Hallucination Budgets and the Engineering of Trust

There is a version of this story that is mostly hype. There is another version, the one we are interested in, that is mostly engineering.

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.

Databricks has been quietly running data cleanup through Replit Agent for months. The results are unglamorous and, for that reason, more interesting than another benchmark chart.

The cost curve matters here. Grok 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.

What DeepSeek actually shipped with Qwen 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.

Inside Figma, the rollout looked less like a moonshot and more like a slow migration. A pilot, a champion, a quiet expansion, a budget line.

Snowflake has been quietly running data cleanup through Perplexity for months. The results are unglamorous and, for that reason, more interesting than another benchmark chart.

The cost curve matters here. Gemini 3 Pro 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. xAI 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.