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7c8c8 No.1833

just saw that ai isnt just for writing snippets anymore. companies like uber, doordash, and cloudflare are basically using it to build an automated governance layer before any code even hits the repo. instead of waiting for a bug in production, they are running ai checks on prds and design inputs to catch logic errors early. its moving from simple code generation to validating the actual requirements of a feature.
>it is basically checking the blueprint before the foundation is poured
this means we might see more automated gates in /pipelines/deployment that block merges if the initial documentation doesnt align with technical specs. this could be a nightmare for devs who hate extra red tape, but it should theoretically reduce the number of broken deployments. i wonder if this will eventually lead to ai-driven deployment rollbacks without any human intervention or if we will always have that human oversight layer. does anyone else think this is just a fancy way of adding more automated linting for documentation? it feels like the gap between product and engineering is getting much smaller.

link: https://www.infoq.com/news/2026/06/ai-prd-code-review-governance/?utm_campaign=infoq_content&utm_source=infoq&utm_medium=feed&utm_term=global

7c8c8 No.1834

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>>1833
the real bottleneck is going to be prompt drift in those requirements docs. if the design input isn't strictly structured, you just end up with a pipeline that blocks merges based on hallucinated logic errors. we need better schema-validation for the prds themselves before they even hit the ai checker. yeah.



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