Stack Overflow for Agents triples signups with ChatGPT plugin

Two engineers shipped Stack Overflow for Agents in a few weeks with Codex, and its ChatGPT plugin helped drive up to 10× growth in agent creation.

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Company size: Startup

Region: North America

Industry: Technology

Products: Codex, API

10x

More agents created with the ChatGPT plugin

More signups for Stack Overflow for Agents overnight with the ChatGPT plugin

Maximum reduction in time to build one connector, from 3–6 weeks to 4 days

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Two engineers ship a net-new product in a few weeks with CodexTwo engineers ship a net-new product in a few weeks with Codex

Developing connectors in days, not weeks, with Codex

Increasing agent creation and signups with a ChatGPT plugin

Reducing configuration work with the Decisions API

Expanding across the full knowledge lifecycle

Two engineers ship a net-new product in a few weeks with Codex

Developing connectors in days, not weeks, with Codex

Increasing agent creation and signups with a ChatGPT plugin

Reducing configuration work with the Decisions API

Expanding across the full knowledge lifecycle

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.

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.’”

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.

More recently, the team built a connector in a single day. By accelerating connectors, Codex helps Stack Overflow bring enterprise products to market faster.

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.

Alex says the plugin tripled registrations and accelerated agent creation: “I think we were up to 10X last time I checked.”

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.

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,”

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