Astra's five-stage agent architecture for long-context work
The video argues that a 1M-token context window alone does not make an agent reliable; what matters is separating planning, tool use, verification, memory, and output into distinct layers.
GPT-6 ASTRA MAKES ONE AGENT MISTAKE IMPOSSIBLE TO IGNORE a 1M+ context window sounds massive, but long context alone does not make an agent reliable. what matters is how planning, action, checking, and memory are separated. plan → tool use → verification → memory → output 5 stages keep one bad decision from silently reaching production, while useful results can be stored for future runs. long-running work starts looking completely different. instead of one giant prompt carrying everything, each layer gets a narrow job and a clear failure point. better agents are starting to look less like smarter chatbots and more like small operating systems built around a model.
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