AI BriefingEval-driven development: Lessons from evaluating GenAI at scale
Key point
To ensure the reliability of its GenAI products, Airbnb introduced 'Eval-driven development,' treating evaluation not as a simple post-hoc check but as a core engineering process.
Details
Unlike traditional software testing, GenAI outputs are non-deterministic, and the criteria for a 'correct answer' are subjective. Therefore, beyond simple unit tests, teams must manage the complex structure of AI evaluating AI.
When building GenAI products, Airbnb practices Eval-driven development, elevating evaluation from a mere afterthought to a core stage of development. This is to systematically verify the complex interactions involving LLM reasoning, Tool calls, and RAG (Retrieval-Augmented Generation).
For successful GenAI evaluation, the following approaches are emphasized:
- Evaluation automation: Building an AI-powered automated evaluation system to handle a scale that humans cannot review one by one
- Multi-layered evaluation structure: Verifying in stages, from simple response quality to the logical validity of complex workflows
- Iterative feedback loops: Establishing a process to immediately reflect evaluation results in model tuning and prompt engineering
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