Jev roundup: agent harness, HFT bot and GTM automation use cases
Memetic Machines uses Jev as a decision engine to filter content and prediction markets, and collected four real-world write-ups: an agent harness, a 24/7 HFT bot, GTM automation and a 200x faster agent brain.
Jev took the world by surprise. It's a model trained with reinforcement learning for calibrated decisions (by @typesafeai). It's not your regular LLM that spits out the next token one word fragment at a time. It only replies with JSON containing confidence-weighted answers. (Useless, you may be thinking...) Yet this is exactly the decision gating bigger models need to be more accurate and effective, at a fraction of the cost. So cheap the output is practically free. So fast it can play Super Mario Bros in real time. At @memeticmachines we're using it to power our decision engines, creating higher-quality prediction markets and helping our ingestion pipelines sort content more accurately into our ontology of reality. Best reads from last week to see what this beauty can do: 1_ Building an agent harness with Jev, by @sydneyrunkle https://x.com/sydneyrunkle/status/21007543645457616432/ 2_ A 24/7 HFT trading bot with sub-100ms decisions, by @RohOnChain https://x.com/RohOnChain/status/21013118139086520693/ 3_ Jev for GTM automation, step by step, by @jasonzhou1993 https://x.com/jasonzhou1993/status/21019252283353172384/ 4_ 10 steps to a 200x faster agent brain, by @0xCarnagee https://x.com/0xCarnagee/status/2101019382009004249
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