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The Quiet Architecture Shift Behind GPT-5.1

A field report on structured outputs and what it changes for analysts.

By Priya Raman3 min read

For most of the last year, the conversation around RAG-as-a-service has been louder than the evidence. That is starting to change.

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

The cost curve matters here. Command R+ 2 is roughly an order of magnitude cheaper per token than the equivalent model 18 months ago, and that changes which problems are worth automating at all.

Teams that win with computer-use agents 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. Figma'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.

What Google DeepMind actually shipped with Mistral Large 3 is less a single capability and more a cluster of small, compounding improvements — the kind that only show up when you put a real workflow on top.

None of this guarantees a clean story. DeepSeek 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.

#voice#policy#evals

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