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Production-Trace Failure Taxonomy — review 100 traces, build the eval substrate from real failures

Pick one Product.ai surface (chat, Alloy, or SimplyCodes' code-verification fleet). Review 100 anonymized production traces. Open-code the failure modes. Axial-code into a mechanism-distinct taxonomy with five-to-eight categories. Convert each load-bearing category into one or more task-level evals against a human-validated golden set. Wire the eval suite into the existing CI gate. Output is a working eval substrate producing real scores, derived from real failures, owned by the PM going forward.

STEP 1 — APPLY

Apply: Production-Trace Failure Taxonomy — review 100 traces, build the eval substrate from real failures

Submit your details below. After this step you'll record a short video questionnaire.

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FIT & LOGISTICS

Most of our roles are on-site or hybrid in Santa Monica. We need your own answers here — please don't rely on what's on your LinkedIn.

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I'm in LA (on-site / hybrid in Santa Monica works) I'm open to relocating to LA Hybrid with travel (I can fly in regularly) I need fully remote

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After submitting, you'll be taken to the Hireflix video questionnaire.

If you encounter any issues submitting your application, please reach out to hiring@product.ai.

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