interview
2 links tagged interview. All tags.
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Vercel CEO Guillermo Rauch on the fight to split off models from agents techcrunch.com
Russell Brandom interviews Vercel’s Guillermo Rauch, whose central question is whether the model and the agent stay coupled. Rauch’s bet is that they come apart, and that companies will want to mix providers rather than commit to one lab. His reasoning is commercial rather than ideological: once you are optimising for production instead of demos, you start looking at price/performance, and at that point Gemini, DeepSeek and open-weight models become real options alongside OpenAI and Anthropic.
The numbers he gives for Vercel’s own vantage point: 6 million deployments a day, half of them triggered by coding agents, and more than a trillion tokens a day through the AI gateway. He names two killer apps for agents so far, coding agents and internal corporate agents that need careful access to company data, with Vercel Sandbox aimed at the second by restricting what an agent can reach without dulling it.
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The framing to remember is the positioning. We’re going to be the AWS of this generation, so obviously we’re fighting for a world of open protocols. Worth reading with that in mind: a company selling the neutral layer has an obvious interest in the layer above staying unbundled.
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How Intercom 2x'd their engineering velocity in 9 months with Claude Code lennysnewsletter.com
Brian Scanlan, a senior principal engineer at Intercom, talking to Claire Vo on “How I AI”. This is a podcast episode page rather than a written account, so the detail comes from the episode summary and transcript rather than an engineering write-up.
The headline number is narrower than the title suggests. What doubled in nine months was merged PRs per R&D employee, not output or delivered value, and a merged PR is a unit that AI tooling makes easier to produce in quantity. Worth holding that in mind before reading it as a doubling of engineering velocity. Alongside it: 100% of engineers, plus designers, PMs and TPMs, now ship code via Claude Code.
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The parts that travel better than the metric are the supporting machinery. Intercom built a skills repository whose hooks enforce engineering standards automatically, and telemetry through Honeycomb to track skill usage, adoption and quality across hundreds of engineers, so claims about what AI is doing to the codebase can be checked rather than asserted. Scanlan also argues that backlog zero is now achievable, and that the product itself needs preparing for an agent-first world through CLIs, MCPs and ephemeral APIs.
See also Intercom on letting AI approve PRs and Fin on good skills and bad skills.