Stack Overflow for Agents: two engineers, Codex, and a ChatGPT plugin

On October 27, 2026, OpenAI published a Stack Overflow case study. The company released Stack Overflow for Agents — a product that delivers a base of verified knowledge not only to people but also to AI agents (programs that independently execute chains of tasks). The product was built by two engineers in a few weeks with Codex (an environment in which the model writes code according to a given plan). A plugin for ChatGPT (an external extension that connects a third-party service to the chat) was added to it. In the headline, OpenAI speaks of tripling registrations; in the text, of growth in agent creation up to 10×. The comparison baseline is not specified.

Previously, Stack Overflow sold knowledge to people through Stack Internal, an enterprise product. It needs connectors (modules for connecting to external systems such as Slack and Google Docs). Building one connector took 3–6 weeks; now it takes 4 days. This is a reduction in engineering plumbing, not a property of the model itself. The second difference is the channel: not a separate website, but a plugin inside ChatGPT, where agents are already being sought.

In practice, the platform consolidates disparate context sources into a single layer and routes tasks between the GPT-6 Astra and GPT-6 Sol models — according to the required depth of reasoning and cost. For the team, this means that knowledge from Slack and Docs can be given to agents in a single format, without spending months building a connection to each system. An example from the case is that very connector in 4 days instead of 3–6 weeks. The engineers, according to Alex from Stack Overflow, gave Codex a container and a plan and then worked together with it: “it really made their team feel bigger.”

What remains unknown: the absolute numbers of registrations and created agents, what the tripling and 10× were calculated relative to, what exactly the plugin does inside ChatGPT, and how much the product costs.