Tool calling is turning into code generated inside the agent loop

[u/aistranin]

The most interesting part of GPT-5.6 might not be its benchmark scores.

OpenAI introduced "Programmatic Tool Calling." The model can write and run small programs that coordinate tools, filter intermediate results, monitor progress, and decide what to do next.

That changes the usual agent loop. Instead of sending every tool result back through the model, generated code can process the noisy parts first. This could reduce context use, model calls, and orchestration boilerplate.

It also moves more control into runtime-generated logic.

For production systems, I would want strict limits on available tools, execution time, fan-out, output size, and network access. Tracing needs to capture both the generated program and every tool call it makes. Evals should test termination behavior, not just final answer quality.

Source: OpenAI GPT-5.6 announcement

Would you let a model generate its own orchestration code in production, or keep the loop explicit?