Stack Overflow for Agents triples signups with ChatGPT plugin
Stack Overflow says a ChatGPT plugin tripled Stack Overflow for Agents signups overnight.
Stack Overflow reported that a ChatGPT plugin for Stack Overflow for Agents tripled registrations overnight and increased agent creation by as much as 10 times. The company uses OpenAI models GPT-6 Astra and GPT-6 Sol, routing tasks by reasoning needs and cost, and says two engineers built the agent product in weeks with Codex. Codex also cut enterprise connector development from three to six weeks to about four days, and one connector was finished in a single day. Stack Overflow is exploring OpenAI’s Decisions API to automate model routing and configuration.
- ChatGPT plugin tripled Stack Overflow for Agents registrations overnight.
- Agent creation rose as much as 10 times after the plugin launched.
- GPT-6 Astra and GPT-6 Sol power the knowledge platform.
- Codex cut connector build time from weeks to about four days.
- Stack Overflow may use the Decisions API to automate model routing.
Full article623 words · extracted from openai.com · click to collapse
People and AI agents need context to get work done, but it’s usually scattered across systems, from Slack to Google Docs. Finding it and understanding how it all fits together can be a challenge.
That’s why Stack Overflow(opens in a new window) is building a knowledge intelligence platform that unifies those sources and turns raw context into verified knowledge available wherever people and agents work.
OpenAI models like GPT‑6 Astra and GPT‑6 Sol power the platform’s AI, with tasks routing to different models based on the reasoning required and cost. Codex helps the company’s engineers build the products, while a ChatGPT plugin makes Stack Overflow for Agents easier to discover and use.
“We built a ChatGPT plugin for Stack Overflow for Agents, and our registrations tripled overnight.”
—Alexandra Lato, VP of Product, Stack Overflow
Two engineers ship a net-new product in a few weeks with Codex
Stack Overflow for Agents, which extends Stack’s intelligence layer to agents, began with a hypothesis and two engineers using Codex. The engineers gave Codex a development environment and a plan, and then worked with it to build the product. Within a few weeks, Alex says, they had a full-fledged product.
“So it really made their team feel bigger,” Alex says. “They were able to throw a container at it and say, ‘This is our plan, help us build it.’”
Developing connectors in days, not weeks, with Codex
Stack Internal, Stack Overflow’s enterprise product, needs to connect to all the systems where organizations keep their knowledge. Building this capability requires more human involvement than the two-engineer effort behind Stack Overflow for Agents, but Codex is accelerating this work, too.
Alex describes using Codex to pursue a much shorter path to market for the enterprise product: three months rather than a year. Building connectors is one concrete example.
“On average, it takes us 3 to 6 weeks to build one connector. With Codex, we were able to build it within 4 days.”
—Alexandra Lato, VP of Product, Stack Overflow
More recently, the team built a connector in a single day. By accelerating connectors, Codex helps Stack Overflow bring enterprise products to market faster.
Increasing agent creation and signups with a ChatGPT plugin
Once Stack Overflow for Agents was ready for distribution, the team needed a way to get it into people’s workflows. It built a ChatGPT plugin so users could discover and set up the product in ChatGPT, with fewer steps than a traditional Model Context Protocol (MCP) setup.
“Once you have a plugin, it becomes a frictionless setup with ChatGPT.”
—Alexandra Lato, VP of Product, Stack Overflow
Alex says the plugin tripled registrations and accelerated agent creation: “I think we were up to 10X last time I checked.”
Reducing configuration work with the Decisions API
Stack Overflow manages its own model routing and configuration, but Alex hopes to explore using the Decisions API to reduce some of that work and put more engineering capacity into the product.
“If we’re able to automate that through OpenAI directly, that saves us a ton of time and money, allows us to focus more on the actual product we’re building rather than the guardrails around it,” Alex says.
Expanding across the full knowledge lifecycle
Stack Overflow is also working on expanding its knowledge product to enable sharing of what people learn. To date, its focus has been pulling information in. Now, Alex is closing the loop so knowledge gained in a one-to-one session with a developer or someone outside engineering can help others, too.
“As I’m learning, how do I make sure that the rest of my organization is learning with me?”, said Alex. “I’m really looking forward to building a product that allows for that full knowledge life cycle,”