How 12 AI agent frameworks handle human approval (most badly)
A recent audit of twelve popular AI agent frameworks reveals significant shortcomings in handling human approval processes. Only two frameworks, LangGraph and Pydantic AI, meet the necessary production standards, while ten others are at risk of failure. The article outlines a strict rubric for evaluating these frameworks, emphasizing the importance of durability, idempotency, and proper user interfaces.
- ▪The audit assessed twelve AI agent frameworks against a strict production rubric.
- ▪Only LangGraph and Pydantic AI scored above 15 out of 30, indicating they are the closest to being production-ready.
- ▪Ten frameworks are one deployment away from breaking due to inadequate handling of human-in-the-loop processes.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3949951) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Adewole Babatunde Posted on May 25 How 12 AI agent frameworks handle human approval (most badly) #ai #agents #machinelearning #langchain I keep watching teams ship agent systems into production and then discover, on day three, that "the agent needs to wait for a human sometimes" breaks every assumption in their stack. Not because they didn't see it coming, every team plans for HITL.
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