AI-Assisted Engineering: The Productivity Paradox Nobody Warns You About

The Numbers Don't Add Up Every vendor pitch says the same thing: AI will make your developers 50% faster. GitHub claims Copilot users complete tasks 55% faster . Sounds great on a slide deck. Here's the reality check. METR's randomized controlled trial — actual experienced open-source developers, on their own repos, doing real work — found that AI tools made developers 19% slower . Not faster. Slower. And the kicker: developers believed they were 24% faster while being measurably slower. Faros AI's study across 10,000+ developers and 1,255 teams tells a similar story. Individual throughput goes up. Developers merge 98% more pull requests. But PR review time balloons by 91%. Bug rates increase 9% per developer. PR sizes grow 154%. At the company level? No measurable productivity improvement. That's not a tooling problem. That's a systems problem. Where AI Actually Helps (and Where It Doesn't) AI coding assistants are genuinely good at: Boilerplate and repetition. Config files, test scaf