A cross-platform memory layer for AI coding agents: conversations from Claude Code, Codex, DeepSeek Harness, OpenClaw, and OpenCode become Markdown memories indexed in Milvus, with optional Jev reranking through the TypeSafe API.
A local SQLite memory layer for CLI agents with an opt-in Jev reranker that batches Noul judgments over the top 40 recalled memories and falls back to a local cross-encoder on errors.
A web-search app where Jev picks sources, time ranges, and query terms, then ranks results from a dozen engines through Search1API, returning links and relevance scores instead of generated answers.
I've been using Jev by @typesafeai Here's the six things i've tried and am confident I'll still use Jev for 60 days from now.
There's many more experiments, ideas, and things I think I will use it for. It's a big deal (more on why in next post).
But I am only sharing thingsShow more
This made me rethink where AI actually fits into security engineering.
For purely engineering work, forget about ChatGPT or Claude.
TypeSafe AI just released Jev, and I think it’s going to change how we build AI into security workflows.
Instead of asking an LLM to “investigateShow more
TypeSafe AI
@typesafeai
we are officially out of stealth! join the frontier and get access to Jev on our website (link on profile)
Jev 发布没几天,开源社区已经开始疯狂复刻了🔥
最值得推荐的五个模型:
1、Laya 421M:原生决策模型,支持 Mac
2、Decider-2B:最像 Jev,基于 Qwen3.5
3、NanoJev 0.6B:专门的 Decision Head
4、Reflex:Qwen3.5 + Direct Logits
5、System-One 4B:专门做概率校准Show more
小墨同学
@xiaomovps
Jev 刚发布没几天,开源社区就出现了同款🔥
Decider-2B模型,是基于 Qwen3.5-2B 做了特殊调整
它和 Jev 模型是一样的 只做选择 评分和判断 不是文本类的 LLM 模型
但两者还是有几个明显区别:
1、模型
Jev:闭源 System One Model
Decider:Qwen3.5-2B,约 1.9B 参数,Apache 2.0 开源
2、价格
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400xShow more