◈Bluesky50
YHacker News50
XX / Twitter50
listening to
Jev
150
mentions
tracked
tracked
net sentiment
+25%
48 positive
92 neutral
10 negative
volume & sentiment over time
Sep 25, 2026 · Daily
sources
most discussed
decision / models
active days
1
what people keep raising
- decision / models 36
- built 15
- models 9
- model 7
- open-source / alternative 4
- performance 3
mentions
Showing 126–150 of 150 mentions
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Y Hacker News 1w neutral decision / modelsJevmem – automatic project memory for Claude Code, built on JevAh, well that makes a bit more sense. Admittedly I haven’t really looked into Jev and thought it was an open decision model rather than a proprietary product from TypeSafe. Ah, well that makes a bit more sense. Admittedly I haven’t really looked into Jev and thought it was an open decision model rather than a proprietary product from TypeSafe.view source ↗
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Y Hacker News 1w positive modelsJevmem – automatic project memory for Claude Code, built on JevThe AI language really stands out, too. "What is automatic and what depends on the agent". A human might write, "jevmen watches your coding session with Claude Code or Codex and picks just the right moment to remember important things that you decided along the way. There are some differences in how jevmem works, depen… The AI language really stands out, too. "What is automatic and what depends on the agent". A human might write, "jevmen watches your coding session with Claude Code or Codex and picks just the right moment to remember important things that you decided along the way. There are some differences in how jevmem works, depending on which coding harness you are using. The table below summarizes these differences:" I don't know why the models were generally trained to be so brief, but it's definitely not the way anyone I know actually writes. A second pass is always a good idea to clean this stuff up. And, thankfully, the models are all pretty good at that.view source ↗
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Y Hacker News 1w neutral builtJevmem – automatic project memory for Claude Code, built on JevTypeSafe AI are the providers for Jev. This complaint is like saying it’s a red flag that Claude Code sends lots of information to somewhere called Anthropic. TypeSafe AI are the providers for Jev. This complaint is like saying it’s a red flag that Claude Code sends lots of information to somewhere called Anthropic.view source ↗
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Y Hacker News 1w ▲ 31 positive open-source / alternativeShow HN: Doom or Bloom, map your AI worldviewMap your AI worldview by answering a few questions, and see how you compare with others. only takes a few minutes && free & open source && private by default && powered by Jev I think this is a really important question for everyone to be asking themselves, and my hope is that this lil project helps to move our convers… Map your AI worldview by answering a few questions, and see how you compare with others. only takes a few minutes && free & open source && private by default && powered by Jev I think this is a really important question for everyone to be asking themselves, and my hope is that this lil project helps to move our conversations around AI futures in a more balanced, productive direction.view source ↗
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Y Hacker News 1w positiveWe're Gonna Need More MathematiciansHe is right. We will need more expert verifiers, thanks to the eventual Jevon's Paradox. He is right. We will need more expert verifiers, thanks to the eventual Jevon's Paradox.view source ↗
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Y Hacker News 1w neutral builtJevmem – automatic project memory for Claude Code, built on JevCurious how this compares to my own tool, https://deciduous.dev I will have to give it a run-through today. I haven't used Jev yet so this should be interesting. I'd be interested to see if any Deciduous users have opinions, too. Curious how this compares to my own tool, https://deciduous.dev I will have to give it a run-through today. I haven't used Jev yet so this should be interesting. I'd be interested to see if any Deciduous users have opinions, too.view source ↗
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Y Hacker News 1w neutral decision / modelsJevmem – automatic project memory for Claude Code, built on Jevjevmem watches Claude Code, Cursor & Codex chats and keeps a JEVMEM.md in your repo up to date. After each message, Jev (TypeSafe) decides whether anything is worth remembering — a decision, a bug, a change of mind — and writes the keepers to that file. Reversed decisions get marked superseded. Install: npm i -g jevmem… jevmem watches Claude Code, Cursor & Codex chats and keeps a JEVMEM.md in your repo up to date. After each message, Jev (TypeSafe) decides whether anything is worth remembering — a decision, a bug, a change of mind — and writes the keepers to that file. Reversed decisions get marked superseded. Install: npm i -g jevmem (needs a TypeSafe API key) Held-out check on 66 messages (23 Sep 2026) vs six frontier LLMs: save/skip 98.5% (tied with Astra); save+correct kind 95.5% (Astra 98.5%, Opus 97.0%); changes of mind 5/5; median 0.30s via Jev API (~0.6s end-to-end) vs 2.8–4.3s for the LLMs; cost $0.000127/decision. Single run by me — treat 1–2 message swings as noise. Limits: early v0.4; fully automatic only in Claude Code today (Cursor/Codex via agent/MCP); messages go to the TypeSafe API with secrets stripped; if the API is down it skips.view source ↗
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Y Hacker News 1w ▲ 58 neutral builtJevmem – automatic project memory for Claude Code, built on Jevview source ↗
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Y Hacker News 1w ▲ 1 neutralSmall questions, measurable gains with Jev – CraftCXview source ↗
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Y Hacker News 1w ▲ 2 neutralJev and Reasonersview source ↗
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Y Hacker News 1w neutralShow HN: Jev Plays Pokémon RedJev can't come up with original text, but I did consider giving it a list of hilarious names. Jev can't come up with original text, but I did consider giving it a list of hilarious names.view source ↗
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Y Hacker News 1w positive modelsJev Is Built for TinkerersAuthor here, and I'll declare my bias so I'm upfront. I am co-founder of Ably, a realtime infrastructure company, so I wanted Jev to be a low-latency story. Two weeks ago I built Jev Pong and thought it was. Then I tried to find a use our customers would ship and couldn't, so I sorted the whole first week of Jev posts … Author here, and I'll declare my bias so I'm upfront. I am co-founder of Ably, a realtime infrastructure company, so I wanted Jev to be a low-latency story. Two weeks ago I built Jev Pong and thought it was. Then I tried to find a use our customers would ship and couldn't, so I sorted the whole first week of Jev posts instead of guessing. The data is on a separate page linked from the piece (see https://mattheworiordan.github.io/jev-landscape/ and https://github.com/mattheworiordan/jev-landscape/ , which scanned ~6k posts and looked at the data from two public gateways and twenty rapidly emerging rivals). The short version. Adoption is very real (a quarter of Vercel's AI Gateway requests, 2% of its tokens), but the 100x claim is against frontier models. In practie, Jev is more like 7x and 5x against small models you'd have likely used. So my conclusion is Jev is a great model, unblocks things you could not do before when you're in builder mode, but when you move into production and definitely do things at scale, you're unlikely to be on Jev. We have solutions already for the things Jev does, just with some friction.view source ↗
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Y Hacker News 1w ▲ 3 negative performanceShow HN: Jev Plays Pokémon RedHey HN! Wanted to share a fun project I've been hacking on. Given Jev can make decisions really fast (but not fast enough to play Doom yet sadly), I wanted to try and push it to play a more complex game than Tetris. So I went with Pokémon. I've spent endless hours playing this game as a child so building this was a ton… Hey HN! Wanted to share a fun project I've been hacking on. Given Jev can make decisions really fast (but not fast enough to play Doom yet sadly), I wanted to try and push it to play a more complex game than Tetris. So I went with Pokémon. I've spent endless hours playing this game as a child so building this was a ton of fun. I open sourced everything in case you want to hack on it yourself here: https://github.com/christianmat/jev-pokemon The game is being streamed live including the tokens and cost - hopefully we get all the badges and don't get stuck in a cave :)view source ↗
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Y Hacker News 1w ▲ 5 neutral builtJev Is Built for Tinkerersview source ↗
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Y Hacker News 1w ▲ 2 neutralReAnchor, a Jev Optimizer in DSPyview source ↗
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Y Hacker News 1w ▲ 2 neutral modelA Jevlike using an escalation model to route between a classifier and an LLMview source ↗
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Y Hacker News 1w ▲ 3 neutral modelsBenchmarking Jev, Laya, and five open models under three stressesview source ↗
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Y Hacker News 1w ▲ 1 neutralMy Take on Jevview source ↗
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Y Hacker News 1w ▲ 2 neutralShow HN: JevPertus – Jev-style option scoring on Apertusview source ↗
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Y Hacker News 1w ▲ 1 neutralJev CEO talk: I made ChatGPT, now I'm building what's next [video]view source ↗
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Y Hacker News 1w ▲ 2 neutralI made a linter using Jev for things a regular linter can't catchview source ↗
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Y Hacker News 1w ▲ 3 neutralShow HN: Herobrine – Minecraft buddies using jevview source ↗
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Y Hacker News 1w neutral modelShow HN: Jevper – the Jev interface on top of any OpenAI-compatible modelas an alternative option to Jev, and to take advantage of LLM's reasoning for the classification. as an alternative option to Jev, and to take advantage of LLM's reasoning for the classification.view source ↗
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Y Hacker News 1w neutralJev Based Code ReviewBut isnt the whole point of Jev that "we trained it so you dont have to"? Yet it make such a simple mistakes still. But isnt the whole point of Jev that "we trained it so you dont have to"? Yet it make such a simple mistakes still.view source ↗
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Y Hacker News 1w positive decision / modelsJev Based Code Review> Like the classifiers we were building 15 years ago with random forrests and logistic regressions I think no one mentioned here, but the obvious difference is that Jev can spit out decisions directly from natural language input. None of these ML models could do that, and other than a full-fledged LLM (which is optimiz… > Like the classifiers we were building 15 years ago with random forrests and logistic regressions I think no one mentioned here, but the obvious difference is that Jev can spit out decisions directly from natural language input. None of these ML models could do that, and other than a full-fledged LLM (which is optimized for conversation and agentic tasks) or some classical NLP models (which underperform compared to LLMs, AFAIK), there is nothing right now that rivals Jev-like models. Of course it's not perfect, but seems like the right step forward for quick classification/decision tasks based on natural language.view source ↗