I built an eval harness to prove an LLM worked. It proved the opposite.
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I set out to have a language model classify integration failures. I built an evaluation harness to prove it worked. The harness proved it wasn't worth using. Final architecture: deterministic rules do the classification and structured extraction. The LLM does exactly one thing, writing plain-English incident summaries. Cheap rules to sort, AI to explain. Harness is here: https://github.com/fissible/llm-triage-eval Here are the numbers, then how I got them. The headline Classification: rules…
1Key Takeaways
- I set out to have a language model classify integration failures.
- I built an evaluation harness to prove it worked.
- The harness proved it wasn't worth using.
- Final architecture: deterministic rules do the classification and structured extraction.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that i set out to have a language model classify integration failures.
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