HelloPM: Lessons from Vercel's rise to a $9.4 billion AI native company
This is the first entry in Ankit Shukla’s AI-era company case study series on HelloPM, published July 1, 2026. It examines how Vercel reached a $9.4 billion valuation without building an AI tool, by positioning as the infrastructure layer that developers reach for after AI generates code.
The article opens with a specific framing: during the gold rush, the reliable business was selling shovels. Vercel applied this logic to the current AI coding boom. As AI tools made it easier for non-engineers to generate working software, the volume of projects needing deployment, hosting, preview links, environment management, and serverless infrastructure grew. Vercel already provided that infrastructure, and had done so long enough to be embedded in developer workflows before demand expanded.
What Vercel actually does. The platform handles the work that comes after code exists — deployment pipelines, global hosting and performance, serverless functions, environment variables, and observability. Products like v0 and the AI SDK extended their presence into the generation step, but the foundation was post-generation infrastructure.
Why the timing worked. Vercel had developer trust and significant Next.js adoption before the AI coding wave arrived. Infrastructure tools are difficult to displace once integrated into production pipelines. When AI expanded who was writing software — bringing in founders, designers, and PMs who had not previously built deployable applications — those new builders entered a market where Vercel was already the default deployment answer.
The second-order question Shukla proposes. Rather than asking what AI tool to build, he suggests asking what behaviors AI makes more common, and then asking what those behaviors create demand for downstream. In Vercel’s case: AI makes more people build more software, and those people need somewhere to put it. The article argues this question is more generative than following the headline behavior.
What the case study does not claim. The article does not suggest that every infrastructure play in the AI era will replicate Vercel’s result, and it does not offer a decision framework. It documents one company’s position, timing, and prior investment — factors that were already in place before the AI coding boom arrived. Teams reading this to find a repeatable formula will need to assess which elements of Vercel’s situation are specific to their context.
The case study is most useful for product managers thinking through platform positioning in AI-adjacent markets, and for teams deciding whether to compete as an AI feature or as a layer that AI features depend on. It is part of a series — subsequent entries in the HelloPM archive examine other AI-era companies using a similar analytical frame.