Knowledge catalogue
New VIDEO: From LLM Wikis to LLM Artifacts Shared all my thoughts on why LLM wikis and HTML artifacts are a big deal. Plus, new tools to help you build wikis and artifacts with agents. Just getting st
Learn how to build LLM Wikis and LLM Artifacts. New VIDEO: From LLM Wikis to LLM Artifacts Shared all my thoughts on why LLM wikis and HTML artifacts are a big deal. Plus, new tools to help you build
LLM Artifacts Connected to @karpathy's LLM Knowledge base idea, I've been building out a fun way to generate dynamic artifacts from these knowledge bases with the goal of discovering and revealing mea
YT Podcast → LLM Artifact This is now my favorite way to consume podcasts. Knowledge artifacts generated by agents. The agent (Opus 4.7) spots important insights, does deep analysis, and generates tho
// Your LLM judge disagrees with the experts // LLM Judges can be tricky to build. Here is an interesting showcasing why: There propose a reference-full benchmark of hundreds of complete human-to-huma
Gary Marcus 又放大招了！ 他直接把 Claude Code 源码泄露后的核心真相点破： ✅ Claude Code 是 LLM 时代以来最大进步 ✅ 但它根本不是纯 LLM，也不是纯深度学习 ✅ 核心文件 print.ts 足足 3167 行，塞满了 if-then 分支 + 确定性符号逻辑 Anthropic 在关键时刻还是靠经典符号 AI来保底，才让 Agent 真正可靠。 这波操
Claude Code is not AGI, but it is the single biggest advance in AI since the LLM. But the thing is, Claude Code is NOT a pure LLM. And it’s not pure deep learning. Not even close. And that changes eve
I released LLM 0.32a0 this morning, a major backwards-compatible refactor of my LLM Python library and CLI tool for working with language models - the new changes should help LLM work better with reas
In the era of base LLM scaling (2022-2024), I believed the LLM line of research would reach a capability plateau (as later seen with base LLMs). In late 2024, after the o3 test-time compute demo, I ch
Another fascinating paper on LLM Judges. (bookmark it) It's from Amazon, and they show that if you run panels of LLM judges, averaging their scores is a trap. 'Overall, we establish that robust aggreg
LLM Wikis are being slept on. I argue that creating knowledge bases with LLMs or coding agents is one of the most valuable applications of AI today. It's about being intentional in building and scalin
llm spend is starting to get really high... a key part of our LLM gateway is spend visibility and spend control sign up for the private beta to try it out today! https://www.langchain.com/langsmith-ll
When you are talking to an LLM, you are speaking to a synthesized work of interactive fiction, not a real being. ChatGPT, Claude, and Sydney are not their neural networks. If any LLM claims to be cons
LLM Wikis + HTML Artifacts are insanely powerful. You should seriously consider this in your workflows. LLM Wikis captures all the important information that lets you and your agents do meaningful wor
The largest agentic LLM Inference dataset has arrived! 206B tokens · 12,002 sessions · 1,186,582 LLM requests · 1,213,347 tool calls The traces include tool names, arguments, durations, and more. Expl
LLM next-token prediction is already a probabilistic classifier, so an open LLM can serve a Jev-like interface: discrete options in, fast probabilities out. Our own @ekzhang1 made it better at the job
Introducing Sakana Namazu: An LLM API with Japanese-vibes! Today we’re rolling out an upgraded version of our LLM, Namazu, now available as an API. Try Sakana Namazu API: https://sakana.ai/namazu 🐟 🐟
🚨Emergency webinar: LLM Wikis and how to give your agent memory LLM Wikis are so hot right now - OpenWiki by @BraceSproul up to nearly 7k GitHub stars in less than a week I'll be chatting with Brace a
Last minute webinar this Thursday Will cover all things related to 'LLM Wikis' 🚨Emergency webinar: LLM Wikis and how to give your agent memory LLM Wikis are so hot right now - OpenWiki by @BraceSproul
We're going to be discussing LLM memory & wiki's this week with @hwchase17 and @devstein64! Don't miss it 🚨Emergency webinar: LLM Wikis and how to give your agent memory LLM Wikis are so hot right now
If you use LLM-as-judge, this one is worth reading. (bookmark it) It's actually one of the most effective ways to use LLM-as-a-Judge for evals. Holistic judge scores hide both their reasoning and thei
RWKV-7 G1g is here: the world's best pure RNN LLM, and a competitive LLM in general. Try https://huggingface.co/spaces/BlinkDL/RWKV-Gradio-2 for bsz16 7B inference. G1h in June 🙂 p.s. const 15000+tps
We built TERMS-Bench, a three-tier benchmark for LLM agents in real-world economic negotiation. No LLM-as-judge, no outcome rubrics: the environment itself is the verifier. 🏆Among frontier models, @An
Hacker News → LLM Artifact I built the most personalized HN feed. It only tracks topics I do research around based on memory and LLM wiki. No point in storing bookmarks. With a few automations, rules,
Introducing TokenSpeed, a speed-of-light LLM inference engine. > TensorRT LLM level performance > vLLM level usability > Built by a lean and mission-driven team in two months > MIT license, open-sourc
arXiv Papers → LLM Artifacts This is how I keep up with AI research now. It's like having access to the most personalized arXiv feed. Automations run everyday to curate papers based a set of rules and
LLM Knowledge Base → Slides When @karpathy shared his LLM Knowledge Base setup, many were wondering how to generate more visual forms of the wiki. There are many options, but I think @GammaApp is one
Romeo Lupascu has criticized the prevailing AI agency framework, which relies on repeatedly looping an LLM core with identical context. He calls this strategy “deeply flawed” and argues that it should
Things to try with Jev right now: 1. LLM-as-a-Judge evaluation 2. Routing for agent harnesses harness 3. Scaling agent orchestration by enabling smarter subagent creation with SOTA classification capa
Everyone keeps asking me how to build a second brain or an LLM wiki. Here is the easiest setup I have found. I took my Wiki Builder skill, installed it into HyperAgent (@hyperagentapp) as a reusable s
April saw significant activity in large language model releases, with five major models introduced including Gemma 4, GLM-5.1, Qwen 3.6, Kimi K2.6, and DeepSeek V4. These releases have been added to a
A few notes on how to get started with building LLM Knowledge Bases. @karpathy popularized it but most people don't know where to start. Everyone should be creating LLM Wikis. Live session tomorrow. S
Test of Time LLM from some legends...pretty fun! Announcing Talkie: a new, open-weight historical LLM! We trained and finetuned a 13B model on a newly-curated dataset of only pre-1930 data. Try it bel
Great paper from Amazon. In discusses when not to trust LLM judges for agent evaluation. (bookmark it) A common way to compare task agents is to have an LLM user simulator talk to each one and an LLM
We have released a little skill to help you build LLM Wikis with your agents. Releasing a little skill to help build LLM Wikis. More people should be building LLM wikis. I hope the skill is useful for
LLM agents loop, drift, and get stuck on hard reasoning tasks up to 30% of the time. Current fixes are either too blunt (hard step limits) or too expensive (LLM-as-judge adding 10-15% overhead per ste
Great technical paper from Harvard and MIT. It's on role drift in compound LLM systems. (bookmark it) End-to-end RL improves the accuracy of a multi-module LLM pipeline without constraining how the mo
Insightful paper on recursive self-improvement with a frozen LLM. (bookmark it) Memento 3 clears every level of all 25 public ARC-AGI-3 games and uses 44% of the human action count. The underlying LLM
// ContextLeak in AI Agents // The whole attack surface here is a tool name and a tool description. Stealing an LLM agent's runtime context, meaning the user prompt, the execution trajectory and the t
Just WOW! Absolutely unacceptable. I look forward to understanding how that is possible. LLM tools get going and you can’t be 100% certain what they’re gonna do. Just like any LLM, you can ask coding
Now we know: The popular Ox Alpha LLM was GLM-5.3-Flash... Compared to GLM-5.2, this new GLM-5.3-Flash model uses: - a Kimi Linear-style 3:1 (super*) hybrid attention pattern with 34 Kimi Delta Attent
some interesting trends in terms of LLM adoption 👀 📊 The latest from the LangSmith Signal: We looked at API call volume and developer adoption trends across LLM providers using LangChain open source t
The LangSmith Signal report analyzes API call volume and developer adoption trends across major LLM providers, leveraging LangChain's open-source data and observability platform to track usage pattern
Great paper on designing multi-agent systems. How many distinct communication topologies does an LLM multi-agent system actually need? This works claims that it's about six. Technical summary: Researc
We’re Hiring: Member of Technical Staff (LLM Development) 🐟 https://sakana.ai/careers/member-of-technical-staff-llm-development/#English The role: ・Develop LLMs that form the foundation of Sakana AI’s
Sakana Chat just got a big upgrade. No login required, free to use: https://chat.sakana.ai/ Powered by Fugu and Namazu, our Japanese LLM. With newly added code execution, you can vibe-code interactive
Try the Tavily plugin for LLM-driven search inside Grok Build Tavily is now live as an official plugin in @grok Build. Bring real-time, LLM-optimized web search into your Grok Build workflows. You'll
Vibe coding isn't just for your PC anymore. Here's LLM Hub generating and previewing code entirely on an iPhone. Everything runs locally. Using the RunAnywhere SDK, Timmy Qian ported LLM Hub, an Andro
New research from Google DeepMind on effective model routing. LLM routers get judged on accuracy and cost. Both can look great while the router is meaningless. If every model in your society responds
who wants to help eyal poke holes in this approach to run LLM inference... in browser? Looking for peer reviewers 🧪 Built an LLM inference engine in pure WebGPU/WGSL. Runs in browser and Node, on-devi
Beyond being fast, LiteParse is designed to provide highly accurate, semantically coherent text for LLM use. We benchmarked every open-source, model-free PDF parser on LLM QA tasks - from PyPDF to PyM
LangSmith's LLM Gateway is a cost control and monitoring tool designed to prevent unexpected high spending on LLM API calls by providing observability and likely rate-limiting or budget-cap features.
“Dependably for LLM agent failures” @hwchase17 Started on this and finding it awesome; also LangSmith engine sparked an idea. The 'Dependabot like for LLM agent failures'. LangSmith Engine gives you t
This works really well btw, at the end of your query ask your LLM to 'structure your response as HTML', then view the generated file in your browser. I've also had some success asking the LLM to prese
Nice paper on optimizing agents and their graders together. The key finding is that you want to update your LLM grader alongside the agent instead of keeping it fixed, because the agent's failure mode
Sometimes everybody is right! Me, spring 2023 onwards: giving LLM-driven agents unrestricted internet access with read/write permissions is going to be a security nightmare. The AI industry: Agents ar
Brilliant paper on long-horizon agents. They cut 78.9% of an agent's LLM calls while raising its success rate. Here is how: It turns out that ReAct issues one primitive action per model round. That al
This is one of the most useful writeups I have seen on keeping an LLM judge effective in production. (bookmark it) Netflix runs judges over hundreds of thousands of show-level recommendation explanati
// Skill Misevolution in Self-Improving LLM Agents // Self-improving agents write their successes down as reusable skills. An unsafe success becomes reusable policy long after the input that triggered
Big new release of my LLM CLI tool and Python library for talking to hundreds of different LLMs - reasoning traces, OpenAI Responses support, server-side tools, smarter logging and a whole lot more ht