Agentic Horizons – When The Wheels Start To Wobble…

I want you to remember this formula. It’ll be on a blue plaque outside my house one day. R = 1 – (1 – C)(1 – P) Where R is the reliability of a single step – a single model interaction – in an agentic workflow, C is the probability of the model’s prediction being correct, and P is the probability of errors being caught before they propagate and compound if it isn’t. There are things we can do to improve C, but there’s only so much uncertainty we can squeeze out of the input, and physics predicts that LLMs are very unlikely to get much more reliable. So it stands to reason that the key to extending agentic horizons lies in validating the output from each step before it becomes input to the next. The E in C.R.E.S.S. stands for Empirical – contexts should contain validated information, observed in reality – and not raw model output. I liken LLM output to untreated sewage. It has to be carefully filtered to be made safe for drinking in future interactions. It’s important to remember that…

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