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Enterprises today are running single-player AI in a multiplayer business. One engineer plus one IDE plus one agent ships lines of code faster. It does not ship coordinated software. Two desks over, another engineer's agent is shipping a change that contradicts last quarter's architecture decision. Neither agent knows. Compliance... assembles the audit trail from screenshots after the fact. We built Software Factory to turn that into a team. Requirements captures the business intent in plain English. Blueprints maps the architecture as it actually exists. Work Orders translates that into structured tasks agents execute through MCP in Cursor, VS Code, or Claude Code. Tests validates the deployed code against the Requirement that started it. The Knowledge Graph wires it all together. Your engineers conduct the agents. The agents share state. The audit trail is part of the build, not a quarterly forensics exercise. EY's deployment: +70% productivity, 95%+ automated test coverage, months of roadmap compressed to days.show more

8090

10,246 subscribers

75,406 views • 4 months ago •via X (Twitter)

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15 Comments

Winston Fonseca4 months ago

I think 8090 Enterprise sounds awesome...but, most small companies cannot afford a $1MM starting price. Do you have a similar service for small companies that cannot write and support code like y'all?

PsudoMike 🇨🇦4 months ago

Single player AI is exactly the framing missing in most enterprise rollouts. Shipping coordinated software needs shared context across teams. The next interesting product is the one that lets agents see what other agents are doing across a company.

80904 months ago

We agree.

Sid Wahi4 months ago

chamath has just rebuilt cursor

John-Daniel Trask4 months ago

Exactly why we build @chamath. Not about coding, but the rest of the business operations. Designed it for making my @raygunio business more AI led. First thing on my notepad in 2023: current AI is all in single player mode, but business is a multiplayer team sport. Everyone in one place, all models, multiple agents, etc. Makes 1:1 AI use feel primitive.

Cyberzk⚡🐸💎4 months ago

Outstanding! Newsroom sources speaking out.

Lukas Andersson4 months ago

Multiplayer comes frome shared state in realtime between humans and agents and declaration of intent, no?

Cyberzk⚡🐸💎4 months ago

Mind-blowing! Emergency responders training for scenarios.

Pradeep Jena4 months ago

@chamath Hey Chamath, I emailed you today . Please let me know what you think!

Prithvi Jadwani | AI SEO | GEO | REDDIT SEO | GMB4 months ago

That's chaos, not a multiplayer business. Compliance has always dealt with that fallout. Software Factory is just automating the cleanup.

gwei intern4 months ago

the missing layer is multiplayer between agents, not just human to agent

🪂4 months ago

@melahjoa Yall be worried about ai bish humans need to be able function to even use it

Sam Z Liu4 months ago

logs are all you need!

Sam - phoenixwild29.sol4 months ago

💯

Subhankar Ghosh4 months ago

is helping enterprises to make the workflows faster, cheaper, better. Happy to connect and talk.

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8090

102,280 views • 4 months ago

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MTS

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18,089 views • 3 days ago

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70,287 views • 26 days ago

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305,609 views • 8 months ago

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42,152 views • 1 month ago

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Nikos

19,883 views • 1 month ago

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Rohan Paul

13,208 views • 7 months ago

Coding agents waste a lot of tokens just figuring out how a site is structured before they can touch it. Map it once instead. Agentmap crawls any site and turns it into a structured map, pages, flows, and the data on each, that any agent loads in one shot. claude code, cursor, a browser agent, all of them skip the blind exploration and go straight to the task. Open source, powered by hyperbrowser ↓

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Hyperbrowser

15,640 views • 2 months ago

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282,005 views • 25 days ago

Cursor pays engineers $1,100,000 a year to run teams of AI agents that ship code while they sleep. [The CEO of Cursor explained in 9 minutes how they ship at 100x speed using team of agents] ↓ Save this before everyone copies the playbook 1. Engineers no longer babysit one assistant. They manage dozens of agent colleagues working in parallel, each on its own remote machine 2. Validation contract before code, not after. Humans only at scoping and review. 3. The agent team handles the full loop : planning, coding, testing, shipping PRs with each agent specialised for a role. Watch the guide. Then read the guide below by Khairallah AL-Awady

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Avid

638,269 views • 4 months ago

SpaceXAI engineer Lauren Tan: "I'm running 20+ GrokBot agents with /loop and /goal inside pstack My bots ship code while I sleep At SpaceXAI, 85% of engineers are already running 10+ GrokBot agents as a team One Chief of Staff agent knows every other bot and manages the entire system" GrokBot → /loop → /goal → Chief of Staff → Agent Teams In a 1-hour workshop, Lauren shows how to build a team of GrokBot agents from scratch Research → Code → Review → Ship Worth more than most $1000 agent engineering courses Bookmark and watch it today Then read the full article on building a GrokBot agent team from scratch

SpaceXAI engineer Lauren Tan: "I'm running 20+ GrokBot agents with /loop and /goal inside pstack My bots ship code while I sleep At SpaceXAI, 85% of engineers are already running 10+ GrokBot agents as a team One Chief of Staff agent knows every other bot and manages the entire system" GrokBot → /loop → /goal → Chief of Staff → Agent Teams In a 1-hour workshop, Lauren shows how to build a team of GrokBot agents from scratch Research → Code → Review → Ship Worth more than most $1000 agent engineering courses Bookmark and watch it today Then read the full article on building a GrokBot agent team from scratch

kaori

100,589 views • 29 days ago

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Lunar

403,447 views • 1 month ago

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.

Dario Amodei just told software engineers exactly how long they have. Six to twelve months. Amodei: “I have engineers within Anthropic who say I don’t write any code anymore. I just let the model write the code, I edit it, I do the things around it.” The people building the most powerful AI in history have already stopped writing code. That is not a forecast. That is the current working condition inside the lab closest to the frontier. Amodei: “We might be six to 12 months away from when the model is doing most, maybe all, of what SWEs do end-to-end.” The tech industry spent a decade making software engineers its highest-paid, most protected class. That era has a last day now. When a model can execute an entire software build end-to-end, the ability to write syntax stops being a skill. It becomes a credential for a job that no longer exists. Amodei: “And then it’s a question of how fast does that loop close.” That is the sentence everyone skipped. The code was never the hard part. The hard part was everything around it. The model just learned everything around it. Writing the code is already nearly gone. Testing is next. Deployment is next. When all three collapse into a single autonomous execution loop, the machine no longer needs a human in the chain at all. The corporation or sovereign state that closes that loop first does not gain a competitive advantage. It gains a category of speed that biological engineers cannot match, track, or reverse. That is not disruption. That is replacement at a systems level. Amodei is not describing a future disruption. He is describing the current state of his own building. The loop is already closing. The only question is whether you are inside it or outside it when it seals.

Dustin

318,750 views • 6 months ago

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

This is one of the coolest open-source AI agent projects I've seen in a while: 'Understand Anything' It's a plugin for Claude Code, Codex, OpenCode etc. that analyzes your codebase and turns it into a knowledge base that you can interact with. It explains the codebase to you, rather than showing you the structure. It seems like it's designed for code but I opened my Obsidian vault of podcast highlights in Claude Code, then ran /understand. The result is a knowledge graph that I can search of highlights from 888 podcast episodes and 144K lines of markdown text.

Dan McAteer

174,887 views • 3 months ago

one agent → a loop → a graph → a system that throttles itself Google just put the whole ladder in one free course. most people never leave the first rung. 2 hours 4 minutes, taught by two Google Cloud engineers. no signup, no paywall. 17:55 - build your first agent 39:55 - loop engineering: iterate, check, break 1:13:25 - graph engineering 1:35:27 - agents that throttle themselves 1:56:19 - the full graph for multi-agent systems the fourth one is the step nobody talks about. an agent that cannot throttle itself is not autonomous, it is just unattended. everyone builds one agent and calls it done. this is the version where the agents wire themselves into a graph and decide their own rate. and the thing that decides when one of them is allowed to stop is not in the course. that part you build yourself. bookmark and watch it today, then read the eval setup below

one agent → a loop → a graph → a system that throttles itself Google just put the whole ladder in one free course. most people never leave the first rung. 2 hours 4 minutes, taught by two Google Cloud engineers. no signup, no paywall. 17:55 - build your first agent 39:55 - loop engineering: iterate, check, break 1:13:25 - graph engineering 1:35:27 - agents that throttle themselves 1:56:19 - the full graph for multi-agent systems the fourth one is the step nobody talks about. an agent that cannot throttle itself is not autonomous, it is just unattended. everyone builds one agent and calls it done. this is the version where the agents wire themselves into a graph and decide their own rate. and the thing that decides when one of them is allowed to stop is not in the course. that part you build yourself. bookmark and watch it today, then read the eval setup below

Hanako

53,692 views • 2 months ago

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 views • 4 months ago

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 views • 17 days ago