The author built an AI bounty hunter with Jev that scans 24/7 for bug bounties, giveaways, grants, open source rewards, and design challenges, then filters, completes, verifies, and prepares submissions.
Jev made my first AI Bounty Hunter. It scans 24/7 for legal money bounties: ➜ Bug bounties ➜ Giveaways ➜ Grants ➜ Open source rewards ➜ Design challenges AI filters what it can actually do, completes the task, checks the result, and prepares the submission. It basically
Gregor Zunic showcases an open-source browser agent combining Browser Use and Jev, finding flights in 7 seconds for $0.0039, using a new action space per step, DOM state space, and small LLM fallback for typing.
Scott Williams predicts custom Jev-style models (parallel constrained decoding) will make existing company agent systems more token efficient, creating millionaires.
The user praises the JEV model for its extremely fast reproduction of each movement and command, believing bots will become smarter as a result.
