Keep anything as Markdown for your AI agents

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Likes: 303
Reposts: 11

Read from X on 24 Sep 2026. Counts change daily.

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Search rerank: 7x faster7x faster search rerank compared to the current hybridx.com
Tagging speed: 50x faster50x faster tagging of content vs GLM 4.7 Flash with no failuresx.com

keep.md saves pages, posts, files and notes as plain Markdown that an AI agent can search, read and update. When Jev became available on Cloudflare Workers, Ian Nuttall put it to the test on the site.

Nuttall reports two results. Search reranking, reordering results by relevance after an initial retrieval, ran about 7 times faster with Jev than the site’s current hybrid approach. Content tagging ran about 50 times faster than with GLM 4.7 Flash, with no failures.

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Introducing Clef: our open-source decision models, and new RL fine-tuning platform

Cloudflare's launch post for Clef and Clef-flash, two decision models on Workers AI that accept the Jev request format and open weights under Apache 2.0. It covers the architecture, Cloudflare's own benchmark tables against Jev, Kev and Laya, and a new reinforcement learning service.

Michelle Chen (@michellechen)140k viewsOpen

ArticleSupport inbox triage

Decision Model Leaderboard

Cloudflare's live leaderboard for decision models on the Jev Decision Index suite, with Clef, Clef-flash, Jev, Kev-9B and Laya plotted by score and latency. Cloudflare built and ran it, so treat the ranking as vendor-run.

Cloudflare (@ritakozlov)41k viewsOpen

Article

[AINews] Jev: a System One Model that only decides/classifies/routes/scores

AI News daily roundup leading with the Jev launch, summarising RLCD and TypeSafe's 20-200x speed and 40-400x cost claims. Its recap of reactions notes posters using Jev as a structured classifier, judge and routing policy where text generation is unnecessary.

Latent.Space (AI News)Open

ArticleIntent and model routing+1

Jev means structured output is interesting again

Argues Jev's speed comes mainly from constrained single-token generation and aggressive prefill, techniques reproducible with existing LLMs, rather than a new architecture. Still treats very fast structured output as a new primitive, while doubting Jev matches frontier models on raw intelligence.

Sean GoedeckeOpen

Article

Zaious/jev-capability-atlas

An independent, evidence-based map of where Jev's calibrated-decision claim holds up and where it breaks down, built from real API-call receipts rather than a leaderboard.

Zaious26 starsOpen

Article

willkelly/jev-evaluation

An adversarial evaluation of Jev with nine experiments and 28 predictions fixed before any data was collected. One run covered 123,805 requests over 138 minutes for $12.69, with five failures, plus a 13-rule prompting guide.

willkellyOpen

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Keep anything as Markdown for your AI agents

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Introducing Clef: our open-source decision models, and new RL fine-tuning platform

Decision Model Leaderboard

[AINews] Jev: a System One Model that only decides/classifies/routes/scores

Jev means structured output is interesting again

Zaious/jev-capability-atlas

willkelly/jev-evaluation

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