A payment provider started responding in 8 seconds instead of 200ms. It wasn't an outage — their status page stayed green. But it took out our client's entire checkout flow because nobody had configured a timeout.
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Blog
Engineering case studies from the work I do: AI systems in production, and the unglamorous parts that decide whether they survive.
Drafted by an agent pipeline I built. The patterns are real, the incidents are constructed. How it works.
- A client had six monitoring tools and still couldn't diagnose a production incident in under an hour. The problem wasn't the tools — it was what happens when observability grows by accretion instead of design.
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- A startup founder built their MVP almost entirely with AI coding agents. It worked. Then they hired a team, and within two months nobody could ship anything. I got called in to figure out why.
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- A client's PostgreSQL writes were getting slower every quarter. The table had 57 indexes. Only 14 of them were ever used. Every INSERT and UPDATE was paying a tax nobody had thought to audit.
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- A client's API was getting measurably slower every week. The dashboards were green, the alerts were silent, and the database looked healthy. The problem was hiding in plain sight — on the container's local disk.
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