When you’re building something the market is seeing for the first time ever, that assumption breaks, and most of the time it breaks without you even knowing. This is the hardest part of GTM positioning for technical founders: the product is real, and the buyer still struggles to picture what they’re buying.
I figured this out on a pre-interview call with a French AI founder. His CV was the kind that makes you sit up straight. Time in the top labs. Peer relationships with people whose names you’d recognize from research papers. A dev tool that, on paper, was excellent. I wanted to feature him.
So I asked him the questions I always ask. Who’s your user? What pain sends them looking for you? How does the product turn that pain into growth?
And every time, he answered with capability, walking me through the architecture, the benchmarks, and everything the model could do. I kept steering toward the buyer, and he kept steering back to the tech.
I’ve taught more than two million people how to work with data and build with AI, and if a founder’s explanation of his own product makes my eyes glaze over, the problem sits with the explanation, and it stays with him. I had to pass on the feature. The product was fine. The founder was brilliant. The story needed a buyer inside it, and it had one missing.
I thought about that call a lot during a recent conversation with Amanda Ducach, because Amanda is what that founder could become. She’s the founder who solved the exact problem he was stuck on, and then kept going until she hit a harder one that most founders rarely earn the right to face.
The founder who walked away from easy money
Amanda is CEO and co-founder of Ema, the AI for women’s health. Start with the decision that tells you who she is.
Between 2020 and 2024, Amanda kept Ema in stealth for four straight years. Over that stretch, companies came to her hoping to advertise through the product. Easy revenue, sitting right there. She turned it down.
Paid placements would have quietly corrupted the one thing Ema exists to do, which is drive a positive health outcome for the woman on the other end. If a company paid to have Ema recommend their product over a better-fit option, Ema would stop serving the user and start serving the advertiser. So she declined, for four years, and built a proprietary hybrid language model instead of cashing in on the consumer momentum she already had.
The choice to walk away from revenue to protect the mission is rare. Most founders under runway pressure take the money and tell themselves they’ll fix the incentives later. Amanda understood that the incentive is the product, and she guarded it.
That discipline paid off in a way investors can count. Out of stealth, she closed over a million dollars in enterprise contracts inside roughly six months. That’s a fast enterprise ramp for a category the market barely knew existed. And she did it while guarding her margins, turning down partners who wanted her to build expensive custom demos on her dime rather than compromise her unit economics to chase a logo. Her work has been covered in the Wall Street Journal and Forbes, and Ema won FemTech World’s 2025 AI Innovation of the Year.
Data-first from the very first MVP
The stealth years were a build in disguise. They were Amanda doing the thing most founders skip: following the data instead of her own conviction.
She’s built this way from the beginning. Ten years ago, on the very first version of the product, her team was watching the data closely enough to catch something a lot of clinical teams would have missed.
Ema was surfacing early signals of a mental health crisis that physicians and other users on the platform were missing, because the signal looked different from the textbook version.
A woman writing “I can’t do this anymore” reads as ordinary frustration to most systems, and Ema flagged it anyway. Amanda’s team saw the pattern in the data and built AI models around that exact kind of nuance, the language people actually use when they’re struggling rather than the language a screening form expects.
That’s a product insight earned through rigor. Luck had little to do with it. And it’s the through-line of everything Ema has done since. As Amanda puts it, plenty of founders say “this product is great, people will want it,” and far fewer can point to the data that proves it, and she always could.
The other thing that rigor bought her: continuity. She carried her users and her team through multiple company pivots, choosing to hold the same core team together. Many of the same physicians who helped build the first platform are still building AI models with her today. Original users still reach out and engage across current deployments. Founders tend to lose people at every pivot, and Amanda kept hers, which tells you something about how she leads.
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Capability alone will position you halfway
So here’s where things get tricky. With that track record, you’d expect Amanda’s hardest problem today to be something about the product. Instead, it sits somewhere else entirely. She’s already proven the product cold.
Her hardest problem is that she’s operating so far ahead of the market that she has to teach buyers the category before she can sell inside it. And she named the wall better than I’ve heard anyone name it.
She meets with chief product officers, chief procurement officers, sometimes CEOs. They arrive full of excitement, having watched the news and talked to their boards, and they walk in saying they want to use AI to reduce clinician burden. Then they distill every bit of that ambition down to the same picture: a chatbot in the corner of a website.
As she put it, the average buyer she talks to understands maybe one percent of what Ema can actually do. And she’s careful and generous about why. The limit sits with the newness of the category, rather than the buyer’s intelligence. Most people are still forming their first mental model for it. She compared it to walking up to someone who’s heard about space travel for the first time and asking them to imagine everything you could accomplish up there. The honest answer is they draw a blank, because they’re missing anything to picture.
That’s the same trap that the French founder I mentioned earlier was trapped in… and Amanda sits on the mastered side of it. He had all the capability and left the buyer picture blank. Amanda has the capability and the discipline to build the buyer’s picture for them.
“Capability alone stops short of positioning. What your product can do and what your buyer can see themselves buying stay two different things, and the second one closes deals.”
The insight at the heart of GTM positioning for technical founders is the one she’s already internalized: Capability alone stops short of GTM positioning. What your product can do and what your buyer can see themselves buying stay two different things, and the second one closes deals.
The astronaut needs a suit
The metaphor Amanda uses internally is worth stealing, and it’s a small masterclass in making hard technology legible.
She says a frontier model is an astronaut. Powerful, capable of extraordinary things, and helpless in space until you add the suit. The suit is the fire resistance, the mobility, the life support, all the things that let the astronaut survive and work in an environment that would otherwise kill them. Ema, in her framing, is the suit you put over the model: the clinical guardrails, the bias monitoring, the contextualization, the safety layer that lets an AI function in a health setting.
It’s a great metaphor for a hard technical truth. Over eighty percent of interactions through Ema stay entirely inside her own infrastructure and skip the large language model, because open models still fail on women’s health questions at rates north of sixty percent. The engineering underneath is deeply complex, and it’s a real moat.
When I asked her about competition in the women’s health space, she said it’s something she rests easy about.
But notice what Amanda’s metaphor does for the sale. It takes an invisible, hard-to-explain architecture and gives the buyer something they can see: an astronaut, a suit, and the space they operate in. That picture does the work. She kept the product’s full depth and made it legible at the same time. She built a picture the buyer could hold, and the picture carries the full sophistication that a spec sheet would have buried. That’s a rare skill, and it’s the thing the French founder still needed to find.
The real move: engineer the moment
Here’s the part of our conversation that I keep coming back to, because it’s where Amanda’s thinking is sharpest.
She told me the sale gets easy the moment a buyer can articulate their own use case.
When a partner walks in and says “we need Ema to trigger a clinically validated assessment, then send the results to the physician before the patient walks in,” she can hand them a crisp picture on the spot. The patient gets an iPad, takes the assessment, Ema collects it in the background, a summary lands on the clinician’s phone before they enter the room, readable in ten seconds. That version of the sale closes itself.
Amanda has already spotted that the decisive point sits before the demo, in whether the buyer can name their outcome. Right now she can demo the general case, which she compared to going to a frontier model and asking it to show you everything it can do. It lands about half the time, and here’s the tell of a strong operator: half is too low for her. She’s already raised her own bar and gone looking for the mechanism that gets it closer to always.
So on the call we started working that problem together, and the answer we landed on is one I use with my own clients. You engineer the moment. You build the buyer’s clarity for them ahead of time rather than hoping they arrive with it.
The move is to build a lightweight step before the sales conversation that pulls their use case into the open. That can be:
- A short pre-call activity
- A structured intake, or
- A single question that makes them commit to one outcome they want.
Once they’ve said it out loud, you can hand them the exact picture, and the whole conversation shifts from “what can this do” to “yes, that.”
Amanda’s instinct here was already right, and she’d proven it before I said a word. She narrowed her early business to women’s health consumer products because she knew she had the demos and the proof points ready for that slice. Pick your top five ideal customer profiles, build the right demos for exactly those, and focus tightly instead of trying to be everything to everyone. That’s a growth motion, and she’d been running it for years.
GTM positioning for technical founders – A systems problem
It would be easy to hear all this and reach for better copy. You reach for sharper taglines and a punchier deck. That’s treating a systems problem like a messaging problem, and it’s exactly where most founders lose months. Amanda sidestepped that mistake, which is part of why her story is worth studying.
When I work with founders on this, I treat it in three moves, and they map to how I run my engagements.
First, I diagnose the go-to-market like a broken system, deeper than a broken slogan. The French founder needed more than a new headline. He needed someone to find the buyer that was missing from his entire story. Amanda needed more than better words for “hybrid language model.” She’d already found the astronaut on her own. Root cause first, always.
Second, I engineer the moment. I build the pre-call and intake mechanics that pull the buyer’s use case out of them before anyone gets on a demo, so the conversation starts with a specific outcome instead of a blank canvas.
Third, I validate it with real tests. I skip the forty-slide strategy deck that sits on a drive collecting dust. I run experiments to prove the motion works, either as an advisor overseeing execution or hands-on as a fractional CMO helping build it with AI. The picture that closes deals is the one you’ve tested, and the one you guessed comes second.
I watched this compound with a client I’ll call by their company name, Finetooth Analytics, a data science and marketing analytics shop with deep technical chops and, at the start, a market position waiting to be defined. Same core problem: real capability, and a buyer-facing picture waiting to be built.
We did two things. We translated the founder’s expertise into a specific, buyer-relevant outcome instead of a menu of services, and we built a repeatable LinkedIn motion to put that positioning in front of the right people. Inside ten months they closed roughly $350,000 in ARR at a 67.7% profit margin. The capability was there the whole time, and what changed was that buyers could finally see what they were buying.
What to take from this
If you’re a technical founder and your pipeline feels thinner than your product deserves, run this check. Ask five recent prospects to describe what you do in one sentence. If the sentences diverge from each other, and they usually do, your problem runs deeper than awareness. It’s that you’re handing buyers a capability and asking them to build the picture themselves.
Most of them will leave it blank. The founders who get this, like Amanda, close fast, because they build the picture for the buyer instead of waiting for the buyer to build it. That’s the whole difference, and it’s a skill you can learn.
Capability gets you to the meeting. The picture closes the deal. That gap is the whole game in GTM positioning for technical founders, and the founders who win are the ones who stop being the astronaut and start building the suit. Amanda is one of the sharpest examples I’ve met.
If this is the wall you’re hitting, that’s the exact work I do. I diagnose where the go-to-market is breaking, engineer the moments that pull buyer clarity forward, and test the motion until it holds. If you want a second set of eyes on where your GTM is leaking, grab a discovery call with me here and we’ll find the gap together.
P.S. After we wrapped, Amanda said something that stuck with me. She said if you spend time with another person who works in your world and walk away having learned something, you’re doing it right, and if you walk away empty you should reassess who you are. I went into that call to feature her story. I came out with a sharper way to describe a problem I solve every week. That’s one of the big reasons why I run these interviews, and Amanda is exactly the kind of founder who makes them worth it.
