Jev in Practice: Browser Use and Agent Workflows

The author uses three.js to visualize Jev and Laya handling falling cars, showing the Jev decision model's self-balancing ability.

On TermiX's agent.family, Jev FC Buddy lets a player take 1P while the AI plays 2P in classic NES co-op games, alongside a 1 USDC service that makes custom 3D hologram cards.

A 3D office demo staffs 8 departments with agents, connecting Jev with Claude, GPT and GLM through a custom orchestrator to check budgets across 9 ad accounts and draft fixes.

The author is building a free university in the Project0 metaverse and adapted Levanto's decision model into a quality-control agent that tours virtual spaces and gives improvement feedback, saying Sage worked better than Jev and cost far less.

AutoTrust AI answers community questions, saying JEV-27B-VL centers on a visual decision loop of seeing the screen, calibrating a decision, then clicking or typing, is open-sourced under Apache-2.0, and will get quantized versions soon.

Built overnight with Opus 5.5, the browser fighting game has Jev read the fight several times a second and choose jabs, low kicks, circling, or clinches, with live odds on screen and bodies driven by MuJoCo physics.

Using Jev for routing, scenes, 3D and copy go to Sonnet 5.5 while frame-by-frame aesthetic review goes to Opus 5.5, and four parallel agents built four scenes in about 24 minutes.

In Termix's points campaign, $1 lets users try agents including an AI 3D holographic card studio and the Jev FC Buddy for classic NES games, with 5x points on qualifying purchases and 500 more for posting about the experience.

For $1 you can try Holo Card Studio, which turns text into a 3D holographic card, and Jev FC Buddy, an AI co-op partner for NES games.

The Japanese virtual character's official site uses Jev to judge comment type, mood, gesture and malice in parallel, picking reply text only from candidates so hallucinations and tone breaks are ruled out by design.

The author built six 3D residents with their own homes, jobs, needs and friendships, and Jev decides whether they grab food or seek shelter, letting users inject a situation and watch the small world react.

A single prompt produces a complete 3D town: GPT-6 directs, HYPER3D generates the scene and vegetation, and Jev plans quickly with automatic collision avoidance and one-click scene randomization.