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Checked 25s ago18 accounts
  1. jev is so exciting! so you started using jev, now you need to know 1. what decisions is jev making? (observability) 2. is it making the right ones for my application? (evals) 3. how can i help jev make better decisions? (engine) and for obs+evals+engine, you need langsmith langchain.com

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  2. instead of generating text, jev from @typesafeai generates structured output this makes it great for classification tasks like model routing, tool selection/search, and guardrails of many forms! it's also ridiculously fast and cheap compared to LLMs doing the same tasks

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  3. right now, a lot of agents perform classification tasks / steps if you can replace those steps with a model that's optimized for classification, you can massively reduce latency and cost i think jev is re-kindling the "graph engineering" phase of agent design x.com/sydneyrunkle/s…

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  4. i normally would not post this late, but wanted to share what @huntlovell and I have been jamming on. @typesafeai just released Jev, a new type of classification model. it's really popular right now because it's ridiculously fast and cheap (up to 200x / 400x reductions vs comparable LLMs on classification tasks). learn all about Jev and how to build it into your harness!

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