What's really happening inside an AI infrastructure team when agents start doing the work? The common story is that AI makes every team faster. The reality is more complicated, because the speed arrives unevenly and someone underneath has to absorb it. I sat down with Emma, who leads data infrastructure engineering at OpenAI, to find out what her team is actually building to stay ahead of the agents.
In this interview, I share the inside scoop on why platform teams become the bottleneck when AI agents scale across a company:
- Why app teams and platform teams accelerate at completely different rates
- How goal-directed agents start to feel adversarial without meaning to
- What OpenAI's data platform team built to buy back time
- Where a private eval suite fits into surviving constant model upgrades
For platform and infra engineers, this is the telegraph from the future: the pinch point is coming, and the teams that instrument the load now are the ones who stay standing.
For deeper playbooks and analysis: https://natesnewsletter.substack.com/
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