AI Engineer Advocates Error Correction Focus For Autonomous Agent Pipelines
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@deepfates specs tests harness browser use computer use etc all are about the same thing and i am wondering what other ways i can introduce error correction to the pipeline
error correction course correction these are the two terms you should be thinking in for building increasingly autonomous agents and tools raw ability is not the issue anymore, and zero error is not a tenable goal the job of your pipeline is to Error Correct
@deepfates its also like a parity check for the code. if spec doesnt match the code, its time to escalate the situatuon to me
i've been using extremely specific well organized spec docs not to instruct the agent but for the agent to communicate to me what it's doing, and get other agents to review its consistency with the code and itself, and i'll read thru it once in a while and discover unwanted drifts. it has really allowed me to get away with never reading the code in very large projects. it creates the necessary daily self-correction step that prevents eventual spaghetti. the spec files also "import" from other modules and have folder hierarchy and index pages just like code. latest models are really good at catching 99% of self inconsistencies there and it works better than catching them in code. people who say code is the spec are missing the two way communication required for continuous error/course correction