// The Bitter Lesson of Tool Calling //

Tool calling is a design choice, and the defaults are quietly costing accuracy.

How so?

New research releases a generation-spanning comparison of programmatic tool calling against native JSON tool calling, across 14 language models on BFCL v4.

Programmatic tool calling exposes tools as typed Python stubs the model invokes through code, with execution and results handled in a single agent turn. It matches or beats JSON tool calling in 11 of 14 models, and the GPT-5.6 family gains 10.6% over the JSON baseline.

Under parallel fan-out it wins in 13 of 14 models. Under context rot it holds steady while the JSON baseline drops 2.3% on average.

The gains track model generation, so the advantage grows as code ability grows.

Paper: https://arxiv.org/abs/2608.06370

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