AI coding assistants promise speed, but do they deliver? Explore data, developer insights, and security risks showing why AI feels faster bu
The claim that AI makes developers 10x more productive gets repeated pretty often. But the math does not hold up. A 10x boost means what used to take three months now takes a week and a half. Anyone who has actually shipped complex software knows that it is impossible. The bottlenecks are not typing speed. They are design reviews, PR queues, test failures, context switching, and waiting on deployments. [...] Even when AI enables parallelism, one more research shows the cost is more juggling, more reviews, not less time to ship. In July 2025, Faros AI analyzed telemetry from over 10,000 developers across 1,255 teams. They found that teams with high AI adoption interacted with 9% more tasks and 47% more pull requests per day. Developers were juggling more parallel workstreams because AI could scaffold multiple tasks at once. Historically, context switching is a negative indicator, correlated with cognitive overload and reduced focus. Faros points out that developers spend more time orchestrating and validating AI contributions across streams. That extra juggling cancels out much of the speed-up you get in typing. [...] Not all findings are negative. In 2024, researchers from MIT, Harvard, and Microsoft ran large-scale field experiments across three companies: Microsoft, Accenture, and a Fortune 100 firm. The sample covered 4,867 professional developers working on production code. With access to AI coding tools, developers completed 26.08% more tasks on average compared to the control group. Junior and newer hires adopted the tools more readily and showed the largest productivity boost: ⹠Senior developers, especially those already familiar with the codebase and stack, saw little or no measurable speed-up. ⹠The boost was strongest in situations where devs lacked prior context and used the AI to scaffold, fill in boilerplate, or cut down on docs lookups.
