Playbooks for engineering with Jev

codila

@0xCodila

Jev is the "Internet" moment for the AI industry It tells your agents and LLMs what to do next, in milliseconds and at almost zero cost If you set it up correctly, you will have the AI engineer’s stack for 2028 In this article, I show you how x.com/i/article/2077…

Movez

@0xMovez

x.com/i/article/2100…

Ricker

@0xRicker

Jev could become the control layer AI agents have been missing. Instead of spending 5–20 seconds and expensive LLM calls deciding every next step, it can route actions in milliseconds at near-zero cost. In this article, I break down how x.com/i/article/2101…

Charly Wargnier ♨️

@DataChaz

Jev might genuinely be an “Internet moment” for AI. TypeSafe reports up to 193x faster and 444x cheaper performance in tests with Claude Fable 5.1 and GPT-6 Astra. @0xCodila just wrote a great 10-page article explaining what Jev is, how to use it, and where its 100x advantage comes from. Here are the 10 steps: 1 → LLMs create. Agents act. Jev decides the next move. 2 → Turn agent forks into three primitives: Choice, Score and probability. 3 → Build with OpenAI, Anthropic or xAI first, then swap Jev in without rebuilding the graph. 4 → Start with shared state, parallel decisions, risk thresholds and an execution queue. 5 → Batch decisions instead of making them sequentially. In one test, 13 questions were 10x faster and 12.2x cheaper. 6 → Put Jev at bounded forks: agent, model, tool, browser action or human escalation. 7 → Benchmark the whole loop, not just individual model calls. 8 → Rank wide, read narrow: shortlist first, then spend compute on what matters. 9 → Reuse the same system: State → Questions → Action → Verify. 10 → Keep Jev out of math, writing and irreversible execution. Code computes, LLMs create, Jev decides. The result: A slow, expensive agent loop becomes a much faster decision system that can route, score and escalate in milliseconds. Full breakdown below ↓

Codez

@0xCodez

Jev Founder, Diogo Almeida (ex-OpenAI): "The next era is not the Claude Code or Codex era, they are still part of the assistance era with human in the loop - JEV is what comes next for LLMs x200 faster, x400 cheaper, 0 hallucination, no human in the loop - that's JEV, this is how LLMs will look like" in 36-minute tech talk, Jev Founder explained why RLHF isn't a thing anymore and how modern LLMs will be built this talk is worth more than a Stanford Machine Learning degree watch today no matter what, then learn how to become a Jev Engineer in the article below

darkzodchi

@zodchiii

Jev Founder (ex-OpenAI): "I believe JEV is the biggest breakthrough we've ever worked on This sounds too good to be true but it's beating everything" In 5 minutes, he breaks down why older LLMs were great at talking and terrible at deciding and building. Watch it and then read the guide below on how to use it at it's fullest 👇🏼

Alex Volkov

@altryne

This is actually insane. This uses @typesafeai Jev model, as a plugin in Claude to review all the un-nesseasary tool calls, and it takes 1s to run! Like, literally, 1 second to take my Claude session from nearly 1M to ... 86K tokens! 😮 Ask your claude to install it and be amazed Use this prompt ``` Install, and configure : https://github.com/tamaratran/fast-jev-compaction ```