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0 to 14 Products in 6 Months: The Live Post-Mortem Before We Know How It Ends

Six months in. Fourteen products. Zero unicorns. Here's the live post-mortem before we know how it ends.

I run Inithouse, a one-person venture studio where I build and launch products fast. Not "move fast and break things" fast. More like "ship something every two weeks, see what sticks, learn from what doesn't" fast.

The thesis was simple: instead of betting everything on one idea, build a portfolio of small products. Each one is an MVP targeting a different market. Treat the whole thing like a portfolio of experiments. Some will work. Most won't. The data will tell you where to double down.

Here's what six months of doing that actually looks like.

What worked better than expected

Gift and fun products have real pull. I built Magical Song (AI-generated personalized songs) and Ziva Fotka (static photos turned into short AI animations). Both are gift products. People buy them for birthdays, weddings, anniversaries. The conversion psychology is completely different from utility tools. When someone needs a last-minute gift, they don't comparison-shop for three weeks. They find it, they buy it, done.

Multi-domain, multi-language SEO is underrated. Ziva Fotka runs on five domains across five languages (Czech, Slovak, Polish, English, German) from a single codebase. Each domain targets a different regional market. It's not a hack. It's just recognizing that "animate my photo" is a universal need, and the competition in smaller European languages is almost nonexistent.

Card games travel well digitally. I built three card game products: Here We Ask (deep conversation starters), Party Challenges (action-based party games), and Scary Challenges (horror-themed). They're free to play, no signup required. The interesting part is how they segment naturally. Different audiences, different vibes, same underlying engine. Virtually no marginal cost per user.

What didn't work (yet)

Broad utility tools are a grind. VoiceTables is a voice-first data workspace. Speak what you need, get a structured table. It's genuinely useful. But "useful" isn't enough. The market for productivity tools is so crowded that being good barely registers. You're competing with everyone's existing workflow, and switching costs are invisible but real.

Generic AI wrappers have no moat. Early on I was tempted to build things that were basically "ChatGPT but for X." Every time I went down that path, I hit the same wall: the moment OpenAI or Anthropic ships a minor update, your entire value proposition shifts under your feet. The products that survived in my portfolio are the ones where AI is the engine, not the product.

The surprises

Niche beats broad, every single time. Be Recommended checks whether AI chatbots recommend your brand. Super niche. But marketers who care about AI visibility care a LOT. Audit Vibecoding audits vibecoded projects for security and quality issues. Again, tiny market. But the people in that market have an urgent, specific problem.

Distribution matters more than product quality. This one hurts to write. I've built products that I think are genuinely well-made, and they sit there with minimal traffic. Then I've built simpler things that happen to target keywords with low competition, and they grow organically. After six months, I'm fully convinced: distribution first, product second.

The portfolio approach creates its own momentum. When you have a dozen live products, you start seeing patterns across all of them. What messaging works. What pricing triggers conversion. Which channels drive traffic for which product types. Each product is a data point, and the dataset gets more valuable as it grows.

Open questions (the honest part)

I still don't have confident answers to these:

Pricing. Most of my products are one-time purchase or free. Is that right? Subscriptions are the indie hacker dream, but my best-converting products are impulse buys. Maybe the answer is different pricing models for different product types.

Focus vs. breadth. The portfolio approach gives you optionality, but it also means no single product gets my full attention. If one product shows strong traction, do I go all-in? Or do I keep the portfolio alive because the cross-learning is worth it?

When to kill a product. I haven't killed any yet. That's probably a mistake. Some of these products are clearly not going anywhere, and the honest move would be to sunset them and redirect traffic. But "not going anywhere yet" and "not going anywhere ever" are hard to tell apart at six months.

What I'd do differently

I'd start with distribution channels, not product ideas. Find where the audience already is, what they're already searching for, then build the thing that answers that search. I did this accidentally with some products (multi-language SEO) and intentionally missed it with others.

I'd also spend less time on polish and more time on getting the first ten users. Several of my products launched looking great and then sat in silence because I hadn't built any distribution before launch day.

What's next

The plan for the next six months is pretty clear: double down on what's working (gift products, niche tools, multi-language SEO), kill or merge what isn't, and build distribution systems that work across the portfolio instead of one product at a time.

I'm also publishing everything I learn along the way at Inithouse. Not because I have the answers. Because writing about it in public forces me to think clearly about what's actually happening vs. what I wish was happening.

If you're building a portfolio of products, or thinking about it, I'd love to hear how you're approaching the same questions. Especially the "when to kill" one. That's the one keeping me up at night.

Jakub, builder @ Inithouse

posted to Icon for group Growth
Growth
on May 9, 2026
  1. 1

    Really strong and honest breakdown — especially the fact that this is a live post-mortem rather than a hindsight narrative.

    There’s a clear shift happening here: from “idea → product” to “portfolio of experiments → allocation of attention.” And that’s usually where things get harder, not easier.

    The real constraint in a portfolio model isn’t ideas or execution speed — it’s attention. At some point, the portfolio stops being a learning system and starts competing for the same scarce resource: the founder’s focus.

    A few reflections that might help structure the next phase of decisions:

    — On “when to kill a product”: instead of asking whether it’s growing, it might be more useful to ask whether it still generates new strategic insights for the portfolio, or just consumes attention. If it’s the latter, it’s effectively dead as an asset, even if it’s still “alive” in metrics.

    — On distribution vs product: you’re already circling a key truth — distribution fit comes before product fit. In a portfolio setup, you’re almost building distribution hypotheses first, and products are just instruments to test them.

    — On focus vs breadth: the next evolution might not be “pick one winner,” but define 1–2 anchor products that justify deeper focus, while explicitly treating the rest as a constrained R&D layer with capped attention and investment.

    Your point about polish not correlating with traction is especially on point — that’s one of the most expensive lessons in building.

    Curious to see what patterns emerge for you after another cycle — not just which products survive, but which types of bets consistently compound

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