Watch Desk posted an update
An engineer says AI helped him complete 295 pull requests across 49 repositories and ship 30 project releases in ten days, using about 1.2 billion AI tokens.
Why it mattersThe work included spelling-linting tools and updates across several software projects. The engineer argues that decades of programming experience were still needed to guide AI through complex maintenance and feature work. That is a striking personal account, not a controlled productivity benchmark. But it puts a useful question on the table: when AI multiplies output, does experience become more valuable, not less?
Discuss: In AI-assisted software work, should teams reward the volume of changes shipped or the experience needed to judge which changes are worth making?
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