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The Engineering Harness: Turning an AI Agent Into a Reliable Colleague on a Real Information System

· 14 min read
Software Engineer & Cloud Architect

The frontier conversation in AI has quietly shifted. For two years it was "which model is smartest?" Now the people actually shipping agentic systems are asking a different question: "what do you put around the model?"

That surrounding machinery has a name — the harness. The model is the engine. The harness is the chassis, the steering, the seatbelt and the brakes. A brilliant engine bolted to nothing kills you at the first corner; a modest engine in a well-built car gets you home every time. On the ktayl-solution information system — a six-node Kubernetes platform running a simulated insurer's entire IS — I've spent months building the harness that lets an AI agent do real engineering work against live infrastructure without me holding my breath.

This post is that harness, concept by concept. Not the theory — the actual rules I put in place, why each one exists, and the incident that usually forced it.

3-2-1, Not 1: Why I Kept MinIO Instead of Going Cloud-Only for Backups

· 5 min read
Software Engineer & Cloud Architect

While hardening disaster recovery on the ktayl-solution information system, a fair question came up: we already mirror backups to Cloudflare R2 — so why keep a MinIO server running on the controller at all? Couldn't we retire it and go cloud-only?

R2's free tier is generous, cloud object storage is durable, and one less service to operate is always appealing. So it's a reasonable instinct. It's also wrong — and about an hour after I talked myself through why, I proved it the hard way by deleting the wrong bucket prefix. This post is that reasoning, and the honest incident that validated it.