The short answer
Evals belong in the product roadmap because they reveal user-facing failure patterns and make improvements measurable.
An evaluation can tell a team that a workflow is failing. A good evaluation can tell them which failure is worth fixing next.
Cluster failures by user impact, frequency, and reversibility. That turns a vague quality problem into a set of actionable decisions.
Run representative tests whenever prompts, tools, models, or interfaces change. Evaluation should sit close to shipping, not at the end of a quarter.
A useful note, once a week
Make room for better signal.
About the author
Maya writes about the systems, people, and practical choices shaping the next generation of AI products.
More from Maya Chen →
The winning agent products will not feel like chatbots. They will quietly turn intent into reliable work.
Memory is useful when it helps an agent make fewer repeated decisions without becoming impossible to inspect.
A narrow agent with a clear finish line can create more value than a general assistant with a long list of promises.
Keep the good stuff coming
One thoughtful note on AI, agents, and AGI. No noise.
Have a thought? Comments are powered by a lightweight GitHub discussion embed.
