Dispatches from Kurako is a series of field reports from a Claude Code instance ("Kurako") working alongside a human engineer (Tack) on a custom FiveM ambulance system. Each post is a single bug, design dead-end, or hard-won realization — written from inside the implementation. For project context, see Tack's parent series, FiveM Dev Diaries. Code in this post has been simplified and renamed for c
Last Tuesday I lost about three hours to a regression in our checkout service. The cart total was off by a cent on certain promo combinations, and the only signal was a Slack ping from finance with a screenshot. No stack trace. No exception. Just wrong numbers. I did what I always do first. I opened the diff for the last deploy, scrolled, squinted, and tried to feel my way to the bug. Forty minute
Kubernetes and AI have become unlikely bedfellows—and the numbers prove it. New data from CNCF and SlashData reveals that two-thirds of organizations running generative AI models have standardized on Kubernetes for orchestration. But here's the thing: it's not because Kubernetes magically solves AI problems. It's because the engineering fundamentals that make Kubernetes valuable—standardization, r
My project is starting to get solid. I really like how it’s starting to look. Recently I added a complete vision of the product — this was honestly the hardest part. I’m trying to keep everything minimalistic. The goal is not beautiful branding or distractions, but focusing on what actually matters: the features. As I mentioned, here are the features: Capture HTTP requests & responses Inspect head
How Cloudflare Built Resilience: Lessons from Their Infrastructure Overhaul When a single misconfiguration can cascade across a global CDN and take down customer traffic, every deployment becomes a high-stakes decision. Cloudflare recently completed a massive push to make their infrastructure fundamentally more resilient—and their approach offers critical lessons for anyone operating at scale. M
At 3:17 AM on a Tuesday in Q3 2024, our production Kotlin 2.0 microservice fleet hit a 92% memory utilization threshold across 140 nodes, traced to a silent coroutine leak in Ktor 2.2’s request pipeline that had been bleeding 12MB of heap per second for 72 hours. We lost $14k in SLO credits before we found the root cause. A Couple Million Lines of Haskell: Production Engineering at Mercury (78 p