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[ARTICLE · art-28569] src=roman.pt ↗ pub= topic=large-language-models verified=true sentiment=· neutral

Agent engineering: Claude Code

A developer describes shifting from using LLMs as occasional third-party dependencies to adopting an agent-driven execution model where the agent loop serves as the primary environment, relegating deterministic code like Python to a minor role for structured storage and API calls.

read1 min views1 publishedJun 2, 2026

I started with LLMs as another third-party dependency. In my apps, code defined the logic, and LLM calls handled small things like summarizing or tagging input. Over time, as agents gained more of my trust, I started experimenting with turning the execution model inside out.

Instead of code that occasionally calls an LLM, I use the agent loop as the execution environment itself. The agent drives the flow, and deterministic code only shows up where I actually need hard logic: structured storage and external API calls. Instead of being the main driver, Python becomes a small fraction of the overall logic.

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