用向量库给 GPT-6 Astra 编码 agent 加跨会话记忆
一个实验用 Actian VectorAI DB 作外部记忆，让 GPT-6 Astra 编码 agent 跨 5 个会话检索并复用已通过测试的修复，只存验证过的方案而非整段对话。
What if your AI coding agent fixed a bug today, but then forgot the solution in the next session? Came across a GPT-6 Astra experiment where they used Actian VectorAI DB as external memory to store and retrieve previously tested fixes across sessions. It worked by: -Search a vector DB for similar previous fixes -Check if the old fix applies to the current code -Save new fixes only after tests pass They also tested it across 5 sessions and the agent successfully retrieved earlier fixes. I liked the idea of remembering tested fixes instead of the whole conversation. I'm curious what others think about giving AI coding agents this kind of memory. Would it be useful in your workflow?