Real guardrails for autonomous agents after one almost destroyed my infrastructure
After an autonomous agent nearly wiped my production database, I built a real guardrails layer. Here are the controls, the code, and the logs that saved my skin.
After an autonomous agent nearly wiped my production database, I built a real guardrails layer. Here are the controls, the code, and the logs that saved my skin.
The viral HN demo shows Cloudflare agents running the full infra cycle with zero human intervention. I replicated it against my Railway stack and documented exactly what the agent executed on its own, where I had to step in, and what permissions it asked for that it absolutely shouldn't have. Real a
I took the DeepClaude repo (467 points on HN) and dropped it into my real production loop. The combination isn't simply "better than either alone" — there's a specific task regime where DeepSeek V4 Pro destroys and Claude fails, and vice versa. Here are my actual numbers.
Specsmaxxing promises to cure "AI psychosis" with YAML specs for agents. I applied it to my real workflow with Claude Code and found the trap nobody mentions: the quality problem doesn't disappear — it moves into the YAML.
The HN thread claimed Claude Code blocked or redirected billing when OpenClaw appeared in Git history. I built a public repo, a reproducible harness, and ran the matrix. On Claude Code 2.1.126, I did not reproduce the block.
I ran git blame on a project where I used Claude Code heavily. 61% of the lines aren't mine. That's not a legal problem yet — it's an accountability problem for when something blows up in production and nobody knows whose signature is on it.
I ran GPT-5.5 against my actual production prompts and compared it to GPT-4o on latency, cost, and output quality. The marketing leap doesn't match the leap in my metrics. Here are the numbers.
874 points on HN for 'I cancelled Claude'. Before joining the chorus, I ran my own regression cases against real Claude Code logs. The degradation is real — just not where everyone's complaining about it.
HN reported that the Linux kernel is receiving removals based on LLM-generated security reports. I took the same pattern and ran it against my own production code. What I found made me uncomfortable — but not for the reasons I expected.
32 years in the dev trenches. Here I write what I learned, what I broke, and what nobody tells you in the tutorials.
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