How the current eval tooling landscape compares for teams trying to ship reliable AI workflows.
Why it matters
AI products are becoming systems of action. This changes how teams design permissions, review loops, metrics, memory, retrieval, and human escalation.
What to watch
Look for patterns that reduce operational risk: clear ownership, durable logs, reliable evals, cost controls, and interfaces that let users supervise without micromanaging.
The interesting question is no longer what can the model do — it’s what should we let it do unsupervised, and on whose behalf.
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