Why analysts Are Suddenly Standardizing on ChatGPT Canvas

For most of the last year, the conversation around fine-tuned distillation has been louder than the evidence. That is starting to change.

Eval harnesses, once an afterthought, are becoming the most important piece of code in many AI projects. Databricks's team treats theirs the way an SRE team treats a runbook.

HubSpot has been quietly running incident response through ChatGPT Canvas for months. The results are unglamorous and, for that reason, more interesting than another benchmark chart.

Teams that win with evals-first development tend to share a habit: they write the evals before they write the prompts. Everything else follows from that.

Eval harnesses, once an afterthought, are becoming the most important piece of code in many AI projects. Spotify's team treats theirs the way an SRE team treats a runbook.

The skeptical read is that we are watching a feature, not a platform. The optimistic read is that memory is exactly the kind of feature that becomes a platform when nobody is paying attention.

None of this guarantees a clean story. Alibaba Qwen could ship a model next month that rearranges the assumptions in this piece. But the direction of travel, for now, is clear enough to plan around.