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LLM agents turn code interpreters into portfolio sizing engines when you evolve the prompt

This story is from 2026-09-17. It is preserved in the archive; the latest stories are on the live feed.

Most agent benchmarks evaluate tool use as an information-gathering exercise. You hand a model an API key for stock prices, a search tool for financial headlines, and a Python REPL. Then you watch whether it makes the right API calls before writing a summary paragraph. In practice, giving an agent…

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  1. 2026-09-17 16:45 · DEV Community — AI
    LLM agents turn code interpreters into portfolio sizing engines when you evolve the prompt

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