What is workflow-specific artificial intelligence evaluation?
Definition
Workflow-specific artificial intelligence evaluation uses representative end-to-end work rather than only isolated prompts. A software-development evaluation can include code quality, instruction adherence, tool use, vision, speed, cost and whether the output is suitable to merge.
The approach reveals tradeoffs that aggregate benchmarks can hide. Tests should preserve comparable prompts and tools, record repair and supervision, and use enough repeated cases to distinguish consistent performance from one strong result.
Acronyms and aliases
real-workflow AI evaluation synonymworkflow-specific AI evaluation variant
General terms
Related terms
Frequently asked questions
Why evaluate AI models in real workflows?
Real workflows combine constraints and tools that isolated benchmarks may omit, making results more relevant to actual use.
What should workflow-specific AI evaluation measure?
It should measure task success, quality, instruction following, efficiency, cost, latency and required human repair.
