fine-tuned distillation: The Pattern Behind the Best Agents This Quarter
A field report on long-context workflows and what it changes for analysts.
The interesting question is not whether Glean works. It does. The interesting question is what teams do with it once the novelty wears off.
Eval harnesses, once an afterthought, are becoming the most important piece of code in many AI projects. Booking.com's team treats theirs the way an SRE team treats a runbook.
Teams that win with small-model orchestration tend to share a habit: they write the evals before they write the prompts. Everything else follows from that.
The skeptical read is that we are watching a feature, not a platform. The optimistic read is that live web browsing is exactly the kind of feature that becomes a platform when nobody is paying attention.
The skeptical read is that we are watching a feature, not a platform. The optimistic read is that computer use is exactly the kind of feature that becomes a platform when nobody is paying attention.
Eval harnesses, once an afterthought, are becoming the most important piece of code in many AI projects. Linear'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 agent mode is exactly the kind of feature that becomes a platform when nobody is paying attention.
None of this guarantees a clean story. Cohere 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.