Workflow Evals
Evaluation suites that mutate prompts, models, retrieval policies, generated code, and node structure before promotion.
Production AI is not a prompt. It is a system of context, tools, permissions, traces, evals, and feedback loops.
Beyond model bake-offs
The question is not which model wins in isolation. The question is which workflow shape survives speed, memory, quality, cost, and safety thresholds.
- Prompt and model diff testing
- Retrieval depth and reranking experiments
- Generated-code and node-count mutations
- Regression datasets from production failures
Promotion gates
Passing candidates are promoted only when quality, p95 latency, memory, tool reliability, and total price remain inside defined thresholds.
Related resources
Agents that generate, test, compare, and promote variants under measurable constraints instead of relying on intuition.
Trace-level visibility into model calls, retrieval, tools, decisions, approvals, costs, and failures.
A gateway strategy for choosing the right model per task based on privacy, cost, latency, quality, and failure mode.