Agents are just a loop: the hard part isn't the framework, it's the evals
alex_verem · x · 2026-10-11
The author argues agent frameworks are overcomplicated: at their core, an agent is just a loop — give the model a task and tools, let it pick a tool, run it and return results, repeat. Teams spend months comparing frameworks when writing the loop with plain API calls clears up most confusion.
Case study: they built an agent for a PE-backed healthcare billing company so clients could ask revenue questions in plain English instead of experts hand-writing SQL against a legacy claims schema.
Key lesson: building the loop was straightforward; the real work was evals — verifying the agent's answers against validated results from the claims data.
Related event: Devs Argue AI Agents Are Just a Loop at Their Core(2 posts)→
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