๐ด High Significance
Developer Tools
๐ด millionco/react-doctor โ Your agent writes bad React. This catches it โ score 87
Sources: github_trending
Your agent writes bad React. This catches it
๐ด One thing I didnโt expect after building AI agents for businesses. โ score 83
Sources: reddit/r/AIAgents
Most companies donโt actually know where automation should begin. They usually come in asking for: an AI employee a smart assistant a fully autonomous agent But after mapping their operations, the real bottleneck is often something much smaller. Things like: - leads sitting unanswered for hours -
๐ด lsdefine/GenericAgent โ Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption โ score 79
Sources: github_trending
Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption
๐ด I built a framework where multi-agent swarms are YAML files, not code. โ score 74
Sources: reddit/r/AIAgents
I work on enterprise projects where you have thousands of documents, dozens of APIs, configuration dumps, and project code scattered across different systems. Last year I needed multi-agent setups to make sense of all this and kept running into the same problem: every time I wanted to change who doe
Other Signals
๐ด 80 tok/sec and 128K context on 12GB VRAM with Qwen3.6 35B A3B and llama.cpp MTP โ score 88
Sources: reddit/r/LocalLLaMA
Just wanted to share my config in hopes of helping other 12GB GPU owners achieve what I see as very respectable token generation speeds with modest VRAM. Using the latest llama.cpp build + MTP PR, I got over 80 tok/sec with 80%+ draft acceptance rate on the benchmark found here: [https://gist.github
๐ด Apple Removes 256GB M3 Ultra Mac Studio Model From Online Store โ score 81
Sources: reddit/r/LocalLLaMA
Getting really worried about the m5 Ultra. From removing 512gb -> 256gb -> 96gb.
๐ด BeeLlama.cpp: advanced DFlash & TurboQuant with support of reasoning and vision. Qwen 3.6 27B Q5 with 200k context on 3090, 2-3x faster than baseline (peak 135 tps!) โ score 73
Sources: reddit/r/LocalLLaMA
TL;DR New llama.cpp fork! I wanted a Windows-friendly inference to run Qwen 3.6 27B Q5 on a single RTX 3090 with speculative decoding, high context without excess quantization, and vision enabled. No option did this out of the box for me without VRAM and/or tooling issues (this was before MTP PR
๐ก Notable
Model Releases
๐ก NVIDIA AI Releases Star Elastic: One Checkpoint that Contains 30B, 23B, and 12B Reasoning Models with Zero-Shot Slicing โ score 65
Sources: reddit/r/LocalLLaMA
I saw this on another sub and didn't see it posted here, it looks awesome, and can definitely be run local. I guess it was released 11 days ago, but it never hit the top of my feed (which I look at way too often), so posting it again. # This is my take on it: Think of this as like scalable video cod
๐ก Pi and Qwen3.6 27B make setting up Archlinux really easy. โ score 58
Sources: reddit/r/LocalLLaMA
Just thought I'd share this use case. I was setting up a miniPC as a home theatre with Archlinux (It's the OS I'm most familiar with). I needed to twiddle some things and am not yet familiar with wayland (I'm trying our hyprland, but normally rock i3). So, I installed pi coding agent, pointed it at
๐ก More Qwen3.6-27B MTP success but on dual Mi50s โ score 42
Sources: reddit/r/LocalLLaMA
TLDR: The hype is real! 1.5x speedup. Up to 2x speedup with tensor parallelism! After reading the PR I immediately hunted for MTP-compatible Q4_1 quants (they offer a small speedup on these compute-lacking older cards) but couldn't find any. Luckily I came across [this](https://www.reddit.com/r
Developer Tools
๐ก What is an average publication outcome for an ML PhD? [D] โ score 69
Sources: reddit/r/MachineLearning
I know publication count is not everything, and quality, contribution, advisor/lab culture, subfield, and luck all matter a lot. But to make the comparison easier, Iโm curious about the publication-count side specifically. For an ML PhD, what would you consider an average publication outcome by grad
๐ก openai/codex โ Lightweight coding agent that runs in your terminal โ score 69
Sources: github_trending
Lightweight coding agent that runs in your terminal
๐ก heygen-com/hyperframes โ Write HTML. Render video. Built for agents. โ score 67
Sources: github_trending
Write HTML. Render video. Built for agents.
๐ก hesreallyhim/awesome-claude-code โ A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic โ score 58
Sources: github_trending
A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic
๐ก rowboatlabs/rowboat โ Open-source AI coworker, with memory โ score 55
Sources: github_trending
Open-source AI coworker, with memory
Omitted 2 additional developer tools items from the main section; see raw data and source-specific sections below.
Infrastructure & Compute
๐ก sgl-project/sglang โ SGLang is a high-performance serving framework for large language models and multimodal models. โ score 58
Sources: github_trending
SGLang is a high-performance serving framework for large language models and multimodal models.
Other Signals
๐ก Running Minimax 2.7 at 100k context on strix halo โ score 50
Sources: reddit/r/LocalLLaMA
Just wanted to share because it took me a lot of tweaking to get here: llama-server -hf unsloth/MiniMax-M2.7-GGUF:UD-IQ3_XXS --temp 1.0 --top-k 40 --top-p 0.95 --host 0.0.0.0 --port 8080 -c 100000 -fa on -ngl 999 --no-context-shift -fit off --no-mmap -np 2 --kv-unified --cache-ram 0 -b 1024 -ub 1024
๐ก LLMs corrupt your documents when you delegate โ score 50
Sources: hackernews
๐ก EEML 2026 summer school [D] โ score 44
Sources: reddit/r/MachineLearning
Has anyone accepted to EEML 2026 summer school?
๐ข Incremental
Model Releases
๐ข Building a AI teacher-assistance software, Assistance needed. โ score 39
Sources: reddit/r/AIAgents
Ok, so I have multiple school teachers in my family, so I have an exposure to what problems they face (in teaching, obviously, idc about admin stuff). So I thought of building an AI worksheet generator (idea under development). Claude helped me build a beautiful backend, and through it, I discovered
๐ข Would a community-driven AI agent lab help people actually ship agents? โ score 39
Sources: reddit/r/AIAgents
Iโm validating an idea and would like honest criticism from people building or studying AI agents. A pattern I keep seeing: people test LangChain, CrewAI, AutoGen, OpenAI tools, Claude, local LLMs, n8n, MCP servers, etc., but very few actually ship a working agent into a real workflow. My hypothesis
๐ข Exactly a year ago, I started working on an MCP server I launched on reddit that became by far my most active open source project! โ score 35
Sources: reddit/r/LocalLLaMA
This isn't an advertisement, and it's very much local and open - I already don't have enough time to keep up with the existing pull requests and issues... just a fond look back on how much this space has grown and matured in the past year. Shit was the wild west back then. Nowadays I can run gemma4
๐ข Gemini API File Search is now multimodal โ score 30
Sources: hackernews
๐ข I am overwhelmed by Harnesses โ score 27
Sources: reddit/r/LocalLLaMA
What do i choose? They all have their good but then some features don't work then i end up breaking more with claude code. Is there one harness that rules them all out there for llama cpp??
Omitted 2 additional model releases items from the main section; see raw data and source-specific sections below.
Developer Tools
๐ข As now many companies have started integrating agents in their operations and still question about reliability? โ score 39
Sources: reddit/r/AIAgents
Most companies are still in their beta version and rolling out features integrated with AI to a set of customers now as they too high many reasons for this. I'm trying to figure out how the companies are going to keep track of whether the system has been reliable or not? Any teams or folks out their
๐ข LangChain vs custom wrappers, when did you realize you needed to drop the framework? โ score 39
Sources: reddit/r/AIAgents
When I first started messing around with LLM agents, langchain seemed like absolute magic. It felt like I could hook up memory, tools, and chains in five lines of code. But over the last few weeks of building something slightly more complex, itโs been driving me crazy. The abstractions are so deep t
๐ข Devs building agents... what's actually breaking for you in production? โ score 39
Sources: reddit/r/AIAgents
I've been going deep on prompt engineering as a control mechanism for agents and I'm working on something that makes certain behaviors more explicit and deterministic rather than relying on instruction following. Before I narrow down where to focus, I want to hear from people actually in the trenche
๐ข Most AI workflows drift because state slowly becomes implicit. โ score 39
Sources: reddit/r/AIAgents
Most AI workflow systems drift over time because state slowly becomes implicit. Not because the models fail, but because: * summaries mutate, * assumptions harden, * artifacts lose provenance, * and inference becomes impossible to inspect afterward. Weโve been experimenting with: * explicit continui
๐ข vellum-ai/vellum-assistant โ A personal AI assistant that evolves with you. Memory, personality, proactive reach-outs โ across macOS, Telegram, and Slack. โ score 37
Sources: github_trending
A personal AI assistant that evolves with you. Memory, personality, proactive reach-outs โ across macOS, Telegram, and Slack.
Omitted 7 additional developer tools items from the main section; see raw data and source-specific sections below.
Enterprise Adoption
๐ข Gen Z Resentment Toward AI Grows as Adoption Stagnates and Workplace Fears Mount โ score 10
Sources: hackernews
Other Signals
๐ข The gap between knowing something and actually understanding it โ AI accelerated my learning curve โ score 19
Sources: reddit/r/LocalLLaMA
I've been experimenting with setting up local LLMs lately, and here's what hit me hard: Just because it's cheap to build something doesn't mean you should. If a compatible tool already exists for your use case, use it first. Only roll your own once you've confirmed the existing option falls short. I
๐ข Anyone Trying to submit for ICML FM4LS workshop but noticed link closed Early? [D] โ score 6
Sources: reddit/r/MachineLearning
I was trying to submit to ICML FM4LS workshop but noticed that openreview is not accepting submissions any more? although the deadline listed on the website is end of day May 9th AoE. Was there any communication that
๐ข Homelab setup โ score 4
Sources: reddit/r/LocalLLaMA
Hi everyone, I've been running local models on a MacBook Pro M3 Max with 128GB RAM for a while, and I've recently been thinking about improving my setup. What would make more sense, having a ~7-8K budget? 1- Another MBP (M5 Max) with 128GB, then set up an Exo cluster with my M3 for a total of 256GB
๐ Trending Repos
| Repo | Description | Stars Today | Language |
|---|---|---|---|
| millionco/react-doctor | Your agent writes bad React. This catches it | 806 | typescript |
| lsdefine/GenericAgent | Self-evolving agent: grows skill tree from 3.3K-line seed, achieving full system control with 6x less token consumption | 538 | python |
| openai/codex | Lightweight coding agent that runs in your terminal | 383 | rust |
| heygen-com/hyperframes | Write HTML. Render video. Built for agents. | 345 | typescript |
| sgl-project/sglang | SGLang is a high-performance serving framework for large language models and multimodal models. | 153 | python |
| hesreallyhim/awesome-claude-code | A curated list of awesome skills, hooks, slash-commands, agent orchestrators, applications, and plugins for Claude Code by Anthropic | 153 | python |
| rowboatlabs/rowboat | Open-source AI coworker, with memory | 144 | typescript |
| jingyaogong/minimind | ๐ง ใๅคงๆจกๅใ2ๅฐๆถๅฎๅ จไป0่ฎญ็ป64M็ๅฐๅๆฐLLM๏ผTrain a 64M-parameter LLM from scratch in just 2h! | 112 | python |
| HKUDS/ViMax | "ViMax: Agentic Video Generation (Director, Screenwriter, Producer, and Video Generator All-in-One)" | 108 | python |
| vellum-ai/vellum-assistant | A personal AI assistant that evolves with you. Memory, personality, proactive reach-outs โ across macOS, Telegram, and Slack. | 54 | typescript |
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- datawhalechina/hello-agents โ ๐ ใไป้ถๅผๅงๆๅปบๆบ่ฝไฝใโโไป้ถๅผๅง็ๆบ่ฝไฝๅ็ไธๅฎ่ทตๆ็จ - first seen 2026-05-09
- A recent experience with ChatGPT 5.5 Pro - first seen 2026-05-09
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