A Node.js service kept getting OOMKilled, but only on Tuesdays. The batch job was a red herring. The real problem was a lazy cache eviction strategy that nobody thought to question.
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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's deployment kept failing in staging but not locally. The root cause wasn't code — it was sixty-seven environment variables spread across five files with no documentation and no single source of truth.
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- We practiced deployments religiously but never tested a rollback. When a release broke checkout and we hit the big red button, we found out half the system couldn't actually go backward.
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- A client's platform had 23 AI agents built by a team of 8. Nobody could tell me what half of them did. Agent sprawl is the new microservices sprawl, and the cleanup looks depressingly similar.
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- A client's codebase had try-catch blocks wrapped around everything. Nothing ever crashed. Nothing ever worked correctly either. The error handling strategy was actually an error hiding strategy.
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