Build reliable LLM apps with simple Python workflows, not complex agent frameworks
Instead of wrestling with heavyweight agent frameworks, you can often solve LLM tasks by stitching together clear, deterministic workflow steps in plain Python. The author walks through an anomaly‑explanation use case, showing how modular, transparent pipelines keep control while still leveraging LLM reasoning where it matters.