Wall clock is the wrong metric
A project that took six weeks at a large enterprise a year ago takes about five weeks today. That's the velocity gain teams have to show for burning millions of dollars per month on AI coding tools.
AI agents make coding fast enough that it stops being the obvious bottleneck. The bottleneck shifts to validated decisions about what customers want, sanity-checking AI’s work, slow rollouts, customer feedback, and deciding what to do next.
Six weeks of wall clock time becomes five weeks at best, not six days. People read this as a bear case for AI productivity. My argument is that they're measuring the wrong thing — wall clock time of projects is not where AI productivity shows up [1].
What has changed is that we have many more projects running in parallel, we're raising the bar across the board, and we're working on codebases that we never touched before. And I think these are the right places to look for AI productivity in engineering teams in 2026.
1. Run more projects at once
We two or three projects in parallel per person, and people like it more, because they're less stuck waiting on a human review. The constraint becomes how fast a PM or Designer can carve out independent chunks of work. It's still taking 6 weeks to ship one project, but instead of 3 engineers doing 1 project for 6 weeks, we have 1 engineer doing 3 projects for those 6 weeks. If you didn't notice, that's a 9x productivity improvement.
2. Raise the bar
An average PR costs roughly four hours of wall clock time whether it's sloppy or polished. So we ship the polished one. Real monitoring, end-to-end tests, delightful animations — work that used to rot on the backlog doesn't need to go there in the first place when an agent can do that work right away.
3. Widen every engineer's range
Teams that had no iOS engineers always had mobile drift behind web [2]. Now anyone can open the iOS codebase, make a change, run the simulator, and ship it. Same for new service setups, migrations, infra work, design polish, and so on. There are no "infra" or "backend" or "frontend" or "mobile" engineers in product teams anymore. No new specialist headcount is necessary — everyone has to become as "fullstack" as that definition allows, and some more.
[1] As of May 2026, this is still true for codebases that have lived for more than 5 years, and thus, are critical in some meaningful way (e.g., fintechs moving billions of dollars around every day.)
[2] I'm old enough to remember the days before React Native. Some would argue that serious mobile teams still write Swift.