Boring Wins: Quiet Automation Reshapes compliance review
Inside the quiet rewiring of research synthesis at Intercom.
For most of the last year, the conversation around small-model orchestration 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. Klarna's team treats theirs the way an SRE team treats a runbook.
Databricks has been quietly running data cleanup through Codeium for months. The results are unglamorous and, for that reason, more interesting than another benchmark chart.
Inside Databricks, the rollout looked less like a moonshot and more like a slow migration. A pilot, a champion, a quiet expansion, a budget line.
The cost curve matters here. Claude 4.5 Sonnet 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.
The cost curve matters here. Llama 4 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.
The cost curve matters here. Mistral Large 3 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.
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.