The vitamin trap: AI makes weak ideas cheaper to build
AI lowered the cost of building, which means more products get built that nobody needed. A note on painkillers, vitamins, and why demand is the only test that matters.
AI has made it dramatically cheaper and faster to build a working product. That's mostly good. The side effect nobody mentions: it's now cheap to build things nobody needed. When the cost of building drops, the discipline of deciding whether to build has to rise to compensate — and usually it doesn't.
Painkillers and vitamins
A painkiller solves a problem people are already paying to work around — in money, time, or frustration. A vitamin is nice to have; people nod at it and never change their behaviour. The trouble is that vitamins demo just as well as painkillers. In a slick prototype they look identical. The difference only shows up later, in whether anyone comes back.
Why AI worsens the trap
Because AI makes the vitamin cheap enough to actually ship. Previously, a marginal idea died in the cost of building it; the effort was its own filter. Now the prototype exists in a weekend, the founder falls for the demo, and the "is this a painkiller?" question gets skipped entirely. The market is filling with competent products solving problems that weren't sharp enough to matter.
The only test that survives
Enthusiasm is free — people are happy to tell you an idea is cool. Commitment is the signal: will someone give you something scarce (their time, their email, a deposit) for the promise of the outcome? If the honest answer to "what do they use today" is nothing, because it's not that big a deal, you're holding a vitamin, and no amount of AI polish converts it into a painkiller.
The discipline that compensates
The cheaper building gets, the more valuable it becomes to test demand before building — the fifteen conversations, the landing page, the concierge version done by hand. That work used to feel optional because building was the hard part. Now building is easy and judgment is the constraint. That's the whole reason we push validation up front.
More in validating an AI idea and testing your riskiest assumption.
Want an honest read on whether the demand is real? The free Market Need Analyzer and Riskiest-Assumption Finder are a good place to start.
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