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“After 600+ founder conversations, 90% are building the wrong thing”

After 600+ founder conversations, 90% are making the same mistake.

And I was doing the same.

A lot of people think their situation is unique.

But in reality - most of the mistakes repeat.

Out of ~30–40 founders I spoke to more deeply, around 8–9 out of 10 were struggling with the same thing:

Building… without really understanding what matters
(I saw this over and over again while talking to founders about contracts, risk, and real decisions they had to make)

One pattern stood out:

A lot of founders skip real validation.

They copy what seems to work for others,
jump into building based on чужой опыт,
or define their market and competitors without really understanding the context.

As a result - wrong assumptions, wrong priorities, wrong product direction.

Here’s what kept repeating:

Building features before validating the problem
Listening to random feedback instead of patterns
Waiting for a “perfect launch” instead of testing early
Overcomplicating instead of making one thing clear

It’s not a lack of effort.

It’s a lack of focus.

One example - when I first launched on Product Hunt, it was just a single landing page.

No full product. Just testing if anyone cared.

That, combined with ~6 years building startups, going through accelerators, and speaking with founders across different stages, made one thing clear:

You don’t need more features - you need clarity on what actually matters.

Still learning, but this shift changed how I approach building completely.

Curious - what was the biggest mistake or shift in your journey?

For those curious what I’m working on:
https://joyful-granita-8415bc.netlify.app/index.html

Founders and business owners - curious to hear your take.
What was the biggest mistake or shift in your journey?

on March 27, 2026
  1. 1

    The "patterns vs. random feedback" point is underrated.
    Used to assume that each and every feature request is a data point. Took me embarrassingly long to realize the only real data is in the questions people are asking. Not the questions they're asking in terms of "feature," but where they're getting stuck. Same three questions over and over again. Different people asking them. That's a pattern. "Add calendar sync" is not.
    What's your go-to for recognizing patterns early? Especially before product when there's not a whole lot of data yet?

    1. 1

      Yeah, that’s a good question.

      Early on it’s less about volume and more about repetition - even 2–3 people describing the same problem in a similar way is already a strong signal.

      Not the feature they ask for, but the situation they’re in.

      That’s usually where the pattern starts.

      Curious - what’s something you thought was a pattern early on, but turned out to be just noise?

      1. 1

        One of the users requested integration with some third-party software, that would be very time-consuming to build, it might make sense later though, but since there's just one request I prefer just to keep in a backlog for now.

        1. 1

          Yeah, that makes sense.

          Single requests like that can be dangerous - especially when they’re expensive to build.

          Feels like the right move to keep it in the backlog until you see the same need coming up again.

          Curious - have you ever built something like that early and later realized it wasn’t worth it?

  2. 2

    Appreciate everyone sharing their experiences here - a lot of patterns are repeating.

    Curious to hear more:
    what was the biggest mistake or shift that actually changed how you build?

    1. 1

      Good question.

      For me, the biggest mistake was not understanding the market before starting. I had an electronics business, didn’t study demand in my city properly, and had to shut it down after 4 months.

      The shift was focusing on customers first - now I try to understand demand before putting in time and money.

      After that, I started a smaller business, and with that experience, things became much more stable.

      Learned it the hard way - if I had seen a post like this earlier, it would’ve helped a lot.

      1. 1

        Yeah, that’s a great example of it.

        It’s interesting how often it’s not about execution, but starting with the wrong assumption about demand.

        Curious - what would you do differently now before starting something new?

        1. 1

          Now I’d definitely start by researching the market and demand - talking to potential customers and seeing what’s really missing before investing. Experience taught me to focus on the customer first, not just the product.

          1. 1

            Yeah, that makes sense - starting with demand changes everything.

  3. 1

    "Listening to random feedback instead of patterns" is the one that gets me. Early on we'd get one user asking for Unity support and immediately start scoping it out. Took us months to realize 80% of our actual paying users were on Godot and just wanted the existing thing to work better. The pattern was right there in the data the whole time, we just kept chasing the loudest voice instead.

    1. 1

      Yeah, that happens a lot.

      It’s crazy how one loud request can pull you in the wrong direction, even when the real pattern is right there.

      Easy to miss in the moment.

  4. 1

    The pattern I keep seeing: founders validate against their own assumptions, but ignore the validation already baked into the market.

    Competitors have been learning for years about who pays, for what, and at what price. That signal is hiding in plain sight — pricing pages show who they're actually targeting, G2 reviews surface the exact jobs customers are hiring the product to do, job listings reveal strategic bets before press releases do, changelog announcements tell you which features got traction.

    The irony: founders will spend weeks on customer interviews but skip a two-hour competitor intelligence pass that would give them ground truth from thousands of paying customers instead of a handful of conversations.

    This doesn't replace talking to customers. It filters which customers to talk to and which questions matter. The founders who get this right treat competitor data as a first draft of market knowledge — then customer interviews as refinement. The ones who get stuck tend to skip step one entirely.

    1. 1

      Yeah, I get what you’re saying.

      But I think a lot of founders already look at competitors, pricing pages, reviews - and still miss the point.

      The problem is not lack of information, it’s not understanding what actually matters for the decision.

  5. 1

    I'm a solo dev and I've been struggling with localization costs for my micro-SaaS. Tools like Lokalise are just too expensive for small projects.

    I'm thinking of building a very simple, pay-as-you-go API that translates JSON while keeping the UI context (character limits, etc.). It wouldn't have a dashboard, just a clean endpoint.

    Would you actually use something like this if it cost around 1 buck per translation? Or am I overthinking this? Just looking for some honest feedback before I write more code.

    1. 1

      I’d probably try to validate it first.

      Feels like something that could work, but depends a lot on who actually needs it and how often.

      Have you talked to anyone who’s already dealing with this problem regularly?

  6. 1

    This resonates. I've been building an AI tool for Canadian government questions and the biggest shift for me was realizing that the problem validation was already there. People were already searching for these answers and getting lost in hundreds of government pages. I didn't need to invent demand, I just needed to make the existing pain go away. The mistake I almost made was overbuilding before putting it in front of real users.

    1. 1

      Yeah, that’s a good point - sometimes the demand is already there, just buried under a bad experience.

      Feels like the mistake is trying to invent something instead of fixing what already hurts.

      Sometimes you get it right early - but that’s pretty rare.

  7. 1

    Living this right now. Built a fully functional AI receptionist (multi-tenant, Stripe, Twilio, onboarding form, dashboard) before getting a single paying customer. Zero validation.

    The product works. But I skipped the hard part — proving anyone actually wants to pay £39/mo for it. Now I'm 30+ days in, £0 revenue, learning that 'build it and they will come' is fiction.

    Your line about 'clarity on what actually matters' hits hard. I thought the tech mattered. Turns out the conversation with the customer matters way more.

    1. 1

      Yeah, that’s real.

      It’s crazy how easy it is to build something that works but nobody actually needs.

      That shift to talking to users first is harder than it sounds.

  8. 1

    90% 가 아니라 99%일걸?

    1. 1

      맞아요, 거의 99%인 것 같아요 😄

  9. 1

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    Eligible AI businesses can access up to $200K in GCP credits (24 months)
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    1. 1

      Oh nice, didn’t know about this - will check it out, thanks.

  10. 1

    I’ve been thinking about this a lot recently.

    I started building something from a problem I was personally experiencing (in my case, around worldbuilding tools).

    So in a way, it didn’t feel like “guessing” — it felt real.

    But reading this made me realize something:

    That’s still internal validation.

    I’ve had positive feedback from a few people who saw what I was working on, but I’m not sure yet how strong the demand actually is.

    Right now I’m trying to shift from:
    “this makes sense to me”
    to
    “how many people actually need this, and how urgently?”

    Curious — how do you personally distinguish between real validation and just “positive feedback”?

    1. 1

      Get up to $200K in GCP credits (24 months)

      Eligible AI businesses can access up to $200K in GCP credits (24 months)
      *Note : only for AI teams who are focused to build profitable scalable businesses models from day 1

      https://www.linkedin.com/posts/sai-rithvik-2176302b1_eligible-ai-companies-can-access-up-to200k-activity-7442865181254209536-EiDB

    2. 1

      Yeah, that’s a good realization.

      I think the difference shows up in what people do, not what they say.

      A lot of people will say “this is cool” - but real validation is when they actually try to use it, come back, or bring their own problem.

      Have you had anyone actually try to use it in a real situation yet?

  11. 1

    which database does the project use?

    1. 1

      Still experimenting with different setups - keeping things flexible for now.

  12. 1

    This applies to business in general, not just startups.

    I had an electronics business before - didn’t really study my local market or demand properly.
    Opened, but there just weren’t enough customers, and I had to shut it down after 4 months.

    Biggest lesson for me was understanding the market first, before building anything.

    1. 1

      Yeah, makes sense - understanding demand upfront probably saves a lot of time and pain.

      How would you test that today before launching something

      1. 1

        Today, I’d start by talking to potential customers directly - surveys, interviews, even small test offers - to see if there’s real interest. I’d also check competitors and see what’s missing in the market before investing time or money.

        1. 1

          Agreed - talking to real customers early is key.

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