LLM Evaluation•6 min
How to Evaluate an AI Workflow Before Scaling It
A scorecard for deciding whether an AI workflow should scale, stay in pilot, be redesigned, or be rejected.
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Test cases, regression checks, acceptance criteria, and evidence for AI workflows.
A scorecard for deciding whether an AI workflow should scale, stay in pilot, be redesigned, or be rejected.
Before building a copilot or agent, map the process friction, decision latency, rework, and evidence needed to prove value.
A research-backed note on using scale-invariance tests as part of AI system evaluation, falsification, and deployment discipline.
A research note on recursive structure, compression, and why complex AI systems need falsifiable evaluation rather than abstract certainty.