OpenAI has published a case study describing how Braintrust, a software team, uses Codex alongside GPT-5.5 to turn customer requests into working code. According to the source, the main benefit is speed: engineers are able to run experiments and write code faster than with traditional methods.
The workflow appears to center on interpreting customer needs and translating them into code changes. Codex handles the code generation, while GPT-5.5 likely assists with reasoning or natural language understanding, though the source does not detail the exact division of labour.
Since there is only one source, there are no conflicting accounts to reconcile. The article is written from OpenAI's perspective, so it inherently highlights the effectiveness of its own tools. That said, the concrete example of Braintrust using these models for real engineering work provides a practical reference point for teams considering similar approaches.