# Building a software factory for AI SDK

DevFeed: [Building a software factory for AI SDK](<https://devfeed.tech/articles/building-a-software-factory-for-ai-sdk-728.md>)

Original publisher: [Read original article](<https://vercel.com/blog/building-a-software-factory-for-ai-sdk>)

Author: Eric Dodds

Published: 2026-08-12T00:00:00Z

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>)

Tags: [agents](<https://devfeed.tech/tags/agents.md>), [ai](<https://devfeed.tech/tags/ai.md>), [anthropic](<https://devfeed.tech/tags/anthropic.md>), [automation](<https://devfeed.tech/tags/automation.md>), [bots](<https://devfeed.tech/tags/bots.md>), [bugs](<https://devfeed.tech/tags/bugs.md>), [building](<https://devfeed.tech/tags/building.md>), [claude-code](<https://devfeed.tech/tags/claude-code.md>), [code](<https://devfeed.tech/tags/code.md>), [codex](<https://devfeed.tech/tags/codex.md>), [coding](<https://devfeed.tech/tags/coding.md>), [engineering](<https://devfeed.tech/tags/engineering.md>), [maintainers](<https://devfeed.tech/tags/maintainers.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [pull-requests](<https://devfeed.tech/tags/pull-requests.md>), [sandboxes](<https://devfeed.tech/tags/sandboxes.md>), [software](<https://devfeed.tech/tags/software.md>), [vercel](<https://devfeed.tech/tags/vercel.md>)

## AI overview

The article describes how the AI SDK team built a software factory to manage a growing volume of issues and pull requests. It emphasizes automation designed to improve reviewer efficiency while preserving human accountability for agent-generated changes.

## Source excerpt

The AI SDK is one of the most popular open-source AI projects in the world. It serves over 20 million npm downloads a week and the repo has over 26,000 stars. Maintaining the codebase means tracking four moving targets at once: Model providers: new providers, new capabilities, and new bugs UI frameworks: bindings for React, Next.js, Svelte, Vue, and others Sandboxes: the execution environments agents run code in Harnesses: adapters for Codex, Claude Code, Pi, and others After multiple years of growth, the repo was getting 100+ new issues every month, and when Anthropic's Opus 4.6 model was released, PRs hit an inflection point. By late June, that compounding had accumulated over 1,000 open issues and almost 800 pull requests. That backlog is not a discipline problem. No maintainer, however good, can close that gap by working harder, and because generating code is cheap, it will only grow. Instead of trying to scale ourselves, we built a software factory. Four weeks in, it authors between 25 and 35% of PRs we merge and closes 70-80% of issues. Deciding what type of factory to build Before we built anything, we had to answer three questions: Why our existing approach using agents wasn't enough What level of automation fit a project like the AI SDK How to align automation and human effort to risk Why not add more agents? The best maintainers are already using agents aggressively. Mitchell Hashimoto runs Ghostty with the goal of an agent always working, and encodes every agent failure in AGENTS.md so it never repeats. Simon Willison runs four coding agents in parallel, and review bots like Vercel Agent and CodeRabbit sit on millions of repos. Other maintainers like Daniel Stenberg have opted to block AI-generated submissions to curl. All of it helps, but none of it solves for the core constraint: every one of these solutions still routes every change through one human's attention. We believe that human accountability is still the core of trust in agentic engineering, so