Evals

Evals & production AI quality

Treat evaluation as a first-class deliverable. Regression suites, safety dims, and shipping without demo-grade guesswork.

ICP job: Stop shipping LLM features that only look good in demos

Published in this pillar

Topic inventory

Planned and live topics for this pillar. Priority 1 ships first.

  • BacklogP1checklist

    CI that blocks deploys on failing evals

    Query: Run LLM evals in CI/CD

    Sampling, cost caps, flake handling, and which suite is required vs nightly.

  • PublishedP1pillar-guide
    Evals are the product

    Query: Why LLM evaluation suites matter for production AI

    Eval suite as a scoped deliverable that changes how you negotiate engagements.

  • PublishedP1field-note
    Every postmortem becomes a regression test

    Query: Turn production AI incidents into eval regressions

    Cultural + technical loop from incident → fixture → CI gate.

  • BacklogP1framework

    Safety evals for clinical and health chatbots

    Query: How to evaluate safety of healthcare chatbots

    Refusal, escalation, medical advice boundaries, hallucination of dosages/claims.

  • BacklogP1framework

    Three eval dimensions: functional, qualitative, safety

    Query: LLM evaluation dimensions for product teams

    Brandlabs Discovery Sprint pattern — set targets in week 1–3.

  • BacklogP2field-note

    Building a prompt regression dataset that ages well

    Query: How to build LLM regression test datasets

    Golden sets, adversarial sets, and who owns updates.

  • BacklogP2framework

    Evaluating multilingual health assistants (India)

    Query: Evaluate Hindi Hinglish healthcare chatbot quality

    Locale fixtures, code-switching, and safety across languages — Myna lessons.

  • BacklogP2framework

    Groundedness evals for RAG in regulated domains

    Query: How to measure RAG groundedness healthcare

    Citation fidelity, refusal when retrieval is empty, and poison documents.

  • BacklogP2field-note

    LLM-as-judge: when it helps and when it lies

    Query: LLM as judge evaluation reliability

    Calibration, bias, and when human rubrics still win — Precision lessons.

  • BacklogP2comparison

    Offline vs online evals for AI products

    Query: Offline vs online LLM evaluation

    When batch suites lie; when production scoring is too slow.

  • BacklogP3field-note

    Closing the loop from Learn content to eval agents

    Query: AI evaluation platform for product teams

    How Precision’s Learn hub and Agent Library reinforce shipping quality — lab proof.

  • BacklogP3field-note

    Eval cost budgets that don't bankrupt the sprint

    Query: Cost of running LLM evaluation suites

    Sampling strategies and model tiers for judges vs product models.

Canonical hub: https://brandlabs.app/blog/topics/evals-production-quality