you care about

21:30 When sales is the wrong channel

23:55 What stopped working in marketing

26:47 The challenge she couldn’t ignore

29:29 Rethinking the identity of the business

32:11 The inner work that changed everything

41:41 Treating sales like a science

43:26 Taking marketing back in-house

45:42 Hiring without losing the culture

47:15 Pricing mistakes and what they cost

52:48 Getting to real product-market fit

57:43 Building something you can sustain

01:01:22 The sacrifices behind the freedom

📚 Melissa’s book recommendations

The Presentation Secrets of Steve Jobs by Carmine Gallo — Melissa describes it as more than a sales book and uses it as a communication playbook for pitches, positioning, and landing pages. A good one if you want to get better at saying the right thing in a way people actually hear.

Questions Are the Answer by Tom Freese — A strong sales and communication read for founders who want to get better at guiding conversations, understanding buyer pain, and asking better questions instead of rushing into the pitch.

The Alchemist by Paulo Coelho — A simple one, but one that stays with people. Good for founders who need a reminder about instinct, direction, and staying close to what matters when the path gets messy.

Luck matters, yes. It just gets blamed for too much while the ordinary reasons companies fail are sitting there in plain sight.

That’s the argument Bernie Bulkin makes in his new book Why Start-Ups Fail, which I’ve been reading this month.

When you’re in the thick of it, with tech, staff, product, and constant questions all going wrong at once, you do not always see it clearly. Some distance changes that. 👇🏻

Failure gets dressed up

Failure gets talked about as courage, bad timing, or the cost of trying something ambitious. Founders get to sound brave and investors get to shrug off dead companies as the cost of backing the future.

Bulkin is critical of the venture model here. A fund does not need a portfolio full of strong, well-run businesses. It needs one or two huge outcomes big enough to pay for a long list of write-offs.

That leaves founders in a different game from the people backing them. You are trying to build something that survives. A fund built around home runs can ignore a perfectly good business if the upside is not big enough. If it goes wrong, you are the one left living with the consequences.

He also shows how easily this gets cleaned up after the fact. Bad decisions start sounding like ambition. Failure starts sounding like proof you were serious, when often it was just bad judgement with better PR around it.

Where the boring damage starts

One of the easiest mistakes to miss is the gap between proving something can work and building a business around it.

Something works in a lab, a prototype gets built, a demo lands, and people act like the hard part is over. It usually is not. Science proves something can work. Engineering turns it into something repeatable, reliable, affordable, and scalable.

Building one impressive thing is not the same as building a system that can produce ten thousand of them properly.

The same thing happens in the market. Founders love a big TAM, but the harder question is how the market actually works. A giant market means very little if you do not know who actually buys, how they buy, who sits in the middle, and what it takes to get them ready to buy.

Enterprise sales are no different. Founders love talking as if they are going to sell straight into Shell, Ford, or another giant incumbent. In practice, a lot of those industries buy through procurement chains, tiered suppliers, and middlemen. The buyer is often a lot less glamorous than the logo on the pitch deck.

Then they burn months in meetings and pilots while nobody buys. A big market does not help much if your company cannot actually reach the buyer.

The money usually goes wrong earlier

After 21 years in venture capital, Bulkin knows running out of money is usually not the whole story.

By the time the money runs out, the real damage has usually been building for a while. The company was underfunded, or the founder kept cutting the wrong things and calling it discipline.

A lot of founders tell themselves they are being disciplined when they raise too little to avoid dilution. Then they spend the next year stuck in fundraising mode, preserving a larger share of a weaker company while starving the thing they were supposed to be building.

Work that looks non-essential gets pushed back until you realise it was holding the structure up. IP protection gets delayed. Market work gets skipped. Nobody gets a proper grip on the numbers early enough. The company starts penny-pinching and ends up broken underneath.

He makes the same point with cash timing. Founders model salaries and rent, then act surprised when inventory timing wrecks them. Paying suppliers long before customers pay you is part of how the business works. If you do not understand that gap early, growth can make the company weaker, not stronger.

Valuations create another version of the same problem. High paper valuations can narrow the ways out, inflate expectations, and turn sensible outcomes into disappointments for the wrong people on the cap table. That kind of valuation can make the business much harder to save later.

Then the founder becomes the problem

This is the bit that can sting. The founder who is right in year one is often wrong by year three. What gets a company off the ground often starts causing problems later.

Bulkin’s founder types are easy to recognise. The technical founder who never really becomes someone who can run the business. The fundraiser who is stronger in pitch rooms than inside the company. The arrogant one who cannot hear challenge.

Once the company gets bigger, those weaknesses stop being quirks and start doing damage. Startups still give too much credit to confidence, visibility, and a good story long after the business needs something else.

It’s easier to keep telling a story about a bold founder changing the world than to admit the company needed someone different to lead it and never got that.

Most startups die because the boring bits were not taken seriously enough. The ones that stay alive usually take them seriously early. They understand how the business actually works, from engineering to buyers to cash, and they know when the founder has to change with the company.

Bernie Bulkin also gets into how founders can stay out of some of these lethal traps. I’m turning that into a separate Millennial Masters feature. In the meantime, you can get Why Start-Ups Fail here.

That’s usually where things start slipping. The pitch gets stronger, the business underneath it gets harder to explain, and one simple question can give that away very quickly.

That’s why I asked Montgomery to write this guest piece. She’s backed multiple companies that reached billion-dollar outcomes, writes the Angels and Unicorns newsletter, and has a new book coming out under the same name.

What she gets into here is one of the clearest investor tells I’ve read in a while. 👇🏻

The pitch is working 🔍 The business isn’t

The pitch was excellent. It had a tight narrative, a clear picture of the market, and the founder knew their fundraising history cold. He also had a decent answer on competition.

He was also wearing a Patagonia vest, which somehow felt on-brand for the whole thing. By the time the deck ended he’d said the word “momentum” five times. I remember because it’s one of the words I always keep a tally of when I’m being pitched.

I made one request. “Walk me through last month.”

The long pause was eventually followed by, “We’re seeing really strong traction across multiple channels and the market response has been very positive.” I stopped taking notes.

That’s not a business update, it’s a brand statement. I’ve heard a version of it in more first meetings than I care to count, usually from founders who’ve spent three months on the pitch narrative and about seven minutes on their numbers.

What I’m actually watching for

By the time I’ve agreed to meet you, I’m not really watching the deck. The deck is what got us in the room in the first place.

I’m watching for the gap between what you’re saying and what’s actually happening in the business. This is easier to spot when I’m tired and grumpy, which probably says something unflattering about late afternoon slots.

A deck is designed to close that gap. If it got us together, then it’s a good deck. You’ve worked hard on it. But the gap shows up in how you answer the question that wasn’t in the prep and that no deck ever covers.

So I make the same request in every first meeting. Not because I’m so smart, but because it works and I haven’t found anything better.

Walk me through last month

Founders who know their business can usually answer in under sixty seconds. They give me one number and what moved it, or one decision they made or didn’t.

Whether the number is good or bad is almost beside the point, which still surprises some people when I say it. What I’m looking for is operational clarity.

Founders who are running on narrative answer with narrative. Trends. Channel response. Market signals. Healthy pipeline. No number, no cause, no decision.

The longer the answer, the wider the gap. I’ve never had a founder answer like that and turn out to be running a tight business underneath it.

Maybe the exception exists somewhere. I’ve mostly stopped expecting it.

The thing I don’t know how to fix

Most founders in a fundraising process have spent more time on the pitch than on their operating data in the months leading up to it. I understand why. The pitch gets you in the room. Nobody schedules a meeting because your MRR tracking is clean.

But somewhere in the preparation, the pitch stops being a representation of the business and starts replacing it. The story becomes load-bearing and the founder starts knowing their TAM better than what happened last month.

The strange thing is that by the time they’re in front of me, they’re not exactly lying. They’ve just been in pitch mode long enough that the pitch feels like truth.

I don’t have a clean answer to this. The obvious one is “stay close to your numbers”, but founders raising a round are doing twelve things and the numbers rarely feel like the most urgent one.

What I can tell you is that the founders who stay in contact with their operating data during a raise are noticeably easier to talk to. The meeting just feels different, more relaxed and less performative.

If you’ve already closed a round

Don’t think this stops applying once you’ve raised. You’ll likely raise again.

The next round’s investors will be later stage, less patient with narrative, and quicker to spot the gap. What passes at seed doesn’t pass at Series A.

Not because Series A investors are smarter, but because they’ve sat through more of these meetings and the filter gets tighter with exposure.

Run the test on yourself now. What’s your answer? Pick last month. One number and what caused it. One decision you made as a result. Say it out loud. Time it. If you can’t do it cleanly in sixty seconds, it’s worth asking why before someone else does.

The pitch should be good. That part’s not wrong. It just shouldn’t be the thing you know best when you walk in.

👤 Susan Montgomery backed 13 unicorns at pre-seed and seed. In Angels and Unicorns, she writes about what investors are actually clocking in those first ten minutes, and why founders often miss it until it’s too late. Subscribe for a clearer view from the other side of the table.

Susan | Angel Investor

I backed 13 ‘unicorns’ at pre-seed and seed. Writing for angels who want better returns and for startup founders who want their attention.

Two more reads before your next investor pitch

His background spans data science, product, healthcare, education, and workforce transformation. That gives him a clearer view than most of where AI is genuinely helping and where it is making things worse.

A lot of companies say they are investing in AI when what they really mean is they bought a tool, opened a few licences, and hoped for the best. Ben’s view is more grounded. Most AI projects fail because the basics are weak: poor data, weak guardrails, little training, no real change management, and no clear idea of what the tool should actually be doing.

In this episode, we get into why AI is still misunderstood inside businesses, why treating it like simple automation causes problems, how leaders should think about upskilling, and what changes when junior work starts disappearing first.

🔗 Find Ben on LinkedIn and his website

Key takeaways

1️⃣ AI doesn’t understand, it predicts

That sounds obvious, but a lot of founders still use it as if it knows what it is doing. Ben’s point is that AI is not reasoning through your company like a smart operator. It is making probability-based guesses. That is why weak prompts, messy data, and vague instructions lead to rubbish output.

2️⃣ AI projects fail because they’re not shortcuts

The big mistake is buying a licence, plugging in a tool, and expecting transformation. Ben kept coming back to the same point: no setup, no guardrails, no training, no real change management. That is why so many AI rollouts fall apart. The problem is rarely the model on its own.

3️⃣ AI works best when it makes your people better

The strongest use case here was not full replacement. It was augmentation. If your best people can move faster, make fewer mistakes, and handle more with the same headcount, that is a real gain. A lot of founders jump too quickly to cost-cutting when the bigger upside is better output.

4️⃣ Data hygiene is still boring and still decisive

A lot of AI talk skips the ugly part. Bad data in, bad output out. Ben was clear that if your systems are messy, siloed, inconsistent, or badly formatted, AI is going to magnify that weakness rather than solve it. Founders love the shiny layer. The real work usually starts underneath it.

5️⃣ Junior roles are going, so you need to learn faster

This was one of the most uncomfortable parts of the conversation. Entry-level work in coding, support, marketing, and data-heavy roles is already getting squeezed. Waiting for that trend to reverse is a bad bet. The better move is to build skills that sit on both sides of the shift: how to work with AI, and how to stay strong at the human parts it still cannot do well.

In this episode

00:00 Introduction to Ben Tasker

01:37 Data came before AI did

03:27 ChatGPT changed what people think AI is

06:16 Useful does not mean trustworthy

09:33 AI is not the same as automation

11:57 The right AI job depends on the size of the business

14:52 AI can guide you, but it cannot think for you

16:49 Start small before you break something bigger

19:17 What to check before AI goes live

21:21 Reviewing AI work without wasting time

26:32 Advanced work still needs human judgement

28:26 Human review is still doing the heavy lifting

29:19 Bad data will break good AI

33:10 AI skills are rising, human skills still matter

35:44 Fear makes people resist AI before they learn it

39:17 Junior roles are getting squeezed first

43:15 The better move is augmentation, not replacement

47:25 What businesses should do next with AI

We got into ChatGPT vs Claude, role-based AI setups, why weak output is often a setup problem, and what changes when you stop treating one tool like it should do every job.

A lighter one than the usual Millennial Masters podcast, but plenty in here if you’re trying to make AI more useful inside real work.👇🏻

What came up in the live

1️⃣ Stop using one chat for everything

A lot of weak AI use starts with people treating one chat like it should hold every task, tone, and context at once. Once the work gets more varied, that setup starts slipping fast. ⏱️ 08:19

2️⃣ One AI tool shouldn’t be doing five different jobs

Research, writing, editing, analysis, strategy, and admin all need different standards. A lot of disappointment starts when one tool gets asked to do too many of them badly. ⏱️ 11:33

3️⃣ If the output is weak, look at the setup first

Examples, tone, banned words, context, previous materials, and clear standards all matter more than you think. A lot of what gets blamed on the model is really bad setup upstream. ⏱️ 12:19

4️⃣ Voice dictation is still badly underused

If you’re still typing compressed prompts, you’re often starving the model of tone, detail, and intent. Speaking your thoughts out properly gives it much better raw material to work with, and it’s much faster than typing. ⏱️ 16:46

5️⃣ A better setup beats a clever prompt

Once the conversation moved into orchestrators, sub-agents, and repeatable workflows, the bigger point was that useful AI is less about clever prompts and more about building a better system around the work. ⏱️ 19:04

6️⃣ ChatGPT vs Claude matters less than you think

The useful question is not which one “wins” in the abstract, but which one fits the job, the workflow, and the level of context you need. Tool choice matters, but setup and role clarity matter more. ⏱️ 25:00

7️⃣ You still need to decide what stays human

Delegation matters, but so does judgement. AI can take work off your plate without taking the parts of the job that still need your taste, voice, and final call. ⏱️ 52:24

8️⃣ Good AI use looks more like management

Once AI becomes part of the workflow, the founder job starts looking less like “using a tool” and more like setting roles, standards, and feedback loops properly. ⏱️ 53:44

A few of the ideas we touched on came from these pieces:

Joel’s features: Start building AI teams | How to use Claude Cowork task scheduler | 5 Claude skills that save me 40 hrs | Cross-domain thinking as an AI skill

Millennial Masters articles: You’re the AI manager now | Managing AI like a bad hire | What to delegate to AI without losing control | How not to sound like ChatGPT

I’ve been there, and it’s frustrating.

That’s why I asked executive coach and adviser to write about how to get aligned with your team and clear confusion before it turns into culture.

Kathy is a 2x CEO and COO, writes the Lead Without Limits newsletter, and works with leaders on fixing themselves before they start trying to fix everyone else. 👇🏻

Where confusion starts

When teams start missing things or doing work twice, the problem often starts earlier than you think.

The instruction sounded clear enough in the room. But once the work got moving, it turned out not to be clear at all.

That’s because capable people still need to know what’s actually being asked of them.

You thought you were clear

If you are a leader, especially early in your career, there is a bias a lot of organisations push on you: sound more confident than you feel.

I got that advice in my mid-twenties, just after stepping into my first executive role at a large media company.

My boss told me I would be more effective if I answered questions with more confidence and fewer caveats. What I heard was simple: stop sounding uncertain.

When I pushed back and said, what if I don’t know the answer, what if I’m not sure, he said to come off as sure. That’s what people expect.

What happens next is harder to notice. You get used to sounding certain, and after a while you stop checking whether people understood what you meant in the way you thought they would.

That’s where the question starts to matter. Instead of asking yourself whether you said it clearly, ask what the other person actually heard.

The team fills in the gaps

This problem doesn’t stop with the leader. It moves through the team as well.

In some teams, people learn quite quickly that asking too many questions makes them look slow or unsure. After a while, they stop asking and just try to keep up.

That’s one of the biggest gaps inside a team. People start acting as if they should already know what the leader meant and move forward without needing much else.

Something else happens as well. People learn to talk about what is going fine and stay quiet about the rest. Anything messy, unclear, or unfinished gets left unsaid.

Over time, fear starts shaping what people say and what they hold back. The team gets less honest about what is not working, and problems stay untouched for longer than they should.

Where the damage shows up

This starts in a very ordinary way. Someone gives direction too quickly, assumes it was clear enough, and moves on.

I know because I was one of those leaders. My to-do list was so long it could not be done in a day, sometimes not even in a year.

In a startup environment, it can feel like the whole organisation is sitting on your shoulders. When that pressure builds, speed feels like the only sensible response because everyone is waiting on you.

That’s when the direction goes out too quickly and some of the detail gets lost.

The team feels the rush as much as they hear the words, so people stop looking for more context and move ahead with whatever they think they understood.

Then it spreads. One unclear conversation becomes several, and by the time it reaches vendors or partners, people are already working from different versions of the same expectation.

You start seeing work repeated, and people get frustrated with each other because they don’t realise they’re working on the same thing.

After a while, trust starts to go because nobody is completely sure what was meant to happen or who was meant to do it.

You don’t need a weak team for that to happen. It can happen with good people when the expectation was never as clear as everyone thought.

Most “clarifying” makes it worse

One of the biggest mistakes you can make at this point is deciding for yourself what needs clarifying instead of finding out what the other person actually took from it.

You can try to fix the problem by explaining more, but that does not always help.

Sometimes you answer the original question, add extra detail around it, and leave people more confused than they were to begin with.

Or you can say a lot more and still leave the real point untouched. What matters is whether you dealt with the part that had actually gone wrong.

That’s why the better question is not did I say it clearly? Ask what the other person actually heard.

The other mistake is treating clarification like another announcement. It works much better when it becomes a conversation.

Support is not control

Not everyone on your team needs the same level of oversight.

A newer team member who is still learning the role usually needs more check-ins. Someone experienced and motivated can work with much lighter ones.

I think about it as an 80/20 problem. For someone who needs more support, I might stay close to roughly 80% of the work in progress. For someone stronger and more self-directed, maybe 20%.

The numbers are not really the point. The point is that different people need different levels of support, and a lot of leaders forget that.

The next part gets missed a lot. Don’t just tell people when you will check in. Ask what helps them do the work well.

People don’t all need the same thing. One person may prefer to give updates in writing, while someone else works better by talking things through.

Someone learning something new might need a daily check-in for a while, and another person may find that amount of contact suffocating.

You don’t have to follow every preference, but it helps to understand what makes the work easier for each person to do well.

What will make a difference is building a way of working that gives people the support they actually need.

Silence is not alignment

When nobody has any questions, don’t assume that means things are clear. More often, people don’t feel safe enough to say what’s not making sense yet.

If everyone walks away from an important conversation saying “that was fine” or “sounds good,” and nobody has anything they want to push on, that should worry you.

A team that’s really thinking something through will want to test at least one part of it. They might ask what happens if this goes wrong, or whether something has been missed.

The same thing applies in one-to-ones. If you want the real answer, give people a heads-up that you want their honest read on something specific, and be clear about what you are asking. Then ask and pause.

It’s easy to rush in and fill the silence too quickly. Leave it there for a moment, and that’s usually when people say what they really think.

Start where the cost is highest

Start with one or two things, not ten.

Sit down and ask where the biggest gap is right now. You don’t need the full picture straight away. Focus on the area where unclear expectations are causing the most trouble or wasting the most time.

Write it down, be honest about what is not working, and then do the part most leaders resist by naming it openly with your team.

You don’t have to have it figured out. You can say: I’m not sure I’ve been setting clear enough expectations in this area. I want to do better, and I’d like to understand what you need.

That kind of honesty doesn’t weaken your authority. It gives people room to tell you what is actually getting in the way.

Then get specific about the gap. Are you clear on the outcome but vague on how people should get there? Or have you been clear on behaviour without explaining why it matters? Start there.

Build in one way of checking this and actually use it, starting with the area that matters most and the team closest to it.

Change shows up in the work first

You’ll feel the difference before you can measure it properly.

People start saying sooner when something is unclear, and problems get picked up before they have had time to spread.

That’s the first sign things are getting clearer. The team spends less time cleaning up confusion later because more of it gets dealt with properly at the start.

👤 Kathy Wu Brady is an executive coach and adviser, a 2x CEO and 2x COO, and the writer behind Lead Without Limits. She has spent 20 years launching, scaling, and reshaping businesses across five industries, and now helps leaders make clearer decisions and lead with more courage. Connect with Kathy on LinkedIn

Lead without Limits

Find your path to meaning and success with the help of a 2x CEO & COO, executive coach, and artist who's been in the arena.

By Kathy Wu Brady

🤜🤛 More teamwork from Millennial Masters

Before founding Cosmic Universe, she worked in journalism and SEO, watching in real time what people searched for, what they clicked, and what they kept coming back to. One pattern stood out. Astrology was not a side interest or a joke category. The demand was huge, the audience was engaged, and the market was much bigger than most people realised.

That insight became Cosmic, a personality and connection platform built around astrology, compatibility, and live experiences. What sounds niche on paper has turned into something much more interesting in practice: a business sitting at the intersection of identity, loneliness, self-discovery, and how people now try to connect.

In this episode, we get into why Michelle left journalism to build something of her own, what she saw in the data that others missed, and how she is building in a space a lot of people still do not take seriously.

We also talk about solo founder pressure, motherhood while building, user behaviour, scepticism, and what it takes to keep going when you know the opportunity is real before everyone else does.

🔗 Find Michelle on LinkedIn

Key takeaways

1️⃣ Search demand tells you what people actually want

People say all sorts of things. Search is harder to fake. Michelle saw a huge volume of demand around astrology, compatibility, and personality long before most people would have treated it like a serious business signal. Attention leaves clues. Founders who know where to look can spot a market before it looks respectable.

2️⃣ A business people dismiss can still be a great one

Plenty of people don’t take astrology seriously. That did not stop the market being real. If anything, the scepticism gave her room to build without too much noise. Founders spend too much time chasing ideas that already look credible instead of backing something with real pull.

3️⃣ Connection is the product now

The app was never just about content. The real signal was what people were asking for underneath it: love, compatibility, self-discovery, someone to meet. That is what pushed the business into live events. When users keep showing you the same emotional need, pay attention. That is usually where the bigger opportunity sits.

4️⃣ Building alone gets loud in your head

Solo founder pressure is different. There is no one next to you to split the weight when a decision is on you and the stakes are real. Data helps, but it does not remove doubt. You still need ways to get out of your own head, reset, and come back clearer.

5️⃣ You don’t need universal approval to build something real

Trying to make everyone take your idea seriously is a waste of time. The better move is to get close to the people who already want what you are making and build for them properly. Once the traction is there, the outside scepticism matters a lot less.

In this episode

00:00 Introduction to Michelle Bell

01:36 Journalism trained her for founder pressure

04:24 She spotted a real astrology market

08:15 A different answer to dating app fatigue

10:45 Turning the app into live events

13:02 People want connection but avoid the risk

15:38 The pressure of being a solo founder

18:39 Measuring meaningful connection

20:57 Social media still drives growth

23:21 What sceptics miss about astrology

26:34 Why founders are wired differently

29:12 When personality helps or hurts leadership

30:43 Building a business through motherhood

32:13 Building in a space people dismiss

34:21 Community matters more than audience

37:18 What power users do differently

39:33 Motherhood, work, and constant adjustment

43:12 New York, London, and raising children

44:31 Why walking clears her head

46:00 Growth means changing your mind

47:55 The reality behind building a business

If AI keeps giving you bland writing, obvious ideas, and work you still have to rescue, the problem usually is not the model.

You haven’t really trained it, briefed it, or given it enough context to do the job well. You’ve been throwing work at it and hoping for the best.

You wouldn’t onboard a human hire this way. AI is no different.

To get real value from it, you need to treat AI more like staff and take the time to train it properly. That’s the point Millennial Masters guests keep coming back to.

A better question is what a new hire would need to know in order to do this well. Ask it that way and the mistake becomes obvious. 👇🏻

You skipped the onboarding

Carly Meyers explained it in the clearest way I’ve heard: “Think of it like one person. Think of it like you’ve just hired someone.

“Say you just hired a sales and marketing person. They’ve walked into your office for the first time. You sit them down and say, right, this is what I want you to do.”

That’s the part most founders skip. They don’t explain the business properly or spell out who the customer is.

They also don’t show the AI what the brand sounds like, what counts as good work, what needs approval, or where it should stay in its lane.

They start with tasks, which is the same mistake people make with new hires when they are moving too fast. Things get messy quickly.

That’s not new. Strong hires still need context, and good employees take time to become useful. Throw someone into the middle of the business without proper onboarding and the work usually comes back half-baked.

Then AI gets treated as if none of that applies. The expectation is close to finished output on day one, and when it disappoints, the tool gets the blame.

This is a management problem

Damon Flowers was direct: “AI is like a staff member and it can do anything. It can do finances, it can do marketing, it can have a conversation with you and negotiate stuff.

“But you’ve got to be really good at training it around who it is, what’s the role, what context you’re giving it, and what do you specifically want it to go do for you.”

That’s the shift a lot of founders still haven’t made.

If AI is sitting inside your workflow like a member of staff, the output depends on the job you have given it and how clearly you have set it up.

If that setup is vague, the output usually comes back vague too. You get writing, research, strategy, and sales copy that could belong to almost anyone.

Jess Jensen made the same point: “I think of AI as almost like a junior employee. The more that I train and invest in that junior employee to get them to understand our strategy, our goals, our vision, who I am, the better the output’s going to be because now they’re really tracking with me.”

That’s a much better approach than treating AI like a one-shot tool. The quality improves when it starts following how you think and the standards you work to.

Open a fresh window, type a request, get something back, and judge the whole experience on that one exchange. Of course the output will disappoint.

There’s no real context, no memory worth using, no examples from previous work, and no proper explanation of how the business operates.

Ryan Carruthers described AI as “a marketing or copywriting assistant right now… like having a graduate, someone who’s just getting into it, who’s starting to learn the frameworks.”

That’s useful because it brings the expectation back down to earth. A graduate can help and save you time. They can also waste a lot of time if you expect them to understand the business from one instruction and a few scraps of documentation.

You’re expecting senior output from something you barely trained, then blaming the tool when it cannot deliver.

Give it a job first

Start by getting clear on the role. A lot of AI use is still far too broad.

If you ask it to be a strategist, researcher, editor, analyst, and operator all at once, it ends up being none of them properly. If you want better work, define exactly what role it is supposed to play in the business.

That might mean a copy assistant, a research analyst, a sales support function, a coding reviewer, or an editorial second pair of eyes. The more precise the role, the easier it becomes to train well.

Carly Meyers’ framing helps here. One “person” does one type of work. The AI is no longer guessing what it is there to do.

The practical test is simple. If a human joined your team tomorrow and got this exact brief, would they know what role they were in and what good looked like in that role? If the answer is no, the AI will struggle too.

Once the role is clear, context starts doing most of the heavy lifting. A lot of people cut corners here because giving context feels slower than prompting. Skip it and the quality usually falls apart.

Nick Holzherr described AI as “a distributed team member,” which is useful because anyone working outside the room needs clear documentation to do the job properly. Nobody expects remote employees to just pick all of that up on their own.

It has to be written down somewhere, with examples and enough detail for someone to understand how the company operates. AI is no different.

That’s why businesses with decent documentation and defined processes often get stronger results from AI sooner. The material needed to train it already exists.

If everything is still sitting in your own head, the output is usually worse because the AI is being asked to work inside a business that has never been clearly articulated.

Teach it what good looks like

You get weak output when you expect AI to pick up voice and standards from nothing. Give it a clear sense of how the business sounds at its best.

That means showing it strong examples of how you write, sell, and communicate, along with the kinds of phrasing or claims you do not want it using.

This matters because voice is not decoration. In a lot of businesses, it carries judgement. It tells you whether something feels salesy, technical, or generic. Leave that undefined and the model usually fills the gap with average internet sludge it’s been trained on.

Yota Trom uses AI as an editor rather than a creator, saying it helps her because she’s not a native speaker. That’s a useful boundary. It gives the AI a clear job and makes it easier to see what should still stay with the human.

The same thing applies to the goal of the task. If you ask for writing, research, summaries, or strategy thinking without explaining what the work is supposed to achieve, the AI has to guess what good looks like, and the output usually gets weaker.

When the task has a clear purpose, the output usually improves. AI is no different.

Constraints matter too. If it cannot make claims without sources, say that. If it should not sound too polished, say that. If it needs to protect margin, stay within brand language, or avoid legal overreach, make that clear as well.

You don’t need a perfect instruction sheet for every task. You need to stop expecting AI to know the business better than the person using it.

This is where it gets useful

Don’t ignore this part because it is less exciting than trying a new tool.

The quality improves when you start correcting the work and letting that shape the next round. That is how a useful working relationship develops, whether it is a junior hire or a custom GPT.

Jess Jensen’s point about investing in the junior employee matters here. It takes repetition, correction, and enough patience to build something better over time instead of opening a fresh session and starting the whole disappointment cycle again.

What looks like the model getting smarter is often just better management. That is where the gains stop being theoretical.

Once the system is trained properly, more first-pass work gets handled before a human steps in. Drafts come together faster, research is easier to pull together, and more of the admin-heavy work gets moved off people’s plates.

James Augustin thinks about AI automation as taking the admin-heavy parts of a role away so people can focus on the work they are actually good at and paid for.

Ryan Carruthers gave a similar example when he described building an AI that could handle after-hours sales work, gather the right information, and book calls so nobody on the human sales team had to keep carrying that burden late into the evening.

Damon Flowers sees it as getting work to 85 to 95% done before a person even touches it. That number will vary by task, but the principle is right.

At that point, you are reviewing and refining far more often than you are starting from scratch. That’s where the time starts coming back.

The real mistake you are making

AI is starting to expose which businesses are systemised and which still live mostly in the founder’s head.

Weak output comes from shoddy setup. The role is vague, the context is thin, the standards live in your head, and then the tool gets blamed for sounding half-baked.

You’re expecting too much from something you’ve barely trained.

That’s why this is more fixable than you think.

You don’t need a better model to get better results. You need to brief it clearly, train it properly, give it feedback, and hold the standard.

Do that and you’ll get more from AI than most people complaining about it ever will.

I first heard it mentioned in one of my early Millennial Masters interviews with Yehong Zhu, who referenced Nassim Taleb’s Antifragile in her book recommendations.

By then, I had already lived through years where stability disappeared.

The pandemic period, especially 2020 through 2022, was one of the hardest stretches I’ve had in business and in life.

I had seen the shocks, the uncertainty, and plans breaking down without having a useful language for it, let alone a framework for how to respond.

That is why ’s take stood out. When we spoke about antifragility and I read how he translated it into the day-to-day reality of running a company, I knew it would make a strong guest post for Millennial Masters.

His piece below turns antifragility into something far more useful than theory. It is the practical version of what founders can do when the old playbook stops working. 👇🏻

How you build for shocks

It is easy to get used to a stretch where demand is steady, costs are predictable, and suppliers pick up the phone.

That has not been the world for a while now. Tariffs shift, energy prices move, and supplier pricing changes without much warning.

A Harvard survey of more than 4,000 SMBs found that nearly half of owners misjudged how tariffs were affecting their costs.

That is not because small operators are careless. It is because the world around them is changing faster than most people can track while still trying to run a business day to day.

Last October, I published a detailed piece on Operating translating Nassim Taleb’s ideas on antifragility into business practice. The framework still holds up, but frameworks do not pay invoices.

This is the practical version. It is for the founder with 12 employees, one line of credit, and a Monday morning stand-up with very little patience for theory.

By antifragile, I mean a company that can take a shock and come out stronger on the other side. The goal is to build in a way that leaves you better placed when things move against you.

The 5 buffers that keep you in the game

Buffers are what keep a bad quarter from becoming a crisis.

If they are too thin, one shock can put you on the back foot. If they are strong enough, you have time to respond and, sometimes, enough room to take advantage.

1️⃣ Cash

How many weeks can you operate if revenue drops 30 percent tomorrow? Not based on a trailing twelve-month average, but on your actual weekly burn against your actual cash balance.

If the answer is less than eight weeks, that deserves your attention before almost anything else. When I was scaling R.G. Brewton from $27 million to north of $75 million in industrial distribution, the metric that gave us permission to be aggressive was knowing exactly how many weeks of runway we had.

2️⃣ Time

Slow decisions kill small companies faster than most bad decisions do. How many days does it take you to reprice a product, switch a supplier, or shut down a project that is bleeding money?

If the answer is weeks, you have a problem. Tariff policy changed eleven times in six months last year. The founders who got through it repriced in 48 hours. The ones who waited absorbed the margin hit.

3️⃣ Pipeline

If your top three clients represent more than 50% of revenue, your P&L can look steadier than it really is. It holds until one of them leaves, delays payment, or renegotiates terms.

Concentration risk is one of the most common buffer gaps I see in advisory work. It does not show up on a dashboard. It shows up on a Tuesday morning phone call.

4️⃣ Talent

Name every person in your company who is a single point of failure for a critical process. If that person gets sick, quits, or burns out, what breaks?

That is a structural weakness. Cross-train the role or document the process. Do that this month.

5️⃣ Suppliers

How many of your key inputs come from one source, one country, or one contract with no pre-vetted alternative?

In B2B distribution, we kept backup supplier relationships for every critical SKU category. Not because we assumed we would need them, but because if we did, there would be no time to start from scratch.

Small bets and fast feedback loops

Taleb’s barbell strategy is simple. Keep 80 to 90% of resources in proven work that pays the bills. Put 10 to 20% into small bets with real upside. The danger sits in the middle: the mid-budget initiative with medium conviction and no kill switch.

For a small company, a small bet is not something you talk about on a strategy retreat. It might be a landing page with $300 in ad spend behind a new offer, a pilot engagement with one client in a new vertical, or a price test on a single product line for two weeks.

What matters is that the hypothesis is written down before you spend the money, the downside is capped, and the timeline is short enough to read before the next move.

The kill rule matters more than the bet itself. Define what failure looks like before you start, not after sunk cost fallacy has you giving it another month. If a test cannot show signal within two to four weeks, it is either too slow or being measured badly.

Review active bets once a week. Spend fifteen minutes looking at what is still open, what should be killed, and what is showing enough signal to push harder.

Done properly, this is how small wins start to stack without small losses quietly piling up underneath them.

Guardrails to stop a bad month from spiralling

One bad month is manageable. The problem starts when a second bad month passes with no real response and a third is allowed to land on top of it. What matters most is how quickly you react.

This comes down to urgency, both yours and your team’s.

Three triggers should force a same-week decision:

• Cash drops below your minimum weeks-of-coverage threshold

• A top-three client signals churn or payment delay

• The cost of a key input spikes by more than 15% with no clear date for it to come back down

When one of those triggers fires, do not leave it hanging. Make the call that week. The response might be small. Reprice one line, pause one project, or call one client. What matters is that you move.

Run a subtraction audit once per quarter. List every recurring cost, meeting, subscription, and initiative, then cut the bottom 10 to 15%. This is not about being tidy. It is about reducing the number of places where a shock can hurt you.

Every unnecessary cost gives rising prices another place to squeeze margin. Every unnecessary meeting takes time away from fixing what matters when something breaks.

Before any commitment above a number that matters to your business, spend ten minutes writing down how it could fail and whether the structure of the bet protects you if it does. It is Taleb’s premortem at founder scale.

It takes ten minutes. It has saved me from more bad decisions than any financial model.

5 items. 10 minutes. Weekly.

That is the entire system. No single review will change much on its own. The value comes from doing it 52 weeks in a row.

The forecast is dead. Your business shouldn’t be.

You cannot run a company as if conditions will stay still long enough for the spreadsheet to catch up.

What matters more is whether the business can absorb pressure, respond quickly, and adjust when something changes.

This is practical, not theoretical. The founders who keep moving well under pressure are usually the ones who have already built for it.

👤 John Brewton writes Operating, a bestselling newsletter documenting the history and future of operating companies. He graduated Harvard University and began his career as a PhD student in economics at the University of Chicago. After selling his family’s B2B industrial distribution company in 2021, he spent the years since helping business owners, founders, and investors improve how they operate. He’s the founder of 6A East Partners, a research and advisory firm focused on the future of companies. He still cringes at his early LinkedIn posts and loves making content every day, despite protests from his wife, Fabiola. Connect with John on LinkedIn.

Operating by John Brewton

Weekly Reporting on the History & Future of Operating Companies

He’s a four-time CEO with two eight-figure exits, including taking one business from $3.5 million to $30 million in just two years.

Across those companies, he kept running into the same problem.

Growth would slow down, not because of the market or the product, but because too much still depended on the person running it.

Through his latest venture, Modern Operators, Damon works with businesses that already have traction.

The focus is simple: shift how the company runs so it no longer needs constant founder involvement to keep moving.

This conversation gets into what actually needs to change for that shift to happen and why working harder rarely fixes it.

🔗 Find Damon on LinkedIn

Key takeaways

1️⃣ You’re still too central to how things run

When too much flows through you, the business slows down as it grows. The fix starts with spotting where you’re still needed for decisions that should move without you. Remove yourself from those first.

2️⃣ More effort won’t fix a structural problem

Putting in extra hours keeps things moving for a while, but it doesn’t change how the business operates. Look at where work gets stuck or handed back to you and redesign that flow.

3️⃣ Growth without independence creates pressure

If the company needs your involvement to keep momentum, it adds weight as it expands. Start shifting ownership so progress continues even when you’re not in the loop.

4️⃣ The way you operate sets the standard

The structure of the business reflects the person running it. If you stay in the middle of everything, the company will keep pulling you back in. Changing that starts with how you show up day to day.

5️⃣ Stepping back needs structure, not intent

Wanting to be less involved isn’t enough. You need clear ownership, simple systems, and expectations that don’t rely on you stepping in when something breaks.

In this episode

00:00 Introduction to Damon Flowers

03:24 Early bruises in business

07:03 Knowing your strengths and blind spots

08:11 Better partners, better outcomes

12:08 Stepping out of the middle

18:16 Paying to buy back your time

20:56 Delegating the low-value work

23:43 Hiring, roles and handover

26:12 The lonely side of running a business

28:08 Getting staff to think like owners

30:40 Losing sight of the numbers

33:25 Cadence, dashboards and the right metrics

37:52 Stabilise, build, optimise, grow

41:39 AI inside the operating system

45:53 Training your team to use AI well

I spent years watching startups burn through funding, trying to out-build incumbents, and I made the same mistake on products I worked on.

The teams that lasted focused on less.

That lesson is why I asked to come back and break down how lean teams build competitive advantage.

In his last guest post, he broke down how to find gaps in a competitor’s strategy. This time, he walks through what to do once you find them. 👇🏻

The edge comes from precision

The trap most teams fall into with AI

Building an impressive demo is easier than ever with AI.

Competitors can spin up tools in a weekend that look great on the surface. But those screens rarely integrate with a customer’s existing setup, so they fall apart in real production.

Big competitors optimise for speed and broad appeal. Lean teams win by spotting small friction points those tools ignore and building around them.

AI design platform Magic Patterns reached $1M in ARR with no team. Co-founders Alexander Danilowicz and Teddy Ni built and scaled it on their own, managing to raise a $6M Series A.

Tools like v0, Bolt, and Lovable generate interfaces from prompts, but the output often feels generic and disconnected from the actual product.

Danilowicz and Ni came from front-end development, which shaped how they approached the problem.

They focused on design system integration, letting teams import their own components, so prototypes match the existing product from the start.

That focus created an advantage broad tools struggle to replicate without changing how they work.

How lean teams build moats

Saying no matters

Lean teams work within constraints, which forces focus.

Magic Patterns said no to customers who wanted backend support. They focused on product teams of 5–50 people working with existing design systems.

Each decision made the positioning clearer. Product teams with design systems created better expansion and retention than one-off project work.

A customer might start with a couple of licences and expand across the team as the product proves itself. You see the same pattern elsewhere.

In the AI meeting space, Granola made a similar decision. They ignored the mass transcription market and focused on C-level executives and VCs in sensitive meetings.

Both companies built multi-million-dollar businesses by committing to very specific customers, which shaped everything else they built.

Where the advantage actually comes from

Magic Patterns focused on understanding what product teams were trying to build and preserving that in the output.

The Chrome extension pulls structure from existing sites and reuses components so outputs match the product.

That keeps them strong in a specific part of front-end work where generic tools struggle.

Changing what each role can do

Speed doesn’t hold for long, so advantage comes from somewhere else.

Magic Patterns shifts what different roles can do inside a team. When Zeal’s CTO Pranab Krishnan started using it, he stopped writing long UX descriptions and began building interactive prototypes himself.

Engineers no longer wait on design handoffs, and they build with a clear sense of what can actually ship. Even product managers can lay out requirements visually. The product team can do more without adding new roles.

That kind of shift makes a tool hard to remove once a team adopts it. I break down the full strategy of Magic Patterns in more detail in Product Strategy Decoded.

The lean team competitive advantage audit

Three quick tests you can run on your product:

1️⃣ The rejection test

Who are you explicitly saying “no” to? If your product tries to serve very different customers at once, the focus disappears.

Pick the customer you understand best and build for them. Every customer you turn away sharpens how well you serve the ones you keep.

2️⃣ The workflow test

Does your product fit into how people already work? Magic Patterns integrated into the design systems teams already use.

AI tools that ignore existing context are easy to replace. The closer you are to real workflows, the harder it is to replace you.

3️⃣ The capability test

Are you only speeding things up, or changing who can do the work? Tools that only save time compete on shrinking margins.

Tools that let non-specialists contribute become part of how teams work. Does your product let new roles do work they couldn’t before?

The real advantage

Building advantage as a small team comes down to focus, not feature volume.

It comes from a clear understanding of the customer and helping them do things they couldn’t before.

Every market leader operates on a set of assumptions. Over time, those assumptions stop matching reality.

That’s where lean teams find their opening. They spot constraints larger competitors ignore and build for the customers who feel that gap most.

The competition becomes useful if you pay attention.

Start with one question: what are the biggest players in your market not set up to solve? That gap is where your advantage sits.

👤 Mike Goitein writes Product Strategy Decoded, where he reverse-engineers the strategy of products, startups, and creators using a proven framework. He’s a Certified Strategy Professional with over 15 years of experience helping Fortune 200 companies and startups alike sharpen their choices and deliver measurable results. Connect with Mike on LinkedIn.

Product Strategy Decoded

Every week, I pull back the curtain and make strategy easier using a proven framework. You'll get insights of what works today and why, with powerful takeaways you can apply to your own business.

By Mike Goitein

At Adidas, she helped launch the brand’s first Facebook presence. At Qualcomm, she worked directly with senior leaders on how they show up publicly and how trust is built online.

She now runs Copilot Communications, helping founders and executives build a presence that supports the business instead of hiding behind a brand.

In this episode, we get into why leaders stay quiet online, why polished messaging often gets ignored, and why trust and visibility take longer than people expect but pay off in ways most founders underestimate.

🔗 Find Jess on LinkedIn

Key takeaways

1️⃣ Your company cannot speak for you

A logo, a website, and a polished brand do not create real trust. People want to understand the person making decisions and setting direction. When founders stay invisible, the company feels distant and credibility grows slowly.

2️⃣ People judge the founder first

Before someone buys, partners, invests, or joins the team, they look at the person running the company. Your thinking, your values, and your judgment form an opinion long before a sales conversation ever starts.

3️⃣ Clear thinking travels further

What people remember is a founder explaining something well. A practical lesson, a point of view, or a story from the trenches carries far more weight than carefully manufactured marketing posts.

4️⃣ Authority comes from repetition

A few posts do not move the needle. Authority forms through steady presence over time as people start recognising the voice behind the company and paying attention to what that person says next.

5️⃣ Visibility is part of leadership now

Running a company now includes communicating publicly. Sharing how you think, what you believe, and what you are learning helps people understand the direction of the business and why it exists.

In this episode

00:00 Introduction to Jess Jensen

02:15 Early agency career and learning everything

07:14 MBA, Nestlé and the Fortune 500 path

09:58 Adidas, Facebook and early digital marketing

11:59 Microsoft, Qualcomm and the tech shift

15:01 What leaders can say beyond the company

17:41 Causes, values and leadership identity

20:35 Choosing Causes and charitable engagement

22:20 Why simple language builds trust

26:33 Why leadership can feel lonely

29:12 LinkedIn beyond the digital CV

32:24 Mixing personal and professional identity

35:23 Why imperfection builds trust

37:57 Why founders miss the audience

40:24 Leaders doing social media well

43:04 Should leaders outsource LinkedIn?

45:50 Using AI to shape better content

47:23 What entrepreneurship taught Jess

48:55 Why brand building takes time

Over the last two years I’ve lost a significant amount of weight using GLP-1 medications. They definitely work. The part nobody explains comes after.

I’ve tried all three of the big ones along the way: Ozempic, Wegovy and Mounjaro. I now stay on a small maintenance dose because the main thing people say about them is actually true.

Weight-loss injections quiet the constant thinking about eating. When that noise fades, a surprising amount of attention comes back to the work you actually care about. Anyone running a company knows how valuable that mental space can be.

The part people talk about less is what the process feels like while the weight is coming off. These drugs work by pushing your calorie intake down automatically.

When that happens your body runs on less fuel, which means energy can dip, mood can wobble a bit and exercise is usually the first thing that disappears from the week.

That’s usually the moment you realise the injection handles the appetite, while everything else still depends on you. You feel lighter on the scale while your body sometimes feels worse.

Another practical point is cost. Unless you have them prescribed, GLP-1s can become a serious monthly expense (up to £400). When you are spending that kind of money, it makes sense to think about how to get the best outcome from them instead of hoping the injection will solve everything on its own.

And sooner or later most people face the same question: what happens when you stop or reduce the dose, because the food noise returns and the habits underneath start running the show again.

That’s why I asked Tom Hutchinson-Smith about this.

Tom is a personal trainer I interviewed previously on Millennial Masters and he works mostly with founders and operators whose schedules look messy from the outside but still want their body to keep up with the demands of running a business.

I asked him to explain how GLP-1s actually fit into that reality and how training and nutrition keep the process from weakening the system underneath. 👇🏻

Why the injection suddenly makes sense

Founder life rarely supports neat routines around food.

The day fills with calls, travel, meetings and deadlines. Meals happen wherever they fit and hunger tends to appear at inconvenient moments.

Over time eating becomes something that constantly interrupts the day. GLP-1 medications change that environment quickly.

Hunger fades into the background and the urge to snack stops driving the schedule.

Meals shrink naturally and eating becomes something you do when needed rather than something you think about all day.

For someone already juggling a company that change feels like relief.

What the scale doesn’t show you

GLP-1 drugs make eating less much easier to maintain. That part works very well.

What they don’t do automatically is protect strength or muscle while bodyweight falls.

When calorie intake drops for months at a time the body adjusts. Muscle can shrink along with fat and strength in the gym slowly slips.

The scale continues moving in the direction people want, so this often goes unnoticed.

For founders that matters more than it might seem. Your body is the machine that carries long days, travel, pressure and constant decision making.

When strength fades the work feels heavier even though nothing in the calendar has changed.

The training that keeps your body intact

Tom’s advice to founders is deliberately simple because complicated plans rarely survive busy schedules.

Three strength sessions during the week keep muscle active while weight comes down. Each session fits inside an hour and focuses on movements that train large parts of the body at once.

The real focus is keeping the engine running properly while the rest of the business keeps moving.

When founders travel frequently Tom usually gives them a shorter hotel-gym version of the same routine so the habit doesn’t disappear during busy weeks.

Tom shared the exact framework he gives founders using GLP-1s. 👇🏻

Download The Lean Leader Program and use it as a practical guide.

What to eat when you barely feel hungry

When GLP-1s suppress appetite the amount of food drops quickly. That means the food you do eat needs to carry more of the workload.

Protein helps hold on to muscle during the weight loss phase. Vegetables help digestion and keep the body getting nutrients even when meals are smaller.

Dietary fat still matters for hormones and general health even though extremely heavy meals tend to feel uncomfortable on these medications.

Tom usually encourages founders to think less about strict dieting and more about building meals around protein and vegetables first.

This approach usually covers what the body needs without turning food into another project to manage.

The body that runs your business

GLP-1 medications are powerful tools and they genuinely help many people lose weight.

They remove the constant battle with appetite which used to make fat loss extremely difficult to sustain.

What they don’t replace is the physical foundation that keeps someone functioning well while running a business.

Strength training, regular movement and basic nutrition habits protect the body that supports your work. When those stay in place the weight loss process leaves someone lighter without leaving them weaker.

That outcome usually feels very different once the drug is no longer doing the work.

The number on the scale changes quickly. The condition of the body running the company matters far longer.

Discipline still decides the outcome

One part of the conversation that rarely gets mentioned is what happens if you stop taking the drugs.

From my own experience the food noise does not come back overnight, yet after about two weeks the difference becomes noticeable.

Hunger creeps back in, thoughts about snacks start appearing again, and that quiet mental space around food begins to shrink.

That is the reason I now stay on a very small maintenance dose. I do not always follow the seven-day schedule either. Sometimes it stretches to ten days, sometimes fourteen, usually depending on when I feel that background noise returning.

Keeping the result still comes down to discipline.

GLP-1 medications make the early stages of weight loss far easier to sustain, yet keeping the result afterwards depends on the habits that support your body when the drug is no longer doing the work.

If those habits disappear, the body gradually returns to old patterns.

The people who keep the result are usually the ones who built the habits while the drug was helping them.

Because once the noise returns, the discipline is yours.

Quick question for founders reading this:

If you’ve tried GLP-1 injections, what surprised you most about the experience?

I’m curious how others are navigating this.

More healthy stuff from Millennial Masters: