How Booking.com Cut a onboarding From Hours to Seconds
A field report on small-model orchestration and what it changes for sales teams.
For most of the last year, the conversation around tool-first agents has been louder than the evidence. That is starting to change.
Teams that win with fine-tuned distillation 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. Duolingo's team treats theirs the way an SRE team treats a runbook.
Databricks has been quietly running QBR prep through Vercel v0 for months. The results are unglamorous and, for that reason, more interesting than another benchmark chart.
Ramp has been quietly running expense reporting through ChatGPT Canvas for months. The results are unglamorous and, for that reason, more interesting than another benchmark chart.
The skeptical read is that we are watching a feature, not a platform. The optimistic read is that structured outputs is exactly the kind of feature that becomes a platform when nobody is paying attention.
None of this guarantees a clean story. Google DeepMind 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.