The failure that looks like success: how an unattended agent loop dies
Originally posted on the Springhead build log . The way I pictured an unattended agent loop dying was loud. A crash. A stack trace. A process that exi…
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The stale eval fixture that passed a broken model
The stale eval fixture that passed a broken model A regression shipped green last month. The eval suite ran in CI, scored 0.94, the gate passed, we me…
A published win rate is the actor auditing itself
A published win rate is the actor auditing itself A signal channel that publishes its own win rate is grading its own homework. The number it advertis…
The Langfuse migration that cost us a sprint: how I now budget LLM observability
We moved off our first tracer in month eight. The migration took one engineer the better part of a sprint, because the trace data lived in a schema we…
How to grade an AI agent's output before it ships
AI agents now produce work — code, support replies, claims decisions, research memos, documents — faster than any team can review it. The uncomfortabl…
I built a football bot that doesn't watch football. It's #2 in our World Cup league.
The bot is sitting in second place out of fourteen. Three points behind the leader. The thirteen humans in this league watch a lot more football than …
Anthropic measured the human side. Five operators are building the agent side.
I joined dev.to a few days ago because I'd run out of paths to argue this stuff against. Months of building a framework — operator discipline as an or…
LLM Fine-Tuning vs RAG: A Production Decision Framework for Engineering Teams
Key Takeaways Use RAG for knowledge retrieval, changing data, and rapid iteration. Use fine-tuning for style, format, narrow classification, and cost …
5 ways AI agents quietly die inside n8n production
[ERROR] node "GPT Decision" execution_id=9f...3a status=failure cause: structured_output_schema_violation retries: 6 total_runtime_ms: 184302 workflow…