Video yükleniyor...

Video Yüklenemedi

Bu video yüklenirken bir sorun oluştu. Bu geçici bir ağ sorunundan kaynaklanıyor olabilir veya video kullanılamıyor olabilir.

Ana Sayfaya Dön

I tried replicating fully agentic coding on my laptop and I'm impressed! My setup - Qwen 27bn (4bit quant) - Pi coding agent - CCO sandboxing for yolo mode My Mac M3 has 36GB ram. It's surreal to see a local model read prompt, follow it flawlessly and then... show more

Paras Chopra

235,690 subscribers

106,032 görüntüleme • 3 ay önce •via X (Twitter)

Bilim & Teknoloji

Anya Rossi• Live Now

Private livecam show

0 Yorum

Yorum bulunmuyor

Orijinal gönderinin yorumları burada görünecek

Benzer Videolar

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

i tested a fully local ai coding setup: gemma4 from Google DeepMind running through LM Studio, paired with pi which is a minimal open source coding harness this is part 1 of a two part series. here we cover the why and the complete hands-on setup 0:00 - Running a coding agent fully local 0:47 - Why Pi as the coding agent harness 1:39 - Why Gemma 4 and which variant to pick 2:44 - Architecture: Pi, LM Studio and Gemma 4 3:45 - LM Studio setup and model download 5:01 - Starting the local server 5:19 - API sanity check with curl 6:08 - Installing the Pi coding agent 6:20 - Configuring models.json for local models 8:20 - First run: selecting the model in Pi 8:58 - Fixing the context length error 10:16 - Testing the working setup 10:50 - What is coming in Part 2

Nidhi Singh

16,289 görüntüleme • 1 ay önce

i gave a 9B model an agentic OS and told it to build Octopus Invaders from scratch. Qwen 3.5 9B running through Hermes Agent with full tool access on a single 3060 12GB. browser, file system, code execution, terminal. it reads the prompt, plans the architecture, writes every file, and serves the game. one prompt, zero steering, 11 minutes. i've been going back and forth with this model for days now. text, code, reasoning. it handles small chats, batching, bash scripting. at 9B it's fast enough to feel interactive and genuinely useful for local workflows where you'd normally reach for an API. but this is the real test. can it architect and build a full game autonomously without a single correction? it's coding right now. results coming next.

i gave a 9B model an agentic OS and told it to build Octopus Invaders from scratch. Qwen 3.5 9B running through Hermes Agent with full tool access on a single 3060 12GB. browser, file system, code execution, terminal. it reads the prompt, plans the architecture, writes every file, and serves the game. one prompt, zero steering, 11 minutes. i've been going back and forth with this model for days now. text, code, reasoning. it handles small chats, batching, bash scripting. at 9B it's fast enough to feel interactive and genuinely useful for local workflows where you'd normally reach for an API. but this is the real test. can it architect and build a full game autonomously without a single correction? it's coding right now. results coming next.

Sudo su

65,570 görüntüleme • 4 ay önce

Last week I spent $20,000 on Mac Studios so I could run OpenClaw locally Fully powered by local AI models running 24/7 Now my agent: • Is doing tasks 24/7/365 • Doesn't cost any tokens • Is fully private In this video I cover how it works and how you can do the same thing:

Last week I spent $20,000 on Mac Studios so I could run OpenClaw locally Fully powered by local AI models running 24/7 Now my agent: • Is doing tasks 24/7/365 • Doesn't cost any tokens • Is fully private In this video I cover how it works and how you can do the same thing:

Alex Finn

573,500 görüntüleme • 5 ay önce

Linux phone navigation is coming together. The future is your phone being fully agentic and being able to modify itself and write software for you on the fly. Ram is very limited on this device but I will see how a fully local model will perform, something sub 1.5B.

Linux phone navigation is coming together. The future is your phone being fully agentic and being able to modify itself and write software for you on the fly. Ram is very limited on this device but I will see how a fully local model will perform, something sub 1.5B.

vlad

127,575 görüntüleme • 12 gün önce

🚨 This Chinese model is INSANE !! I just tested Tencent's Hunyuan AI model to build a professional landing page & the output is mind blowing 🤯 Here's my exact prompt: "Create a modern landing page for a crypto related product with beautiful hero section, 3d elements, pricing table, and a whitelist form" What it generated: → Clean, responsive front-end code → Complex UI components with smooth interactions → Built-in debugging (it fixed its own errors) → Production-ready in minutes This 295B parameter model has 2 insane agents: → Coding Agent (handles the entire front-end) → Working Agent (task planning & multi-tool workflows) It also has a context window of 256k tokens !! Watch the video to see the full build 🔥 Try it: Tencent Hy

🚨 This Chinese model is INSANE !! I just tested Tencent's Hunyuan AI model to build a professional landing page & the output is mind blowing 🤯 Here's my exact prompt: "Create a modern landing page for a crypto related product with beautiful hero section, 3d elements, pricing table, and a whitelist form" What it generated: → Clean, responsive front-end code → Complex UI components with smooth interactions → Built-in debugging (it fixed its own errors) → Production-ready in minutes This 295B parameter model has 2 insane agents: → Coding Agent (handles the entire front-end) → Working Agent (task planning & multi-tool workflows) It also has a context window of 256k tokens !! Watch the video to see the full build 🔥 Try it: Tencent Hy

AGAFE

110,528 görüntüleme • 24 gün önce

Qwen 3.6 35B running at over 100 tokens per second on my $5,399 MacBook Pro M5 Max. This is the best local AI model I have ever run. 128GB of unified memory. No cloud. No API costs. No rate limits. Just raw local inference at speeds I didn't think were possible on a laptop. This model is more intelligent than GPT 5 on benchmarks. Running locally. On a MacBook. For free after the hardware cost. I said local AI would never compete with frontier. I'm starting to rethink that. The gap is closing faster than anyone expected.

Qwen 3.6 35B running at over 100 tokens per second on my $5,399 MacBook Pro M5 Max. This is the best local AI model I have ever run. 128GB of unified memory. No cloud. No API costs. No rate limits. Just raw local inference at speeds I didn't think were possible on a laptop. This model is more intelligent than GPT 5 on benchmarks. Running locally. On a MacBook. For free after the hardware cost. I said local AI would never compete with frontier. I'm starting to rethink that. The gap is closing faster than anyone expected.

BridgeMind

62,800 görüntüleme • 2 ay önce

I took delivery of my new Tesla Model Y on Thursday. Today, I tried Full Self-Driving (FSD) and it FLAWLESSLY drove a 32 minute trip from my home to my kids' school. I am absolutely BLOWN AWAY. How long has this been possible and why isn't everyone talking about it?!

I took delivery of my new Tesla Model Y on Thursday. Today, I tried Full Self-Driving (FSD) and it FLAWLESSLY drove a 32 minute trip from my home to my kids' school. I am absolutely BLOWN AWAY. How long has this been possible and why isn't everyone talking about it?!

Matt Van Swol

2,895,307 görüntüleme • 1 yıl önce

I'm blown away. Ornith-1.0 35b is the best local model I've ever run that doesn't require 200GB+ of RAM Incredible at coding According to my tests it's both smarter and faster than Qwen 3.6 Plus it runs like a dream on a DGX Spark Here's how I'm using it: I have it running every hour and looping through different parts of my Henry Intelligent Machines codebase It looks for security vulnerabilities Any vulnerabilities it finds, it writes a report with the fix Then once a day another loop I have running in Codex reads the report with all the security bugs and verifies, then fixes I also have it once a day going through a reviewing all my open PRs Local models running on loops 24/7 is the future. I promise you What's becoming possible today with local models is truly mind blowing

I'm blown away. Ornith-1.0 35b is the best local model I've ever run that doesn't require 200GB+ of RAM Incredible at coding According to my tests it's both smarter and faster than Qwen 3.6 Plus it runs like a dream on a DGX Spark Here's how I'm using it: I have it running every hour and looping through different parts of my Henry Intelligent Machines codebase It looks for security vulnerabilities Any vulnerabilities it finds, it writes a report with the fix Then once a day another loop I have running in Codex reads the report with all the security bugs and verifies, then fixes I also have it once a day going through a reviewing all my open PRs Local models running on loops 24/7 is the future. I promise you What's becoming possible today with local models is truly mind blowing

Alex Finn

314,695 görüntüleme • 1 ay önce

So what's your feeling on DeepSeek V4 Flash 0731? Surely great model for Local AI and coding but clearly not at GLM 5.2 or Kimi K3 level. Obviously, because it's a different category. For Frogger I tried 3 times using omp, but I always get a game too complex to play or with small issues here and there. I've used the mxfp4 version. But it worked great with web search, html and CSS issues with custom plugins on TMRNL X with Hermes Agent.

So what's your feeling on DeepSeek V4 Flash 0731? Surely great model for Local AI and coding but clearly not at GLM 5.2 or Kimi K3 level. Obviously, because it's a different category. For Frogger I tried 3 times using omp, but I always get a game too complex to play or with small issues here and there. I've used the mxfp4 version. But it worked great with web search, html and CSS issues with custom plugins on TMRNL X with Hermes Agent.

Ivan Fioravanti ᯅ

41,694 görüntüleme • 2 gün önce

HERMES AGENT + QWEN 3.6 IS CURRENTLY THE STRONGEST LOCAL SETUP MOST PEOPLE CAN RUN. Even if frontier models stopped improving tomorrow, this stack would still cover the majority of real work. Qwen 3.6 (72B and 235B) is officially supported in Hermes and brings: → Strong coding and complex refactoring → Reliable tool calling and multi-step execution → Excellent long context (128k–1M tokens) → Good structured reasoning with /goal workflows → Solid memory and session continuity Paired with Hermes memory, skills, Kanban, cron and tools — you get a fully private, self-improving agent that codes, automates and runs 24/7 without sending data anywhere. You don’t need the latest closed model to build something powerful. This is one of the strongest fully local stacks available right now — and it runs on real hardware.

HERMES AGENT + QWEN 3.6 IS CURRENTLY THE STRONGEST LOCAL SETUP MOST PEOPLE CAN RUN. Even if frontier models stopped improving tomorrow, this stack would still cover the majority of real work. Qwen 3.6 (72B and 235B) is officially supported in Hermes and brings: → Strong coding and complex refactoring → Reliable tool calling and multi-step execution → Excellent long context (128k–1M tokens) → Good structured reasoning with /goal workflows → Solid memory and session continuity Paired with Hermes memory, skills, Kanban, cron and tools — you get a fully private, self-improving agent that codes, automates and runs 24/7 without sending data anywhere. You don’t need the latest closed model to build something powerful. This is one of the strongest fully local stacks available right now — and it runs on real hardware.

YanXbt

53,423 görüntüleme • 1 ay önce

I spent today turning a blank Hermes install into a sovereign local agent on my RTX 5090. always-on, reachable over telegram, fully local. here's everything it can do. it runs Qwen3.6-27B on the 5090 and answers from my phone over telegram. ~~~ I first made it faster. switched to the MTP build for self-speculative decoding: 62 > 115 tokens/sec. ~~~ it now benchmarks models on command. I ask it to speed-test a gguf and it stops its own model server to free the gpu, runs llama-bench, renders a card, sends it to my phone, then restarts itself. it's never left offline. ~~~ it also knows me very well. I pointed it to my private HF repo where I store all my AI traces since I started using it. I created a local markdown memory vault, seeded from my own history, with semantic search over it. ~~~ the whole stack stays home: weights on disk, inference on the 5090, the agent in my pocket. here is the video it created to showcase everything it has now.

I spent today turning a blank Hermes install into a sovereign local agent on my RTX 5090. always-on, reachable over telegram, fully local. here's everything it can do. it runs Qwen3.6-27B on the 5090 and answers from my phone over telegram. ~ I first made it faster. switched to the MTP build for self-speculative decoding: 62 > 115 tokens/sec. ~ it now benchmarks models on command. I ask it to speed-test a gguf and it stops its own model server to free the gpu, runs llama-bench, renders a card, sends it to my phone, then restarts itself. it's never left offline. ~ it also knows me very well. I pointed it to my private HF repo where I store all my AI traces since I started using it. I created a local markdown memory vault, seeded from my own history, with semantic search over it. ~ the whole stack stays home: weights on disk, inference on the 5090, the agent in my pocket. here is the video it created to showcase everything it has now.

witcheer

15,041 görüntüleme • 2 ay önce

Let's be honest Claude Code was not working good with local LLMs. So, I Tried using OpenCode with LM Studio using Qwen 3.5 9B model on my RTX 5080 GPU. It's very usable and much faster than Claude Code. I'm actually planning to use this setup to build an entire vibe coded SaaS

Let's be honest Claude Code was not working good with local LLMs. So, I Tried using OpenCode with LM Studio using Qwen 3.5 9B model on my RTX 5080 GPU. It's very usable and much faster than Claude Code. I'm actually planning to use this setup to build an entire vibe coded SaaS

Tushar Verma

137,536 görüntüleme • 4 ay önce

Nothing beats open-source! We now have a fully open-source coding agent that can compete with any proprietary solution out there: • 500+ available models • It doesn't train on your code • It doesn't charge a penny for tokens • It's open. You can change if you want. Kilo Code is the #1 app on OpenRouter right now, and the community is releasing new features on GitHub at rocket speed (about 20 releases in the last 30 days). I installed it in Visual Studio Code, but you can install it in pretty much any IDE. I need to spend more time with it, but here is a very interesting design choice: Most coding agents support two modes: an "agentic" mode for writing code and an "ask" mode for talking to the model without making any changes. Kilo Code supports 5 different modes: 1. Architect mode - Research, design, and planning 2. Debug mode - Problem solving and troubleshooting 3. Code mode - To write code. 4. Ask mode - To talk to the model. 5. Orchestrator mode - Combine every agent to solve problems. On paper, I really like this. I'll need more time to try out the specialized agents and see whether niching becomes an advantage. Here is the link to the website: Thanks to the Kilo for partnering with me on this post.

Nothing beats open-source! We now have a fully open-source coding agent that can compete with any proprietary solution out there: • 500+ available models • It doesn't train on your code • It doesn't charge a penny for tokens • It's open. You can change if you want. Kilo Code is the #1 app on OpenRouter right now, and the community is releasing new features on GitHub at rocket speed (about 20 releases in the last 30 days). I installed it in Visual Studio Code, but you can install it in pretty much any IDE. I need to spend more time with it, but here is a very interesting design choice: Most coding agents support two modes: an "agentic" mode for writing code and an "ask" mode for talking to the model without making any changes. Kilo Code supports 5 different modes: 1. Architect mode - Research, design, and planning 2. Debug mode - Problem solving and troubleshooting 3. Code mode - To write code. 4. Ask mode - To talk to the model. 5. Orchestrator mode - Combine every agent to solve problems. On paper, I really like this. I'll need more time to try out the specialized agents and see whether niching becomes an advantage. Here is the link to the website: Thanks to the Kilo for partnering with me on this post.

Santiago

73,062 görüntüleme • 8 ay önce

Redes Sociales Twitter/X: Facebook: Telegram: Reddit: Discord: I'm on my way Can't settle down Stuck in ways of being an ass And I got a lot of nerve that I'm ready to pass I'm on my way Can't settle down Stuck in ways of sadistic joy My talent only goes as far as to annoy I'm on my way This is my main offender This is what I've got and it Got me saying Why me? I'm on my way I get around Not all too sure about what I do Feel I've got to stop a second just to think it through And so I stop I'm on my way Yeah, I get around Thought it all over and now I spit it out When I spit, I spit on those that I care less about I'm on my way This is my main offender This is what I've got and it Got me saying Why me? I'm on my way

Redes Sociales Twitter/X: Facebook: Telegram: Reddit: Discord: I'm on my way Can't settle down Stuck in ways of being an ass And I got a lot of nerve that I'm ready to pass I'm on my way Can't settle down Stuck in ways of sadistic joy My talent only goes as far as to annoy I'm on my way This is my main offender This is what I've got and it Got me saying Why me? I'm on my way I get around Not all too sure about what I do Feel I've got to stop a second just to think it through And so I stop I'm on my way Yeah, I get around Thought it all over and now I spit it out When I spit, I spit on those that I care less about I'm on my way This is my main offender This is what I've got and it Got me saying Why me? I'm on my way

HSP Chicas Azules

70,951 görüntüleme • 5 ay önce

My favorite way of interacting with Claude Code is to have it generate static HTML files as outputs (reports, explorations, code structure, mockups etc.) I wanted to iterate on the file by commenting in browser and having Claude update the output live. So, I built this Claude Skill👇 How it works: - Install Claude Code skill (ask it to clone repo) - Build an HTML page for anything (e.g. research coding agents and generate HTML report) - Ask it to make the page interactive That's it. CC will launch a localhost server and allow you to then leave comments on the page itself and once it updates, will give you a tour of changes. It's like Google Docs kind of comments/iteration but for HTML pages.

My favorite way of interacting with Claude Code is to have it generate static HTML files as outputs (reports, explorations, code structure, mockups etc.) I wanted to iterate on the file by commenting in browser and having Claude update the output live. So, I built this Claude Skill👇 How it works: - Install Claude Code skill (ask it to clone repo) - Build an HTML page for anything (e.g. research coding agents and generate HTML report) - Ask it to make the page interactive That's it. CC will launch a localhost server and allow you to then leave comments on the page itself and once it updates, will give you a tour of changes. It's like Google Docs kind of comments/iteration but for HTML pages.

Paras Chopra

215,307 görüntüleme • 2 ay önce

wow i wanted to see what all this cursor hype was about downloaded cursor this morning a few hours later I have a fully functional chrome extension!! it reads the tweet on the screen and turns it into a content template using claude and one of my prompts i didn't write a single line of code i have almost zero coding experience, basically asked the chat to explain and write everything for me this changes everything

wow i wanted to see what all this cursor hype was about downloaded cursor this morning a few hours later I have a fully functional chrome extension!! it reads the tweet on the screen and turns it into a content template using claude and one of my prompts i didn't write a single line of code i have almost zero coding experience, basically asked the chat to explain and write everything for me this changes everything

Moritz Kremb

90,528 görüntüleme • 1 yıl önce

Ok, Remotion is INSANE. I installed it on my OpenClaw this morning. I gave my logo, my landing page and the 14 steps I needed for that video. After 5 iterations, I got this 👇 Well... almost. I wasn't happy about the voiceover. So I sent the script that Marc (my OpenClaw agent) created to ElevenLabs (free plan). Then used Capcut to add the music + the voiceover from ElevenLabs. And I got this video. I am sure it's just a question of time until it becomes perfect (or a lack of skills on my side). But this will go straight to my landing page and I'll save $500 on a video editor.

Florian Darroman

152,536 görüntüleme • 4 ay önce

This is how you get 15x fable 5 usage. Fable -> Composer 2.5 reading Fable -> GPT 5.5 execution I built CNVS to make agent orchestration dead simple and insanely visual. You can watch fable 5 delegate work to cursor, codex, open code, all your agents. using your exsisting ai subs no api pricing. The canvas is fully voice controlled locally with nvidia parakeet for fast and free, or gpt realtime 2 for a fully conversational jarvis experience. The built in mcp and cli means agentic control is bidirectional they can prompt and spawn each other and read agent states. but there is more I built it from the ground up in swift for native performance on mac os. My old 16gb m1 mbp can easily spin up and control eight agents across multiple canvasses. The hermes integration + remote canvases allow you to run agents fully in the cloud on your VPS think google docs of vibe coding. You can literally turn off your mac and they keep working, open cnvs back up and pick up where you left off. I built a cross agent memory system based on 2026 research so all your agents feel like one brain. its SIMPLE and on demand. This eliminates context bloat, and the research supports a massive uptick in cross agent performance. There is soo much more. PS - I am a father building this project 100% solo in my basement on live stream everyday, my goal is to push vibe coding to the next level PPS - CNVS is a lifetime license becuase you DO NOT need another subscription in your life.

This is how you get 15x fable 5 usage. Fable -> Composer 2.5 reading Fable -> GPT 5.5 execution I built CNVS to make agent orchestration dead simple and insanely visual. You can watch fable 5 delegate work to cursor, codex, open code, all your agents. using your exsisting ai subs no api pricing. The canvas is fully voice controlled locally with nvidia parakeet for fast and free, or gpt realtime 2 for a fully conversational jarvis experience. The built in mcp and cli means agentic control is bidirectional they can prompt and spawn each other and read agent states. but there is more I built it from the ground up in swift for native performance on mac os. My old 16gb m1 mbp can easily spin up and control eight agents across multiple canvasses. The hermes integration + remote canvases allow you to run agents fully in the cloud on your VPS think google docs of vibe coding. You can literally turn off your mac and they keep working, open cnvs back up and pick up where you left off. I built a cross agent memory system based on 2026 research so all your agents feel like one brain. its SIMPLE and on demand. This eliminates context bloat, and the research supports a massive uptick in cross agent performance. There is soo much more. PS - I am a father building this project 100% solo in my basement on live stream everyday, my goal is to push vibe coding to the next level PPS - CNVS is a lifetime license becuase you DO NOT need another subscription in your life.

Max Blade

29,504 görüntüleme • 1 ay önce

I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that I reverse-engineered it for my agent orchestrator. And then I built a monitoring dashboard (as an HTML artifact) to track tasks, metrics, and reports. I can now use and monitor dynamic workflows in my agent orchestrator with coding agents like Claude Code, Codex, Pi, and even my own custom-built DAIR.AI agent. This is clearly the future of working with agents to accomplish complex, long-running tasks. Some use cases I'm having success with: - Branching deep research tasks (with verification) - Parallel deep research tasks - Session mining of all my agent sessions - Bug hunting - Triaging - Fact-checking - LLM councils - AI simulations - Data synthesis - Evals generation ... and many others Dynamic workflows, like agent skills, feel like an important primitive to not only get the most out of agents but also incorporate dynamic behaviors and important components like cooperation and verification. There is so much exploration ground here. The exciting part is that this is not limited to coding tasks; it extends to business use cases and many other technical domains like science and research.

I am hooked on Dynamic Workflows! The idea of generating harnesses on the fly is so compelling that I reverse-engineered it for my agent orchestrator. And then I built a monitoring dashboard (as an HTML artifact) to track tasks, metrics, and reports. I can now use and monitor dynamic workflows in my agent orchestrator with coding agents like Claude Code, Codex, Pi, and even my own custom-built DAIR.AI agent. This is clearly the future of working with agents to accomplish complex, long-running tasks. Some use cases I'm having success with: - Branching deep research tasks (with verification) - Parallel deep research tasks - Session mining of all my agent sessions - Bug hunting - Triaging - Fact-checking - LLM councils - AI simulations - Data synthesis - Evals generation ... and many others Dynamic workflows, like agent skills, feel like an important primitive to not only get the most out of agents but also incorporate dynamic behaviors and important components like cooperation and verification. There is so much exploration ground here. The exciting part is that this is not limited to coding tasks; it extends to business use cases and many other technical domains like science and research.

elvis

103,312 görüntüleme • 2 ay önce

I'm extremely excited for this announcement so I decided to build a little explanation page for x402 on Cardano. Cardanos core architecture is extremely strong for x402 with the eUTXO model. Combine this with Leios, Hydra and Masumi and we have a killer stack. My ambition is definitely to make Cardano the nr. 1 Agent-To-Agent chain in the world.

I'm extremely excited for this announcement so I decided to build a little explanation page for x402 on Cardano. Cardanos core architecture is extremely strong for x402 with the eUTXO model. Combine this with Leios, Hydra and Masumi and we have a killer stack. My ambition is definitely to make Cardano the nr. 1 Agent-To-Agent chain in the world.

Patrick Tobler

17,459 görüntüleme • 20 gün önce