Practical writing on applied AI, platform engineering, cloud and the operating discipline behind systems that ship. Lessons from production — not pitch decks.
The gap between an impressive agent demo and a system you can run for real customers is mostly engineering. Here's the architecture we keep coming back to — retrieval, evaluation, and human-in-the-loop controls wired into one auditable loop.
Self-service only works when the paved road is faster than going around it. How we design templates teams adopt by choice.
FinOps done badly turns into a tax on shipping. A practical loop for instrumenting, attributing and trimming spend.
A wall of green graphs doesn't mean your users are happy. Designing service-level objectives that drive real decisions.
Lineage, redaction and audit aren't features you bolt on later. Building copilots that clear the risk committee.
Vibes don't scale. Building offline and online eval harnesses that catch regressions before your users do.
Internal developer portals fail on adoption, not technology. What we wish every team knew before rolling one out.
The strangler-fig pattern in practice: how we move critical systems while they keep serving traffic.
Autoscaling and load shedding engineered for Black-Friday traffic — without lighting your margins on fire.
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A monthly note on applied AI, platform engineering and running systems in production. No fluff, no spam — just the things we'd want to read.