Vercel CEO Guillermo Rauch on the fight to split off models from agents
"The reality is, when you're optimizing for production, you start looking at a price/performance," Guillermo Rauch tells TechCrunch. Known for its cloud infrastructure that allows developers to deploy agents without managing servers, Vercel has quietly become one of the most central companies in AI software. The company currently sees 6 million deployments a day, half of them triggered by coding agents, and more than 1 trillion tokens flow through the company's AI gateway daily.
Key Takeaways
- After the company's ShipNYC conference last week, we sat down with Vercel CEO Guillermo Rauch for his take on this moment in AI, and how platform companies like Vercel end up competing with major labs.
- That's driving a lot of the token utilization in the world, but when you produce so much software, you need somewhere to put it.
The second killer app of agents is the internal agent that helps you run the company.
- For [the] sandbox, the biggest advantage is data control.
A real risk of AI that I always think about is, when you get a coding IDE like Devin or Cursor, if you're in the wrong setting, they may train on your entire codebase.
- The bottleneck for people like her has not been her creativity, intelligence, ability to build relationships, it's been data.
- Same technology, it's just APIs.
Stats & Key Facts
- #The company currently sees 6 million deployments a day, half of them triggered by coding agents, and more than 1 trillion tokens flow through the company's AI gateway daily.
After the company's ShipNYC conference last week, we sat down with Vercel CEO Guillermo Rauch for his take on this moment in AI, and how platform companies like Vercel end up competing with major labs. Here's a lightly edited transcript. It feels like there's a different energy in the community this year, fewer pilot programs and more focus on how to make things work well in practice.
I'm sure you've seen that a lot with clients, but I'm curious what that journey has looked like within Vercel. Last year was about prototyping. The sky's the limit, unleash the agents, everyone can build, and so on.
We did that, and we learned a lot because we had hundreds of agents organically developed and deployed within the company, and then you started getting into the realities of agents in production, and some of the challenges. The biggest lesson for me was the home-run use cases, the two killer apps of agents. One is the coding agent, of course.
For more details please read the original article at TechCrunch AI.
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