# The Agent Stack

DevFeed: [The Agent Stack](<https://devfeed.tech/articles/the-agent-stack-721.md>)

Original publisher: [Read original article](<https://vercel.com/blog/agent-stack>)

Author: Tom Occhino

Published: 2026-06-20T04:30:00Z

Content type: article

Language: en

Sources: [Vercel News](<https://devfeed.tech/sources/vercel-news.md>)

Topics: [AI Bots](<https://devfeed.tech/topics/ai-bots.md>), [vercel ai sdk](<https://devfeed.tech/topics/vercel-ai-sdk.md>), [SDKs](<https://devfeed.tech/topics/sdks.md>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-gateway](<https://devfeed.tech/tags/ai-gateway.md>), [api](<https://devfeed.tech/tags/api.md>), [models](<https://devfeed.tech/tags/models.md>), [routing](<https://devfeed.tech/tags/routing.md>), [workflows](<https://devfeed.tech/tags/workflows.md>)

## AI overview

The article presents Vercel's Agent Stack for building production-grade AI agents. It highlights AI SDK as a model-agnostic interface and AI Gateway as a single endpoint for routing across model providers.

## Source excerpt

Agents are designed to do almost any kind of work, from answering support tickets to writing code. No matter how complex the workload, how long it runs, or how many turns it takes to complete, every agent needs three core capabilities to operate: Agents need to connect to models and route between them Agents need to run workflows across many steps Agents need to connect to the systems that make them useful and the platforms people use to interact with them Implementing these capabilities to build a complete agent forces developers to choose between vendor lock-in with a single provider API, stitching together solutions, or building abstractions themselves. The Agent Stack gives you all the building blocks you need to create and ship production-grade agents. Connect to models Agents don't run on a single model. Every task has a different cost, latency, and capability tradeoff, and the right call depends on what the agent is doing. It needs one interface to reach any of them, a way to route between them, and a way to stream back to the user. AI SDK gives an agent one interface to call any model, and AI Gateway routes across hundreds of them from a single endpoint. AI SDK Every lab exposes model calls through their own API. Streaming, tool calls, structured output, and the shape of the request all vary, so every provider you support adds another integration to build and maintain. AI SDK is a single interface for building AI apps, agents, and frameworks. It is platform, framework, and model agnostic, and allows you to generate text, images, speech, video, and more. AI Gateway Tokens are a production dependency now, the way bandwidth is for the web, and agents use different models per task. Integration across labs means separate keys and billing from providers that are expensive, rate-limited, and always changing. AI Gateway is the CDN for tokens, routing them on the global network we have run for over a decade. It routes each call through a single endpoint, fails over w