The input remains available in an execution environment rather than being placed entirely in one prompt. The model can search, divide and inspect it through code, then use focused calls to help answer the broader question.
This approach changes context handling, not necessarily the underlying model's architecture. Correctness and cost still depend on query choices, execution controls and how intermediate results are combined.
ELI5
Think of working through a large reference book by looking up relevant sections and asking focused questions, rather than trying to hold every page in memory.
For example, an assistant can search a large repository, inspect selected functions and combine the findings into an answer about one feature.
Is recursion the same as a larger context window?
No. The strategy keeps input externally accessible and works with selected portions.
Does it guarantee a correct answer?
No. The system can still select unsuitable evidence or combine results incorrectly.
