Building software got cheap. Knowing what to build didn't — the 2026 data
The cost of building software collapsed — 41% of all code was AI-generated in 2025 — while the cost of knowing what to build didn't move. The data behind the shift.
Building software got cheap. Knowing what to build didn't — the 2026 data
The cost of building software collapsed. The cost of knowing what to build didn't move. Here's the data behind the shift — and why almost nothing in the tooling stack was rebuilt for the expensive half.
Building got cheap — fast
- 41% of all code written in 2025 was AI-generated.
- 84–93% of developers use or plan to use AI coding tools, up from 76% a year earlier (DORA 2025, JetBrains AI Pulse).
- In a controlled study of 4,800 developers, GitHub Copilot users finished coding tasks 55% faster (1h11m vs 2h41m).
Cursor, Claude Code, Bolt, Lovable, v0 — the time to turn an idea into working software dropped by an order of magnitude in about two years. If your bottleneck was ever "can we build it," it mostly isn't anymore.
But most of what gets built is never used
- 80% of software features are rarely or never used. Just 12% of features drive 80% of usage (Pendo, aggregated across finance, HR, education, logistics, healthcare, e-commerce).
- Public cloud-software companies invested up to $29.5 billion building features that are rarely or never touched (Pendo).
- ~43% of startups fail from poor product-market fit / no market need — the #1 or #2 root cause across a decade of post-mortems (CB Insights).
Cheaper building doesn't fix this. It amplifies it. When shipping is the constraint, a wrong bet costs weeks. When shipping is free, you can build the wrong thing faster than ever.
And the people who should catch it can't
- Product managers spend only about 27% of their time on strategy — ~73% goes to tactics and execution (Pragmatic Institute).
- Roughly 52% of a PM's time goes to unplanned "firefighting."
Keep reading
Most "AI Features" Shouldn't Be AI Features. Here's the Test That Tells You.
Most "AI features" shipped in 2026 are rules engines wearing an AI costume. Here's the four-question test to run before you spec one — and what it looks like when a feature fails all four.
The Product Velocity Illusion: Why Shipping Faster Hasn't Made Your Roadmap Better
AI collapsed the time it takes to build a feature, but not the time it takes to decide what to build or validate that it worked. The Three Clocks framework shows product teams where their real bottleneck moved — and how to stop mistaking build speed for progress.
Your Next User Might Not Be Human: A PM's Framework for Agent-Ready Products
Software is quietly picking up a second audience — AI agents acting on a human's behalf. Here's a framework for auditing whether your product actually works for both.