Unlocking AI Potential with Eval-Driven Development (EDD)
Most teams follow a repetitive cycle in building AI agents: prompt, evaluate, tweak. This often leads to inconsistent results. Enter Eval-Driven Development (EDD) — a game-changer inspired by Test-Driven Development (TDD).
Why EDD Matters:
- Define Quality Upfront: Like TDD, EDD emphasizes creating evaluation rules before writing prompts to set clear expectations.
- Data-Driven Iteration: Improve outputs based on quantifiable metrics, not subjective feelings.
- Feedback Loop: EDD fosters a continuous improvement cycle, ensuring your AI agent meets all specifications consistently.
How It Works:
- Set Eval Rules: Determine what “good output” means for your agent.
- Create the Prompt: Build towards those clear targets.
- Evaluate Outputs: Score against your rules to identify areas for improvement.
- Iterate & Lock: Optimize until all criteria are met for production.
Ready to transform your AI development process? Discover the power of EDD with Iris, and let’s elevate agent design together! Share your thoughts below! 🚀
[Explore more on EDD at iris-eval.com/playground]
