{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"Machine Learning Tech Brief By HackerNoon","title":"Your AI Agent Needs an Unknown State","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/d10030d3\"></iframe>","width":"100%","height":180,"duration":1207,"description":"\n        This story was originally published on HackerNoon at: https://hackernoon.com/your-ai-agent-needs-an-unknown-state.\nA timeout does not prove an AI agent’s action failed. Here’s how explicit unknown states, idempotency, and reconciliation can prevent duplicate effects.\nCheck more stories related to machine-learning at: https://hackernoon.com/c/machine-learning.\n            You can also check exclusive content about #ai-agents, #distributed-systems, #agentic-ai, #human-in-the-loop, #ai-agent-reliability, #tool-execution, #ai-agent-security, #human-in-the-loop-ai,  and more.\nThis story was written by: @dmytro_nasyrov. Learn more about this writer by checking @dmytro_nasyrov's about page,\n            and for more stories, please visit hackernoon.com.\nWhen an agent loses the response to a consequential action, retrying can duplicate an effect that already happened. Preserve the uncertainty, keep the operation identity, and only retry when evidence or an idempotency contract makes it safe.","thumbnail_url":"https://img.transistorcdn.com/KyA01h2FD2insgk-wX_xzV6vbJnTNl2BvPYVL-XaI9A/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzQxMjcyLzE2ODM1/ODI0ODgtYXJ0d29y/ay5qcGc.webp","thumbnail_width":300,"thumbnail_height":300}