The Magpie Problem: What Happens When You Can Build Anything?
I’ll admit it. I’m a magpie when it comes to startup ideas.
I’ll admit it. I’m a magpie when it comes to startup ideas. Always have been. I see opportunity everywhere, and focusing on just one thing has never come naturally. For a long time, I thought that was a weakness. The startup playbook certainly says it is: pick one idea, go deep, build something big enough to justify VC investment. It’s a model built on the scarcity of time, capital, and development capacity.
But what happens when those constraints start to disappear?
The collapse of development effort has compounded my magpie tendencies in ways I didn’t expect. Ideas can be built out on a whim now. And that’s both powerful and dangerous. The more AI can do, the more we ask it to do. Instead of building one thing faster, there’s a real risk of building many things slower.
“The more AI can do, the more we ask it to do. Instead of building one thing faster, there’s a real risk of building many things slower.”
And yet… I can’t shake the feeling that the old rules don’t fully apply anymore. There’s something on the other side of this tension worth exploring.
The old math doesn’t work the way it used to
The traditional startup model was designed around bottlenecks. Engineering talent was expensive. Building anything took months. Testing an idea meant raising money, hiring a team, and praying your market research was right.
So naturally, you concentrated everything on one bet. You had to.
But those bottlenecks are eroding…fast. What used to take a team of five engineers three months, a solo founder can now prototype in a weekend. Not a crappy prototype either. Something real enough to put in front of users and learn from. The cost of being wrong has dropped dramatically. And when being wrong is cheap, you don’t need to bet everything on being right once.
“The cost of being wrong has dropped dramatically. And when being wrong is cheap, you don’t need to bet everything on being right once.”
What if founders thought more like Venture Studios?
Venture Studios don’t put all their effort into one company. They build portfolios. They spread risk across multiple bets because they know most won’t work out, but the ones that do will more than make up for it.
Why aren’t more founders thinking this way?
Instead of going all-in on a single product and spending two years discovering the market doesn’t care, what if you built three or four things in parallel? Each one targets a different audience, solves a different problem, and runs as its own experiment. Some would fail. That’s the point. But you’d learn faster, diversify your risk, and probably stumble into something with real traction sooner than you would grinding on one idea.
Essentially, every founder can now operate like a venture studio. Not a lifestyle business portfolio. A studio. Launching multiple bets, watching the signals, then doubling down on whatever wins.
This isn’t about being unfocused. It’s about being strategically diversified.
And what if you focused that portfolio a little? Not randomly, but symbiotically. Every good VC has a thesis. A sector they understand deeply, a category of startup they back again and again. The best ones don’t just pick winners in isolation. They build ecosystems in which their portfolio companies reinforce one another.
Founders can do the same thing. Build products in related industries that share foundational data, overlap in users, or have complementary workflows. Each product you ship deepens your understanding of the space, and the data you collect in one feeds insights into the next. It’s a compounding effect. not just financially, but in terms of knowledge and positioning. You stop being a random builder and start becoming the person who just gets that corner of the market.
The economics of small are changing
There’s a number that used to kill a lot of good ideas: the minimum viable revenue needed to sustain a product. If your addressable market was 500 people, conventional wisdom said don’t bother. The cost of building and maintaining something for that audience just didn’t pencil out.
That calculation is different now. When your development costs approach zero, and your maintenance burden is minimal, it suddenly makes sense. Not as venture-scale businesses, by themselves, but as real, sustainable income streams that compound when you stack a few of them together.
Where it gets interesting… some of these products don’t even need to be permanent. The concept of disposable software, apps built for a specific context, used for a while, then retired, starts to make sense when creation costs are this low. You’re not maintaining a legacy codebase. You’re spinning up solutions as needed and letting them go when they’ve served their purpose.
That’s a very different relationship with the things you build and the value they hold.
The transaction itself might be changing, too. In a world where software is assembled from LLM-powered Lego bricks, pay-per-use starts to make more sense than subscription. Terrible from a VC perspective. ARR is king, and usage-based revenue is messy to model. But in the portfolio world, usage is your signal. It’s the thing you optimise around, the clearest indicator of which products deserve more attention, and just as importantly, which ones it’s time to retire.
Two caveats, though.
The first is operational gravity. It’s easy to get seduced by how much the building part has collapsed and forget that the building is only one piece of running a business. Sales, marketing, operations, support, access to a market. None of those has compressed at the same rate. Not yet anyway. Every product in your portfolio still needs users to find it, customers to help, and someone keeping the lights on. That overhead is real, and it multiplies with every product you add. The development cost might trend toward zero, but the human cost of actually running things hasn’t followed… at least not so far. AI is chipping away at these, too. Automating support, generating marketing copy, streamlining ops. But we’re nowhere near the same collapse we’ve seen in development. The gap between “I can build this in a weekend” and “I can run this in my sleep” is still wide. And that gap is where portfolio founders get buried if they’re not careful.
The second is knowing when to stop being a studio. The whole point of launching multiple bets is to find out what works. But at some point, something will work. And when it does, you need to recognise the signal and go all in. The venture studio model isn’t about staying diversified forever. It’s about earning the right to concentrate. You launch wide, watch the data, and when one product starts pulling away from the others, you pour everything into it. That’s the exit from the studio. Not selling the portfolio, but graduating a winner out of it.
This isn’t for everyone, and the old model may still prove true
I’m not arguing that the traditional model is dead. If you already know what to build and have the conviction to see it through, go all-in. Seriously.
But for those of us who don’t know yet, who are technical, comfortable with ambiguity, a bit of a magpie, the venture studio approach might be the fastest way to find out. Not because it’s trendy, but because the economics now let you run the experiment. Launch a few things. Watch what the market actually responds to. Then bet big on the winner.
The tools caught up to the idea. Every founder can be a venture studio now. The question is whether you’ve got the discipline to know when to stop exploring and start exploiting.