Why serious AI builders are skipping third-party evals
As AI copilots, autonomous agents, and conversational companions continue their march into the mainstream, the teams tasked with evaluating them are no longer asking: Did the model produce the correct answer?
Increasingly, they are asking whether the system was engaging enough and created enough value for users to return tomorrow, next week or next month.
It is a shift that fundamentally changes what evaluation means.
Co-Founder and COO, Kaon AI.
In the age of AI, "good" is a moving target. What delights one user may frustrate another, and what offers value to one business could be deemed irrelevant by the next.
That’s why success can no longer be measured solely through generic, external benchmarks, telemetry dashboards, or "LLM-as-a-judge" scores.
Real-time signals
Models grow stronger today not by adhering to an external standard, but based on traces and real-time signals from inside the organization. Evaluation, in fact, is becoming a core...
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