Agents
Eval-Driven Development
A way of building AI systems where you write evals for a capability before the agent can do it, then iterate on prompts, tools, and harness until the evals pass.
In depth
A way of building AI systems where you write evals for a capability before the agent can do it, then iterate on prompts, tools, and harness until the evals pass. It is the AI counterpart of test-driven development. Anthropic recommends pairing capability evals, which start at a low pass rate, with regression evals that should stay near 100% so new work does not break old behavior.
Primary source: anthropic.com
Example
In practice, developers reach for Eval-Driven Development when they need the capability described above as part of an AI feature or workflow.
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FAQ
Common questions
What is Eval-Driven Development?
A way of building AI systems where you write evals for a capability before the agent can do it, then iterate on prompts, tools, and harness until the evals pass.
Why does Eval-Driven Development matter for AI developers?
Eval-Driven Development sits in the Agents part of the AI stack. Understanding it helps you make better decisions when building, debugging, and shipping AI features.
Where can I learn more about Eval-Driven Development?
Developers Digest publishes tutorials and videos that cover Agents topics including Eval-Driven Development. Check the blog and YouTube channel for hands-on walkthroughs.
Related
Related terms
Agents
Eval Harness
The infrastructure that runs evals end to end: it feeds tasks to the model or agent, records every step, applies graders, and aggregates the results into scores.
Agents
Agent Handoffs
A multi-agent mechanism where one agent passes control of the conversation to a more specialized agent, rather than calling it as a subroutine.
Agents
Evaluator-Optimizer
An agent workflow where one LLM call writes a response and a second call checks it against explicit criteria and sends back feedback.
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