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introducing matrix. the ultimate multi-agent runtime that turns your product into actual revenue and automates 99% of what it takes to run a company. probably the most different, most future-feeling agent product you've ever seen. the harness, the interface, everything is rebuilt from scratch. think of it as the... complement to codex and claude code. they write the code. matrix does literally everything else you actually need done. plug in your codex subscription and run it for free, or byok. fully free either way. this video was edited by matrix and voiced by an agent. more real cases coming soon. matrix is in beta preview right now. full launch next week. retweet + comment and we'll send invite codes to the first 200.show more

Derek Nee

13,341 subscribers

15,361 Aufrufe • vor 3 Monaten •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

37 Kommentare

Profilbild von Derek Nee

Derek Neevor 3 Monaten

try it directly: BNPHNH HAVYPX ESHQKJ L5GYEM SWFZ8E TA9HQP QUHQWP GVEQHB P8QVYD NS2B5V XN6WXS YSQCJN C74KNL 8BFT35 VGFSBX YDYRWF

Profilbild von Matrix

Matrixvor 3 Monaten

😎😎😎

Profilbild von MAMBA 🧲

MAMBA 🧲vor 3 Monaten

5SmytRuQgRYRRnAVbUVLWVxoYyZhMmKrRKpEemtxpump they made a coin to fund your project on @Pumpfun fees goes to you

Profilbild von Maimu

Maimuvor 3 Monaten

There is a solana coin supporting your project Matrix! 5SmytRuQgRYRRnAVbUVLWVxoYyZhMmKrRKpEemtxpump

Profilbild von xWhisky

xWhiskyvor 3 Monaten

This is pretty good project, are you interested in accepting donations through ur github?

Profilbild von Sil

Silvor 3 Monaten

5SmytRuQgRYRRnAVbUVLWVxoYyZhMmKrRKpEemtxpump

Profilbild von kaize

kaizevor 3 Monaten

one of the best tools I've used recently - I've already migrated my entire content infrastructure from the Claude to Matrix to be honest, during the initial setup, something went haywire, and The Matrix identified my profile based on old posts (from a year ago), so I had to tell it that those were old posts and upload links and text to

Profilbild von Hybrid 🏃🏾

Hybrid 🏃🏾vor 3 Monaten

I swear there’s a new project dropping every day with some similarity to the project. I just seen dropped the previous day. I’m overwhelmed

Profilbild von Harper

Harpervor 3 Monaten

can we donate you money trought your Github ?

Profilbild von Bruce Guai

Bruce Guaivor 3 Monaten

@matrix_build 来Matrix测试，构建第一个帮你取得影响力，获得收益的 Agent 公司。在给大家抽点测试额度，名额有限！

Profilbild von luka

lukavor 3 Monaten

code please

Profilbild von Derek Nee

Derek Neevor 3 Monaten

QZT49G try this!

Profilbild von ᕼ ᐱ ᖇ Ƨ ᕼ ᐱ

ᕼ ᐱ ᖇ Ƨ ᕼ ᐱvor 3 Monaten

is there new codes? 🥺

Profilbild von Derek Nee

Derek Neevor 3 Monaten

yes! QEGAP9

Profilbild von Husidi

Husidivor 3 Monaten

Matrix超独特，非常实用！

Profilbild von Colbert

Colbertvor 3 Monaten

@matrix_build Gm need an invite

Profilbild von Badass

Badassvor 3 Monaten

I love to try

Profilbild von MrBoring

MrBoringvor 3 Monaten

👏

Profilbild von 刺刺河豚

刺刺河豚vor 3 Monaten

8ReTVJUb5E1gS67xGYjJ3xy45P3Yrux8JqhLoBvfBAGS Someone has created a tax token for you, which will provide funding for the project if you endorse it.

Profilbild von kierbicAI

kierbicAIvor 3 Monaten

me pls thank u

Profilbild von TTTVV

TTTVVvor 3 Monaten

@matrix_build 我想要

Profilbild von Quixoa

Quixoavor 3 Monaten

The interesting part is whether the runtime makes ownership visible after the demo. Multi-agent systems get a lot more credible when teams can see which agent acted, what it touched, and where human review still sits in the loop.

Profilbild von Doctor Ponzi

Doctor Ponzivor 3 Monaten

a bankr community coin was made to support your project, all fees go to you

Profilbild von Ashique 💪

Ashique 💪vor 3 Monaten

Cool

Profilbild von MonKMind Media🖊️

MonKMind Media🖊️vor 3 Monaten

Matrix ⚛️

Profilbild von tofa

tofavor 3 Monaten

let us fundraise the growth of this no support needed! free fees to you using @pumpfun

Profilbild von Felipe Andra ➔ jurishub.app

Felipe Andra ➔ jurishub.appvor 3 Monaten

I would love to try it out!

Profilbild von lurks

lurksvor 3 Monaten

Sent ya a DM

Profilbild von Türkiye In The World

Türkiye In The Worldvor 3 Monaten

@matrix_build Cong.

Profilbild von Guoguo Lei

Guoguo Leivor 3 Monaten

is there new codes? thanks

Profilbild von Sanjeev

Sanjeevvor 3 Monaten

Exciting , and even more exciting if it would become open source

Profilbild von Ritesh Ranjan

Ritesh Ranjanvor 3 Monaten

invite code, plz

Profilbild von Hervé Dumoulin

Hervé Dumoulinvor 3 Monaten

@matrix_build I hope I might receive a code to explore your latest product achievement.

Profilbild von MISFITSッ

MISFITSッvor 3 Monaten

Gib

Profilbild von Jason

Jasonvor 3 Monaten

Love to try it

Profilbild von Husidi

Husidivor 3 Monaten

已转，希望可以获得一个邀请码，体验最新的agent

Profilbild von I_am_eth

I_am_ethvor 3 Monaten

id like one please. 🙏

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This is literally the easiest way to build an AI agent. Zero code. You only need to run a couple of commands. (I've said this before, but Google ADK is my favorite way to build code-first agents.) Here is what you need to do: 1. Open your terminal and create an empty folder 2. Run `uv init` inside the folder (if you don't have uv installed, you are really missing out!) 3. Install the google-adk library using the following command: `uv add google-adk`. 4. At this point, you can use the ask to create your agent with a single command: `uv run adk create --type=config my_agent`. This will ask you a couple of questions, including your GEMINI_API_KEY (you can create one online). 5. The command above will create a my_agent/root_agent.yaml file. Open it and add the following two lines at the end of the file so your agent can use Google to search for stuff: tools: - name: google_search 6. You have everything you need now. Run the adk web interface and start playing with your agent: `uv run adk web` That's it! Literally zero code. The agent works off the YAML configuration file.

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140,922 Aufrufe • vor 10 Monaten

Another insane Jev use case! Jev makes it incredibly cheap to evaluate and classify agent runs at scale. And finally, someone open-sourced a self-improving memory layer that can put that capability to work across agent harnesses. It turns your agent sessions into a compounding knowledge layer, where every successful run can make future agents smarter across: - Codex - Claude Code - Cursor - OpenCode and 20+ more Beacon by Asymptote Labs continuously builds a shared history across your agent harnesses and uses Jev to identify the runs worth learning from. It then turns the best workflows, corrections, and debugging patterns into reusable skills. GitHub repo: (don’t forget to star it ⭐) Most agent runs are messy. They contain exploration, failed commands, dead ends, and one-off fixes that should never become permanent memory. So Beacon preserves the full session history, while Jev helps decide what should be promoted, reviewed, or discarded. The recording below shows this in action. Beacon found 579 sessions across 5 coding-agent harnesses and normalized them into one consistent history. From there, Jev surfaces the lessons worth keeping and makes them available across your agent stack. - A pattern learned in Cursor can carry into OpenCode. - A lesson from Claude Code can improve the next Codex run. Every successful run adds to the shared knowledge layer, making future agents smarter. If you want to dive deeper into Jev, I also wrote a breakdown of how it works. The article is quoted below.

Another insane Jev use case! Jev makes it incredibly cheap to evaluate and classify agent runs at scale. And finally, someone open-sourced a self-improving memory layer that can put that capability to work across agent harnesses. It turns your agent sessions into a compounding knowledge layer, where every successful run can make future agents smarter across: - Codex - Claude Code - Cursor - OpenCode and 20+ more Beacon by Asymptote Labs continuously builds a shared history across your agent harnesses and uses Jev to identify the runs worth learning from. It then turns the best workflows, corrections, and debugging patterns into reusable skills. GitHub repo: (don’t forget to star it ⭐) Most agent runs are messy. They contain exploration, failed commands, dead ends, and one-off fixes that should never become permanent memory. So Beacon preserves the full session history, while Jev helps decide what should be promoted, reviewed, or discarded. The recording below shows this in action. Beacon found 579 sessions across 5 coding-agent harnesses and normalized them into one consistent history. From there, Jev surfaces the lessons worth keeping and makes them available across your agent stack. - A pattern learned in Cursor can carry into OpenCode. - A lesson from Claude Code can improve the next Codex run. Every successful run adds to the shared knowledge layer, making future agents smarter. If you want to dive deeper into Jev, I also wrote a breakdown of how it works. The article is quoted below.

Akshay 🚀

118,955 Aufrufe • vor 7 Tagen

My new favorite way to build with agents is to organize them into a factory. This is the 4-step workflow: 1) Station. - A custom order gets its own station, so the order does not interfere with the rest of production. - In software, this station is a branch or a work tree. 2) Assembly line. - The agent writes code, changes files, and adds structure. 3) Quality control. - Does it turn on? - Does it fit? - Does it break under pressure? - In software, you run tests, open a preview, and read the logs and screenshots. 4) Shipping. - The product goes out the door. - You merge, deploy the PR, and write release notes. If a product fails quality control, you send feedback to the product team. Then you do the loop again. Write each step of your agent workflow as a factory job.

My new favorite way to build with agents is to organize them into a factory. This is the 4-step workflow: 1) Station. - A custom order gets its own station, so the order does not interfere with the rest of production. - In software, this station is a branch or a work tree. 2) Assembly line. - The agent writes code, changes files, and adds structure. 3) Quality control. - Does it turn on? - Does it fit? - Does it break under pressure? - In software, you run tests, open a preview, and read the logs and screenshots. 4) Shipping. - The product goes out the door. - You merge, deploy the PR, and write release notes. If a product fails quality control, you send feedback to the product team. Then you do the loop again. Write each step of your agent workflow as a factory job.

The Startup Ideas Podcast (SIP) 🧃

13,017 Aufrufe • vor 14 Tagen

New open source project: Easel, a macOS workspace for AI-assisted product design and frontend iteration powered by the Codex SDK. Think of it as "Claude Design for Codex." It brings together a local project library, design-system setup, Codex chat, and a live web preview with a point-and-click inspector. Set up your design system however you like. Import one from Figma , bring your own, or have the agent generate it as a design.md. Then use it to build prototypes and slide decks. Codex-first, with Claude and other AI providers and local models planned for future releases. OpenAI Developers

New open source project: Easel, a macOS workspace for AI-assisted product design and frontend iteration powered by the Codex SDK. Think of it as "Claude Design for Codex." It brings together a local project library, design-system setup, Codex chat, and a live web preview with a point-and-click inspector. Set up your design system however you like. Import one from Figma , bring your own, or have the agent generate it as a design.md. Then use it to build prototypes and slide decks. Codex-first, with Claude and other AI providers and local models planned for future releases. OpenAI Developers

James Rochabrun

61,608 Aufrufe • vor 3 Monaten