A client's dashboard took 11 seconds to render. Everyone blamed the database. The real problem was an ORM doing exactly what we told it to — we just never looked at what that meant.
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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 20-person team was running 14 microservices with three full-time engineers just keeping the infrastructure alive. We consolidated six of them into a modular monolith and cut their deploy time by 70%.
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- A client's team was drowning in a 200K-line TypeScript monolith. When we finally measured what was actually running in production, we found that almost a third of it was dead code nobody had touched in over a year.
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- We ran load tests before a big product launch, got green across the board, and watched the system buckle under real traffic two days later. The tests weren't wrong — they just weren't testing reality.
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- A client's on-call rotation was burning people out — not because of real incidents, but because of noise. Here's how we cut alerts by 87% without missing anything that actually required a human.
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