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How Braintrust turns customer requests into code with Codex | OpenAI

May 29, 2026

Braintrust engineers use Codex with GPT‑5.5 to turn customer feature requests into preview branches in minutes and expand the scope of engineering experiments.

Company size: Enterprise

Region: North America

Industry: Technology

Products: Codex

50%

of the Braintrust team moved to Codex in one month

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Braintrust is the observability and eval platform for shipping quality AI products.

With Codex, its engineers can now take customer feature requests and create preview branches to show working ideas to customers in minutes.

In one month, half of the Braintrust team moved to Codex. For founder and CEO Ankur Goyal, the biggest change is not just faster coding. It’s a faster feedback loop with customers.

“It sounds simple, but Codex can literally print more text in the terminal without getting slow, and other models just can’t replicate that,” says Goyal.

> “The biggest gain is speed.”

—Ankur Goyal, Founder and CEO

Turning customer requests into previews in minutes

Speed is often treated as a property of a tool, one that exists separate from its core functionality, but for Goyal, the speed difference “changes the way I interact with Codex compared to other models.”

With Codex, the Braintrust team can integrate iteration into its development workflow rather than letting requests sit and wait. “Codex unlocked our ability to try out customer feature requests in real time,” says Goyal. “Previously, if someone gave us a feature request, it would enter a backlog and get prioritized later.”

Instead, the team can copy and paste requests into Codex, create a preview branch, and show the completed request to the customer in minutes. “The really cool thing with Codex is that we get to iterate and ideate on feature requests with the customer in real time,” says Goyal.

> “The more code we write, the more customer problems we can solve, and Codex is the most effective way to do that right now.”

Speed makes autonomous problem-solving possible

For Goyal, Codex changes how much setup it takes to try new ideas. “With other models, I would have to try to prompt the model to solve a specific problem,” he says. Slower tools require more hands-on guidance, which raises the cost of experimentation.

“With Codex, I’ve shifted to writing a test that demonstrates a problem, creating a sandbox environment, and then letting Codex run in that environment,” Goyal says. “This is a novel use case for me, and I can run experiments because of the speed.”

That speed gives the Braintrust team more room to experiment. Instead of prompting step by step, engineers can define the problem, let Codex work in a controlled environment, and move faster from idea to working solution.

> “The really cool thing with Codex is that we get to iterate and ideate on feature requests with the customer in real time.”