Stack Overflow is building a knowledge intelligence platform that unifies context scattered across systems such as Slack and Google Docs, and makes it available as verified knowledge wherever people and AI agents work. The platform’s AI runs on OpenAI models, including GPT-6 Astra and GPT-6 Sol, with tasks routed to different models based on the reasoning required and the cost. OpenAI’s Codex is used by the company’s engineers to build products, and a ChatGPT plugin makes Stack Overflow for Agents easier to discover and use.

Stack Overflow for Agents began as a hypothesis tested by two engineers using Codex. They gave Codex a development environment and a plan, and within a few weeks had a full-fledged product. Alexandra Lato, VP of Product at Stack Overflow, says Codex made the team feel bigger: they could hand it a container and ask it to help build according to the plan.

The enterprise product, Stack Overflow’s Stack Internal, needs connectors to all the systems where organizations keep their knowledge. This requires more human involvement than the two-engineer effort behind Stack Overflow for Agents, but Codex is accelerating the work as well. Lato says Codex shortened the path to market for the enterprise product from a year to three months. A connector that normally took 3 to 6 weeks to build was built in 4 days with Codex, and more recently the team built one in a single day.

For distribution, the team built a ChatGPT plugin so users can discover and set up Stack Overflow for Agents in ChatGPT with fewer steps than a traditional Model Context Protocol (MCP) setup. Lato says the plugin tripled registrations and accelerated agent creation, with agent creation up to 10X at last check.

Stack Overflow manages its own model routing and configuration, but Lato hopes to explore OpenAI’s Decisions API to reduce that configuration work and put more engineering capacity into the product. The company is also expanding beyond pulling information in to supporting the full knowledge lifecycle, so that what someone learns in a one-to-one session with a developer or someone outside engineering can help the rest of the organization learn too.