An impressive number
Per a JetBrains survey from January 2026, 74 percent of developers worldwide use specialized AI coding tools. The market reached $12.8 billion, with three vendors crossing the $1 billion annual revenue mark. Claude Code grew the fastest: from roughly 3 percent professional usage in spring 2025 to 18 percent globally by January 2026 – with the highest satisfaction scores of any tool measured.
Looking behind the number: the METR study
An independent, randomized controlled trial by METR paints a considerably more complex picture. 16 experienced open-source developers completed 246 real tasks in codebases averaging around one million lines of code – with and without AI coding tools. Result: with AI tools, they took 19 percent longer on the same tasks. At the same time, those same developers believed they had been 20 percent faster with the tools.
Why faster doesn't feel like faster
The study identifies a concrete cause: small context windows force constant manual re-wording and re-prompting, which creates repeated context switches. These switches interrupt the flow state in which experienced developers are normally most productive on complex work – and this loss stays subjectively unnoticed, because the fast first code result per request feels like progress.
Practice section: not a blanket verdict against AI coding tools
This study isn't proof that AI coding tools generally don't help – its result applies specifically to experienced developers doing complex work in large, grown codebases. Whether that transfers to your team depends heavily on context: experience level, size and structure of the codebase, type of task. Instead of blindly trusting industry promises or any single study, it's worth running your own simple measurement with your team – more on that in a later module of this course on realistic tool selection.