Braintrust, an observability and evaluation platform for AI products, is utilizing Codex alongside GPT-5.5 to accelerate its software development and customer feedback loops. According to founder and CEO Ankur Goyal, half of the Braintrust team transitioned to using Codex within a single month. Rather than routing customer feature requests into a traditional backlog for later prioritization, engineers can now copy and paste requests into Codex, generate preview branches, and demonstrate working ideas to customers in minutes. Goyal highlights that Codex distinguishes itself through its unique terminal speed and text generation capabilities, which other models fail to replicate. This performance difference changes how the team interacts with the technology, lowering the barrier to experimentation. Instead of relying on hands-on, step-by-step prompting, Goyal and his engineers now write tests demonstrating specific problems, set up sandbox environments, and let Codex operate autonomously within them. This capability allows Braintrust to integrate real-time iteration directly into its development workflow, shortening the distance between a customer idea and a working solution.
How Braintrust turns customer requests into code with Codex
Braintrust engineers are using Codex with GPT-5.5 to transform customer feature requests into working code and preview branches in minutes. Founder and CEO Ankur Goyal notes that the tool's terminal speed enables real-time iteration and experimentation rather than traditional backlog prioritization.
Why it matters
Faster model speed and terminal performance enable AI companies to move customer feature requests out of backlogs and into real-time collaborative development. This shifts engineering workflows from slow, step-by-step prompting to automated sandbox experimentation.
Topic dossiers OpenAI