As coding gets cheaper, topic selection becomes the bottleneck

Spend more effort on who needs the workflow and how it is evaluated.

Useful for: Indie developers, AI tool builders, engineering teams, automation teams, and agent workflow designers

GitHub Changelog visual for: As coding gets cheaper, topic selection becomes the bottleneck
Image source: GitHub Changelog.

Separate reader traffic

AI coding tools can compress implementation time, which makes demand selection and validation more important.

Requests are not readers

The useful question is not whether traffic looks busy; it is which activity represents readers, monitoring, crawlers, retries, or system errors.

Check the logs first

  • Spend more effort on who needs the workflow and how it is evaluated
  • Keep the test narrow: one low-risk task or tool entry before connecting permissions, logs, failure handling, and human takeover to production

What still needs proof

Treat this as a primary signal, then still check pricing, limits, and real adoption before acting. Keep the original source open so the announcement, the evidence, and this site's interpretation stay separate.

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