Thread

1. lubujackson · 1789504886 · focus · HN ↗

   After much fumbling around with prompts and evals, this is exactly how I am using LLMs in production, to narrowly make choices and return structured data. Any deterministic work gets pulled out of the prompt and my goal is to narrow the model output to be as clearly defined and as minimal as possible.

   Jev's focus on structured I/O and confidence scores are game changing. If this does at all what it claims, I think this is going to quickly become the new standard approach for agentic systems.

   1. CompleteSkeptic · 1789506148 · focus · HN ↗

      we hope so! the bigger hope is to not just eat LLM market share, but to allow for people to use AI much more in the inner loop of software

      1. copperx · 1789514183 · focus · HN ↗

         I'm sure you've thought of self-driving. How does the model work in that space?

         1. wg0 · 1789534162 · focus · HN ↗

            But the real problem in self driving isn't the decision making but object description. That is, computer vision if with cameras.

            Decision making isn't that of a bottleneck I suppose.

            1. sebzim4500 · 1789558246 · focus · HN ↗

               99.9% of the time you are right, but in the long tails (construction works, major road damage, temporary road markings that contradict permanent signs) I could see this kind of architecture being useful.

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