Evals are the new PRD

In the realm of AI product development, traditional Product Requirements Documents (PRDs) are being replaced by "evals," which are structured, repeatable tests designed to determine if an AI system behaves as intended. Unlike deterministic systems where output is predictable, AI systems produce varied results, necessitating a shift in how product managers define and measure success. Evals act as specs, acceptance criteria, and roadmaps by providing measurable signals for desired outcomes, enabling teams to iterate and improve continuously. The development process involves constructing a "flywheel" where production data feeds back into evals, fostering ongoing enhancement of the AI product. This cycle of observing, analyzing, evaluating, and improving not only accelerates product quality but also creates a durable advantage. Evals employ different types of judges, from algorithmic to AI judges with human alignment, to assess various dimensions of AI output, ensuring that quality improvements align with real-world performance. The role of the AI product manager now includes defining what "good" looks like in code, curating data to highlight deficiencies, maintaining the flywheel for continuous improvement, and safeguarding against regressions. This new approach requires a systematic, data-driven process, where every interaction with the product becomes a potential signal for enhancement, thus ensuring the AI product consistently evolves and improves.

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