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Internal tools are the most underrated use case for AI building. Everyone's showing you consumer apps and landing pages. Meanwhile the operators are quietly building the software that actually runs their companies. 11 internal tools real people are building right now that they could never have built themselves 12...

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Martin Slaney

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21,095 views • 28 days ago •via X (Twitter)

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A DEVELOPER WHO HELPS MAINTAIN GIT ITSELF PROVED THAT USING GIT AND CONTRIBUTING WITH GIT ARE TWO DIFFERENT SKILLS AND ALMOST NO ONE LEARNS THE SECOND 55 minutes from Johannes Schindelin, one of git's most prolific contributors, on the workflow that gets your code accepted into a project you don't own. -> The moment it lands, committing to your own repo turns out to be the easy 10%. Landing a change in someone else's codebase is the part nobody taught you. Most people can save their own work. Far fewer can revise a patch five times, keep the history clean, and merge it into a project moving under them. Saving your code was never the skill -> getting it merged into someone else's is. And when an AI agent fires off a pull request nobody asked for, the person who knows how to really contribute is the one who gets it accepted instead of closed. Anyone can commit to their own repo. The person who can land a change in a project they don't own is the one who actually ships. Bookmark & Watch it today ↓
55:43

A DEVELOPER WHO HELPS MAINTAIN GIT ITSELF PROVED THAT USING GIT AND CONTRIBUTING WITH GIT ARE TWO DIFFERENT SKILLS AND ALMOST NO ONE LEARNS THE SECOND 55 minutes from Johannes Schindelin, one of git's most prolific contributors, on the workflow that gets your code accepted into a project you don't own. -> The moment it lands, committing to your own repo turns out to be the easy 10%. Landing a change in someone else's codebase is the part nobody taught you. Most people can save their own work. Far fewer can revise a patch five times, keep the history clean, and merge it into a project moving under them. Saving your code was never the skill -> getting it merged into someone else's is. And when an AI agent fires off a pull request nobody asked for, the person who knows how to really contribute is the one who gets it accepted instead of closed. Anyone can commit to their own repo. The person who can land a change in a project they don't own is the one who actually ships. Bookmark & Watch it today ↓

slash1s

12,624 views • 24 days ago

Aravind Srinivas just described a future most founders are pretending they are ready for. One person. One machine. A company that runs itself. Srinivas: “Buy a Mac mini, set up a Perplexity personal computer, and run their business on that.” Not a side project. Not a pitch deck. A real business with real revenue while the founder is not in the building. AI runs the ads. Handles SEO. Integrates Stripe. Ships features. Answers customers. All of it executing without a single employee. Srinivas: “Have this all working while you can be sipping wine in Napa.” But before he sold the dream he killed the one most people are already chasing. Srinivas: “Everybody talks about this one-person one-billion-dollar company. It’s not truly moving the GDP by one billion. It’s not truly creating new value.” One researcher collecting a billion in equity does not grow an economy. It rearranges numbers between balance sheets. Nothing gets built. No customer gets served. That is not value creation. That is valuation creation. Srinivas wants no part of it. What he described is the opposite. The person driving Uber between shifts who has the idea but not the payroll. Not the engineering. Not the marketing. Not the support staff. That person gets a machine that replaces all of it. Hundreds of thousands in revenue. Millions. Generated by autonomous systems doing the work that used to require ten employees and a burn rate. Not paper wealth. Not valuation theater. Output that moves through an economy and touches real customers. That is what moves GDP. Not one person worth a billion dollars. A million people each building something worth a million. That math rewrites a country. Then Srinivas said the part that separates him from every hype merchant in the room. Srinivas: “Everybody thinks AI is already there. It’s not there yet. Someone has to do that hard work.” The vision is real. The infrastructure is not. The agents are not autonomous. The integrations are not seamless. The plumbing is not finished. Someone has to wire the APIs. Connect the billing. Build the bridge between what a founder wants and what a machine can deliver. That work is not a keynote. It is not a tweet thread. It is engineering that nobody wants to do and everybody will depend on. Whoever finishes it first does not just build a product. They hand every ambitious person on Earth a company they can run alone. The corporations that need five hundred people to do what one founder with the right infrastructure could do are not efficient. They are exposed. And the person building the thing that exposes them just told you exactly what it looks like. He also told you it is not going to build itself.
1:13

Aravind Srinivas just described a future most founders are pretending they are ready for. One person. One machine. A company that runs itself. Srinivas: “Buy a Mac mini, set up a Perplexity personal computer, and run their business on that.” Not a side project. Not a pitch deck. A real business with real revenue while the founder is not in the building. AI runs the ads. Handles SEO. Integrates Stripe. Ships features. Answers customers. All of it executing without a single employee. Srinivas: “Have this all working while you can be sipping wine in Napa.” But before he sold the dream he killed the one most people are already chasing. Srinivas: “Everybody talks about this one-person one-billion-dollar company. It’s not truly moving the GDP by one billion. It’s not truly creating new value.” One researcher collecting a billion in equity does not grow an economy. It rearranges numbers between balance sheets. Nothing gets built. No customer gets served. That is not value creation. That is valuation creation. Srinivas wants no part of it. What he described is the opposite. The person driving Uber between shifts who has the idea but not the payroll. Not the engineering. Not the marketing. Not the support staff. That person gets a machine that replaces all of it. Hundreds of thousands in revenue. Millions. Generated by autonomous systems doing the work that used to require ten employees and a burn rate. Not paper wealth. Not valuation theater. Output that moves through an economy and touches real customers. That is what moves GDP. Not one person worth a billion dollars. A million people each building something worth a million. That math rewrites a country. Then Srinivas said the part that separates him from every hype merchant in the room. Srinivas: “Everybody thinks AI is already there. It’s not there yet. Someone has to do that hard work.” The vision is real. The infrastructure is not. The agents are not autonomous. The integrations are not seamless. The plumbing is not finished. Someone has to wire the APIs. Connect the billing. Build the bridge between what a founder wants and what a machine can deliver. That work is not a keynote. It is not a tweet thread. It is engineering that nobody wants to do and everybody will depend on. Whoever finishes it first does not just build a product. They hand every ambitious person on Earth a company they can run alone. The corporations that need five hundred people to do what one founder with the right infrastructure could do are not efficient. They are exposed. And the person building the thing that exposes them just told you exactly what it looks like. He also told you it is not going to build itself.

Dustin

64,593 views • 3 months ago

Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.
0:40

Notch Clips. every other ad tool ignores the footage sitting in your dropbox and generates new clips from a prompt. notch opens your library instead. it watches every clip you have ever shot and understands what is inside each one. the mood. who is in frame. what they are doing. the quality. so when you ask it to build an ad, it does not start from scratch. it reaches into your past shoots, finds the clip that fits, and slots it into the exact moment that needs it. here is what that looks like. you had thirteen versions of one reaction shot. notch picked the one that worked and left the other twelve. not by filename. not by guessing from a reference image. it watched all thirteen and could tell the difference. that is the whole idea. the right clip was already in your library. every other tool was about to make a worse one. footage you already shot, turned into every ad you still need. drop your site and a few clips you have. notch builds the first ad from them.

Vinay Jain

406,286 views • 1 month ago

Mark Daigneault shares the coaching philosophy that drives the Oklahoma City Thunder. "Every player is different. And every player is a person first. I've always relied on the instincts of connecting with the person first " Then he shared what professional basketball taught him: "All of these players have a reason to admire them and not just respect them. That's a baseline for any player." "If a player's made it this far, there's a reason to admire them." It means caring about the person. "Expressing that admiration, accepting them for who they are, and then trying to help them be the best they can be. Chase down the vision they have for who they are as a player." "But also plug that into the larger structure of a team in an environment that elevates everybody." The best coaches don't just manage players. They see the person behind the jersey and the team. "It starts with every person. Every person's different - connecting to that and tapping into that." Great coaches care about the person and their future The heart of coaching is a relationships business not a sports business (🎥 OKC Thunder)
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Mark Daigneault shares the coaching philosophy that drives the Oklahoma City Thunder. "Every player is different. And every player is a person first. I've always relied on the instincts of connecting with the person first " Then he shared what professional basketball taught him: "All of these players have a reason to admire them and not just respect them. That's a baseline for any player." "If a player's made it this far, there's a reason to admire them." It means caring about the person. "Expressing that admiration, accepting them for who they are, and then trying to help them be the best they can be. Chase down the vision they have for who they are as a player." "But also plug that into the larger structure of a team in an environment that elevates everybody." The best coaches don't just manage players. They see the person behind the jersey and the team. "It starts with every person. Every person's different - connecting to that and tapping into that." Great coaches care about the person and their future The heart of coaching is a relationships business not a sports business (🎥 OKC Thunder)

Coach AJ 🎯 Mental Fitness

60,212 views • 1 month ago

One person rebuilt an entire company’s brain in 7 days inside Claude Code. Not a doc. Not Obsidian. A living galaxy of nodes. Every employee. Every AI agent. Every SOP. Every tool. All wired together on one screen. Click a department. The human agent team opens up. The SOPs attached to it open up. What each person is allowed to touch opens up. That last part is the whole game. Permissions baked into the brain. An employee opens the chat, the AI already knows what they can access. Agents, data, SOPs surface inside the conversation like you tagged them by hand. Obsidian can’t do this. Notion can’t do this. No dev team. No funding round. No 6-month roadmap. 7 days, 1 person, 1 terminal. This is the part nobody has priced in. The tools to build $200K enterprise software now sit on your laptop for free. The only thing missing is the guy who opens the terminal.
1:20

One person rebuilt an entire company’s brain in 7 days inside Claude Code. Not a doc. Not Obsidian. A living galaxy of nodes. Every employee. Every AI agent. Every SOP. Every tool. All wired together on one screen. Click a department. The human agent team opens up. The SOPs attached to it open up. What each person is allowed to touch opens up. That last part is the whole game. Permissions baked into the brain. An employee opens the chat, the AI already knows what they can access. Agents, data, SOPs surface inside the conversation like you tagged them by hand. Obsidian can’t do this. Notion can’t do this. No dev team. No funding round. No 6-month roadmap. 7 days, 1 person, 1 terminal. This is the part nobody has priced in. The tools to build $200K enterprise software now sit on your laptop for free. The only thing missing is the guy who opens the terminal.

Spike 1%

780,682 views • 1 month ago

i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.
0:22

i just built a 4-agent software team. everything runs from Telegram and gets managed on a kanban board. a project manager who plans the work, a backend developer, a frontend developer, and a tester. the PM reads a goal, breaks it into linked tasks, and assigns each to the right agent. the thing that makes them a team instead of four strangers is a shared kanban board. every task is a row that survives crashes, and when an agent finishes, it writes a summary of what it built and what the next agent needs to know. the next agent reads that summary before it starts. so the frontend developer never has to guess the API shape, and the tester knows exactly what to verify. the hardest part was not the coordination. it was building an agent that could actually act like a backend engineer. a backend engineer stands up a database, wires auth, manages storage, deploys functions, and keeps all of it consistent while the rest of the team builds on top. an agent doing this from scratch drowns. it burns its context window remembering which tables exist and which endpoint it created three steps ago, and the work degrades fast. so the backend agent needs a backend built for agents, not for humans clicking through a dashboard. that is where InsForge came in. it is an open-source, agent-native backend, and i added it to my backend developer agent as a skill. a skill is a step-by-step guide that teaches the agent how to do a specific kind of work. with InsForge installed, the agent stopped improvising infrastructure and followed a reliable path: create the project, define the database, set up auth, deploy functions. to test the whole team, i had them build a working Google Docs clone, AI features included. the backend agent spun up the full service on its own. database tables, user auth, document handling, and edge functions running real TypeScript, all in one dashboard. the frontend agent read that summary and built the UI on top of it, and the tester closed the loop. the result was a backend an agent could reason about end to end, instead of one it kept getting lost inside. if you are building an AI backend engineer, InsForge is worth a look, it's 100% open-source. InsForge GitHub: (don't forget to star 🌟) the full article on Hermes Kanban: Mission Control for your Agents is quoted below.

Akshay 🚀

118,124 views • 1 month ago

I turned myself into a one-person company in 48 hours. No freelancers. No agencies. Just a team of AI Agents from MuleRun 2.0 that actually do the work, not chat about it. This is the closest thing to hiring an entire ops team for the price of coffee.
1:06

I turned myself into a one-person company in 48 hours. No freelancers. No agencies. Just a team of AI Agents from MuleRun 2.0 that actually do the work, not chat about it. This is the closest thing to hiring an entire ops team for the price of coffee.

MAYA

27,253 views • 6 months ago

The Hottest New AI Job: The Agent Maestro Jason: I think the job people are not seeing, but I'm seeing right now, is the person who creates, manages, and is the maestro of the agents. The person who can take the business process, explain it, and train the agent to do it. And there are certain people in business who are just really good at operations. You were one of them, Sacks, running companies. Fire up an agent, train them, and figure out how to manage them and increase their skills. It’s a great job, and it's not a developer. Sacks: With any new technology, there's always a huge change management aspect with enterprises because it's hard for them to adapt and change. And the people in the organization who can lead that change management are the ones who are going to create an amazing career opportunity for themselves.
0:46

The Hottest New AI Job: The Agent Maestro Jason: I think the job people are not seeing, but I'm seeing right now, is the person who creates, manages, and is the maestro of the agents. The person who can take the business process, explain it, and train the agent to do it. And there are certain people in business who are just really good at operations. You were one of them, Sacks, running companies. Fire up an agent, train them, and figure out how to manage them and increase their skills. It’s a great job, and it's not a developer. Sacks: With any new technology, there's always a huge change management aspect with enterprises because it's hard for them to adapt and change. And the people in the organization who can lead that change management are the ones who are going to create an amazing career opportunity for themselves.

The All-In Podcast

350,682 views • 4 months ago

A 2-person startup crossed $2M ARR with an AI agent doing the work of an ops hire. The agent was given read-only access to their codebase and database along with connected tools like Intercom, Stripe, CRM, and Fathom through CLIs. They routed Slack, email, and support requests into a task queue so the agent could pick up each task and run it in Claude Code. So when a customer asked about billing or product behavior, it could inspect how the business actually worked. Along with these tools, a coding agent was also provided. When the ops agent found a repeated task it could not do yet, the coding agent built a tool for it. That tool became permanent. Over time, this grew to 45+ internal tools. The agent also had an instruction.md where it stored the co-founder's feedback to avoid repeating its mistakes.
4:20

A 2-person startup crossed $2M ARR with an AI agent doing the work of an ops hire. The agent was given read-only access to their codebase and database along with connected tools like Intercom, Stripe, CRM, and Fathom through CLIs. They routed Slack, email, and support requests into a task queue so the agent could pick up each task and run it in Claude Code. So when a customer asked about billing or product behavior, it could inspect how the business actually worked. Along with these tools, a coding agent was also provided. When the ops agent found a repeated task it could not do yet, the coding agent built a tool for it. That tool became permanent. Over time, this grew to 45+ internal tools. The agent also had an instruction.md where it stored the co-founder's feedback to avoid repeating its mistakes.

rvivek

11,853 views • 1 month ago

Mark Zuckerberg just described the obsolescence of every institution on Earth and delivered it like a product update. Zuckerberg: “I just think in the future almost everyone is gonna have the power of a 10,000-person organization.” He did not say better tools. He did not say smarter apps. He said the full cognitive output of ten thousand human beings. Packaged into a product. Handed to one person. That is not an upgrade. That is the end of the reason human beings organize at all. Companies exist because one brain is not enough. Governments exist because coordination requires hierarchy. Universities exist because knowledge demands infrastructure. Every institution ever built was a workaround for the same limitation. No single person could do it alone. Zuckerberg is telling you that limitation is about to disappear. The 500-person startup becomes one founder and an AI stack. The law firm becomes one attorney and a system that never sleeps. The hospital becomes one doctor carrying every specialist in their pocket. That is not speculation. That is a deployment schedule. And the man writing it runs a 70,000-person company. He employs 70,000 people and just told the world one person will soon need none of them. That is not a prediction. That is a confession from the man who will be first to act on it. But the part nobody is discussing matters more. This technology does not land on everyone equally. It lands first on the people who already command 10,000-person organizations. Zuckerberg does not get the power of 10,000 people. He already has that. He gets the power of 10,000 organizations. Every revolution in history was sold as liberation. The printing press was supposed to democratize knowledge. It built media empires. The internet was supposed to democratize commerce. It built trillion-dollar platforms. The tool always arrives as liberation. It always settles as leverage. And leverage always consolidates upward. Zuckerberg is not wrong about the capability. One person will do what ten thousand once did. But the question nobody is asking is the only one that matters. If everyone wields the output of 10,000 people, what is a single person actually worth? And then Zuckerberg answered his own question without realizing it. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here?” He meant it as a case for AI. That is the most brutal thing a CEO has ever said about the people who work for him.
0:59

Mark Zuckerberg just described the obsolescence of every institution on Earth and delivered it like a product update. Zuckerberg: “I just think in the future almost everyone is gonna have the power of a 10,000-person organization.” He did not say better tools. He did not say smarter apps. He said the full cognitive output of ten thousand human beings. Packaged into a product. Handed to one person. That is not an upgrade. That is the end of the reason human beings organize at all. Companies exist because one brain is not enough. Governments exist because coordination requires hierarchy. Universities exist because knowledge demands infrastructure. Every institution ever built was a workaround for the same limitation. No single person could do it alone. Zuckerberg is telling you that limitation is about to disappear. The 500-person startup becomes one founder and an AI stack. The law firm becomes one attorney and a system that never sleeps. The hospital becomes one doctor carrying every specialist in their pocket. That is not speculation. That is a deployment schedule. And the man writing it runs a 70,000-person company. He employs 70,000 people and just told the world one person will soon need none of them. That is not a prediction. That is a confession from the man who will be first to act on it. But the part nobody is discussing matters more. This technology does not land on everyone equally. It lands first on the people who already command 10,000-person organizations. Zuckerberg does not get the power of 10,000 people. He already has that. He gets the power of 10,000 organizations. Every revolution in history was sold as liberation. The printing press was supposed to democratize knowledge. It built media empires. The internet was supposed to democratize commerce. It built trillion-dollar platforms. The tool always arrives as liberation. It always settles as leverage. And leverage always consolidates upward. Zuckerberg is not wrong about the capability. One person will do what ten thousand once did. But the question nobody is asking is the only one that matters. If everyone wields the output of 10,000 people, what is a single person actually worth? And then Zuckerberg answered his own question without realizing it. Zuckerberg: “If the intelligence of a 10,000-person company is not greater than the intelligence of a single person, then what are we doing here?” He meant it as a case for AI. That is the most brutal thing a CEO has ever said about the people who work for him.

Dustin

54,019 views • 2 months ago

ANTHROPIC OPEN-SOURCED A FREE REPO THAT TURNS CLAUDE INTO A SALES REP, A MARKETER AND A FINANCE LEAD. PEOPLE ARE ALREADY SELLING THIS AS A SERVICE You're not prompting from scratch. You're hiring a department How to set it up: 1. Open Cowork. In the Claude desktop app, open Cowork and go to Customize. You'll see a Browse Plugins button. That's the marketplace 2. Pick your first role. Inside you'll find sales, marketing, finance, legal, data, customer support, product management and more. Each plugin has the skills for that role already baked in, plus the connectors it would use. Install the one you need most 3. Put it to work standalone. It works day one with no setup. Trigger a workflow with a slash command like /sales:call-prep or /data:write-query, paste your notes, and it already knows what good output looks like 4. Connect its tools to supercharge it. Authorize the tools that role uses, your CRM, your analytics, your data warehouse. Standalone is the intern. Connected is the senior hire 5. Build the rest of the team. Install more roles and they work together in one session. Data pulls the numbers, finance reconciles them, marketing turns it into a report. One operator, a full cross-functional team, no payroll This is the same base layer Claude for Legal and Claude for Financial Services are built on. You're getting it for free Full breakdown in my article below. Bookmark this
0:30

ANTHROPIC OPEN-SOURCED A FREE REPO THAT TURNS CLAUDE INTO A SALES REP, A MARKETER AND A FINANCE LEAD. PEOPLE ARE ALREADY SELLING THIS AS A SERVICE You're not prompting from scratch. You're hiring a department How to set it up: 1. Open Cowork. In the Claude desktop app, open Cowork and go to Customize. You'll see a Browse Plugins button. That's the marketplace 2. Pick your first role. Inside you'll find sales, marketing, finance, legal, data, customer support, product management and more. Each plugin has the skills for that role already baked in, plus the connectors it would use. Install the one you need most 3. Put it to work standalone. It works day one with no setup. Trigger a workflow with a slash command like /sales:call-prep or /data:write-query, paste your notes, and it already knows what good output looks like 4. Connect its tools to supercharge it. Authorize the tools that role uses, your CRM, your analytics, your data warehouse. Standalone is the intern. Connected is the senior hire 5. Build the rest of the team. Install more roles and they work together in one session. Data pulls the numbers, finance reconciles them, marketing turns it into a report. One operator, a full cross-functional team, no payroll This is the same base layer Claude for Legal and Claude for Financial Services are built on. You're getting it for free Full breakdown in my article below. Bookmark this

Yarchi

31,798 views • 29 days ago

Boris Cherny: "Claude Code is 100% written by Claude Code, Cowork is 100% written by Claude Code" across all of Anthropic, 90% of code is written by Claude lawyers, designers, finance people are building real things with Claude Code right now with no CS degree, no background, nothing the people who built the tool use the tool to build the tool think about what that means for everyone else the guide on everything Claude can actually do is in the article below
2:15

Boris Cherny: "Claude Code is 100% written by Claude Code, Cowork is 100% written by Claude Code" across all of Anthropic, 90% of code is written by Claude lawyers, designers, finance people are building real things with Claude Code right now with no CS degree, no background, nothing the people who built the tool use the tool to build the tool think about what that means for everyone else the guide on everything Claude can actually do is in the article below

Anatoli Kopadze

90,364 views • 1 month ago

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: “The code that Oracle is writing, Oracle isn’t writing. Our AI models are writing.” This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: “We don’t write the procedure. We declare our intent.” That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: “We just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.” You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.
0:31

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: “The code that Oracle is writing, Oracle isn’t writing. Our AI models are writing.” This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: “We don’t write the procedure. We declare our intent.” That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: “We just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.” You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.

Dustin

534,277 views • 3 months ago

SOMEONE IS CHARGING $5,000/MONTH FOR SOCIAL MEDIA CONTENT THAT CLAUDE WRITES IN 6 HOURS A WEEK no team, no office, just Claude and a scheduling app mid-market companies pay $2,000-$5,000 per month for social media management, and most of them are getting a junior freelancer posting generic content or an agency that barely touches their account one of them runs the whole thing in a weekly workflow: brief Claude on Monday, write posts Tuesday and Wednesday, schedule Thursday, pull numbers Friday another one charged three clients the same $5,000 rate before hiring a single person, that's $180,000/year running on one tool there's a prompt that makes Claude write every post in the client's exact voice by analyzing 5 examples of their existing content, 10 min per post instead of 60 you can land the first client with one outreach message, no portfolio, no case studies, just a specific offer and a 30-minute call the model is already working, the only question is whether you build it or watch someone else do it full breakdown of the workflow, the prompts, and how to find clients in the article below
0:42

SOMEONE IS CHARGING $5,000/MONTH FOR SOCIAL MEDIA CONTENT THAT CLAUDE WRITES IN 6 HOURS A WEEK no team, no office, just Claude and a scheduling app mid-market companies pay $2,000-$5,000 per month for social media management, and most of them are getting a junior freelancer posting generic content or an agency that barely touches their account one of them runs the whole thing in a weekly workflow: brief Claude on Monday, write posts Tuesday and Wednesday, schedule Thursday, pull numbers Friday another one charged three clients the same $5,000 rate before hiring a single person, that's $180,000/year running on one tool there's a prompt that makes Claude write every post in the client's exact voice by analyzing 5 examples of their existing content, 10 min per post instead of 60 you can land the first client with one outreach message, no portfolio, no case studies, just a specific offer and a 30-minute call the model is already working, the only question is whether you build it or watch someone else do it full breakdown of the workflow, the prompts, and how to find clients in the article below

Chrome

13,769 views • 1 month ago

To my brothers and sisters, a call to action.. Please stand with the families of the Samourai Wallet developers. These men built privacy tools in a world that grows more hostile to privacy by the day. Now their families are carrying the weight of a fight they never asked for, while the machine tries to turn builders into criminals and make an example out of those who dared to defend financial sovereignty. Privacy is not a crime. Code is not a confession. Building tools for free men is not an act of evil. Support their families. Help them endure the fire. Because when the state comes for the builders of privacy, it is not only their door being kicked in. It is a warning shot aimed at every sovereign soul who still believes human beings have the right to transact, speak, build, and exist without being watched like cattle. Stand with them. Proof of work is not just mining. Sometimes it is standing beside the men who built the tools when the world turns cold. Sign the pardon petition, and donate.
1:46

To my brothers and sisters, a call to action.. Please stand with the families of the Samourai Wallet developers. These men built privacy tools in a world that grows more hostile to privacy by the day. Now their families are carrying the weight of a fight they never asked for, while the machine tries to turn builders into criminals and make an example out of those who dared to defend financial sovereignty. Privacy is not a crime. Code is not a confession. Building tools for free men is not an act of evil. Support their families. Help them endure the fire. Because when the state comes for the builders of privacy, it is not only their door being kicked in. It is a warning shot aimed at every sovereign soul who still believes human beings have the right to transact, speak, build, and exist without being watched like cattle. Stand with them. Proof of work is not just mining. Sometimes it is standing beside the men who built the tools when the world turns cold. Sign the pardon petition, and donate.

HODLTarantula(HT)🏴‍☠️Sovereign Maximalist

10,126 views • 2 months ago

Your morning white pill from Jeremy Boreing is that to succeed, you must resist a victim mentality: “One of the great truths in life is that you cannot behave as a victim even if you are one- perhaps especially if you are one bc then it is actually reinforced by reality… One of the hardest things to do is to see yourself as a person with agency. It is the difference between the people who succeed in life and the people who don’t. It’s the difference between the people who are happy and the people who are not.”
0:37

Your morning white pill from Jeremy Boreing is that to succeed, you must resist a victim mentality: “One of the great truths in life is that you cannot behave as a victim even if you are one- perhaps especially if you are one bc then it is actually reinforced by reality… One of the hardest things to do is to see yourself as a person with agency. It is the difference between the people who succeed in life and the people who don’t. It’s the difference between the people who are happy and the people who are not.”

Jackie Chea ⚖️

30,479 views • 2 months ago

Jensen Huang just told the world something nobody wants to hear. AI is not coming for your job. It is coming for the part of your job you mistakenly believe IS your job. Huang: “The purpose of your job and the tasks that you do in your job are related but not the same.” That one sentence is the fault line between the people who thrive in the next decade and the people who vanish from it. Huang used himself as proof. Reduce the CEO of Nvidia to his raw outputs and his entire career is typing and talking. Both have been automated to superhuman levels. Huang: “Typing and talking have both been automated to a superhuman level by AI. And yet, I’m busier than ever.” The man building the infrastructure that automates human labor has never worked harder. That should stop you cold. We look at a profession and see the tasks. The motions. The mechanical friction. We never see the intent underneath. And when AI arrives, we panic. Because we confuse the task with the job. The task was never the job. It was always the bottleneck between a human and their actual purpose. Now the bottleneck is dissolving. Years ago, the experts declared radiology dead. The algorithm could read a scan better than any human. A generation of medical students listened. They walked away from the field. The result was catastrophic. Huang: “We need more radiologists than ever, and we don’t have enough.” The algorithm did not replace the doctor. It armed the doctor. Suddenly the department could see more patients. Catch more anomalies. Generate more revenue. The hospital did not fire the radiologists. It tried to hire more. And could not find them. Because we terrified an entire generation out of a career with a prediction that landed exactly backwards. Now the same hysteria is consuming software engineering. The timeline is screaming that coding is dead. Meanwhile, inside the very company building the hardware that automates code. Huang: “The software engineers that know how to use AI, know how to work with agentic systems, are the most popular and the most successful.” The tool did not replace the architect. It replaced the shovel. This is the pattern nobody wants to confront. AI does not eliminate the human. It eliminates the friction that made the human slow. And when the friction disappears, demand for the human explodes. But only if the human shows up. The ones who defined themselves by the mechanical act of writing code are fading. The ones who defined themselves by what the code was meant to build are now the most valuable people on the planet. That is not a nuance. That is the entire dividing line. The machine will write the script. Read the scan. Draft the brief. It will never possess the reason any of it needed to exist. The task was never the job. And nobody who figures that out last gets the privilege of figuring it out twice.
2:00

Jensen Huang just told the world something nobody wants to hear. AI is not coming for your job. It is coming for the part of your job you mistakenly believe IS your job. Huang: “The purpose of your job and the tasks that you do in your job are related but not the same.” That one sentence is the fault line between the people who thrive in the next decade and the people who vanish from it. Huang used himself as proof. Reduce the CEO of Nvidia to his raw outputs and his entire career is typing and talking. Both have been automated to superhuman levels. Huang: “Typing and talking have both been automated to a superhuman level by AI. And yet, I’m busier than ever.” The man building the infrastructure that automates human labor has never worked harder. That should stop you cold. We look at a profession and see the tasks. The motions. The mechanical friction. We never see the intent underneath. And when AI arrives, we panic. Because we confuse the task with the job. The task was never the job. It was always the bottleneck between a human and their actual purpose. Now the bottleneck is dissolving. Years ago, the experts declared radiology dead. The algorithm could read a scan better than any human. A generation of medical students listened. They walked away from the field. The result was catastrophic. Huang: “We need more radiologists than ever, and we don’t have enough.” The algorithm did not replace the doctor. It armed the doctor. Suddenly the department could see more patients. Catch more anomalies. Generate more revenue. The hospital did not fire the radiologists. It tried to hire more. And could not find them. Because we terrified an entire generation out of a career with a prediction that landed exactly backwards. Now the same hysteria is consuming software engineering. The timeline is screaming that coding is dead. Meanwhile, inside the very company building the hardware that automates code. Huang: “The software engineers that know how to use AI, know how to work with agentic systems, are the most popular and the most successful.” The tool did not replace the architect. It replaced the shovel. This is the pattern nobody wants to confront. AI does not eliminate the human. It eliminates the friction that made the human slow. And when the friction disappears, demand for the human explodes. But only if the human shows up. The ones who defined themselves by the mechanical act of writing code are fading. The ones who defined themselves by what the code was meant to build are now the most valuable people on the planet. That is not a nuance. That is the entire dividing line. The machine will write the script. Read the scan. Draft the brief. It will never possess the reason any of it needed to exist. The task was never the job. And nobody who figures that out last gets the privilege of figuring it out twice.

Dustin

52,811 views • 2 months ago

Pedro Franceschi explains why Brex doesn’t hire “people managers” anymore One day Brex founder Pedro Franceschi made a list of all of the leaders at the company who worked and didn’t work. “I was trying to find what was predictive of leadership success,” he explains. “A lot of things are important, but they’re not predictive. For example, being customer obsessed is important, but there are people who were customer obsessed who were on both sides of the list.” The only trait that Pedro found to be predictive of leadership success at Brex was what he calls “the ability to operate at all levels” — someone who even at the highest levels of leadership has a deep understanding of the details of execution at the individual contributor level. What this means in practice is a CTO who is actually a great engineer. A Head of Design who can actually design amazing products. And a great Head of Sales who can actually go and close deals themselves if they need to. “It doesn’t mean that they’re going to do that all the time,” Pedro explains, “But it means that they know the nuances of what makes someone great at the craft… If you don’t know how to identify greatness because you don’t know what the bar is yourself, there’s no way to build a team that’s great.” He continues: “A lot of companies develop this role over time that people call a ‘people manager.’ They’re Director of Engineering but they can’t really code because they manage people now… And that concept is just something we eliminated. At the end of the day, there’s no way to manage people divorced from the work — you’re managing the work itself.” Pedro uses Jony Ive as an example: “Jony Ive wasn’t managing the team that designed the iPhone. He was designing the iPhone with a group of people. It’s simple, but it is a very profound change in how you orient your relationship with the work and what you put out there in the world. And I think you have to select for people who appreciate the actual output of the work and the work itself, not the process of doing the work… What matters is: Do you know what great looks like? Can you do it yourself? And can you bring people along with a really high bar for doing it at all level.” Video source: Kleiner Perkins (2025)
3:50

Pedro Franceschi explains why Brex doesn’t hire “people managers” anymore One day Brex founder Pedro Franceschi made a list of all of the leaders at the company who worked and didn’t work. “I was trying to find what was predictive of leadership success,” he explains. “A lot of things are important, but they’re not predictive. For example, being customer obsessed is important, but there are people who were customer obsessed who were on both sides of the list.” The only trait that Pedro found to be predictive of leadership success at Brex was what he calls “the ability to operate at all levels” — someone who even at the highest levels of leadership has a deep understanding of the details of execution at the individual contributor level. What this means in practice is a CTO who is actually a great engineer. A Head of Design who can actually design amazing products. And a great Head of Sales who can actually go and close deals themselves if they need to. “It doesn’t mean that they’re going to do that all the time,” Pedro explains, “But it means that they know the nuances of what makes someone great at the craft… If you don’t know how to identify greatness because you don’t know what the bar is yourself, there’s no way to build a team that’s great.” He continues: “A lot of companies develop this role over time that people call a ‘people manager.’ They’re Director of Engineering but they can’t really code because they manage people now… And that concept is just something we eliminated. At the end of the day, there’s no way to manage people divorced from the work — you’re managing the work itself.” Pedro uses Jony Ive as an example: “Jony Ive wasn’t managing the team that designed the iPhone. He was designing the iPhone with a group of people. It’s simple, but it is a very profound change in how you orient your relationship with the work and what you put out there in the world. And I think you have to select for people who appreciate the actual output of the work and the work itself, not the process of doing the work… What matters is: Do you know what great looks like? Can you do it yourself? And can you bring people along with a really high bar for doing it at all level.” Video source: Kleiner Perkins (2025)

Startup Archive

45,584 views • 1 year ago

Marc Andreessen went on Chris Williamson's podcast and broke down exactly how Elon Musk runs multiple companies at once No other CEO on Earth does this: 1. Every week, Musk shows up at each of his companies, identifies the single biggest problem that company is having that week, and fixes it. Then he does that for 52 weeks in a row. At the end of the year, each company has solved its 52 biggest problems. Meanwhile, most large companies are still having the planning meeting for the pre-planning meeting for the board presentation with the compliance review and the legal review attached. 2. This is not a new operating method. It is actually how the great industrialists of the late 1800s and early 1900s ran their companies. Henry Ford, Andrew Carnegie, Thomas Watson, who built IBM. Total devotion from the leader to fully and deeply understand what the company does, be in the trenches, talk directly to the people doing the work, and be the lead problem solver in the organization. Andreessen says he is not aware of another current CEO who operates this way. 3. The framework Musk uses is the bottleneck. In any manufacturing chain, there is always one thing holding everything up. Sometimes it is raw materials at the start. Sometimes it is warehousing at the end. Sometimes it is in the middle. The job is to find it and remove it. Musk has universalized this concept across every company he runs. In any given week, there is one main bottleneck. He micromanages the solution to that one thing and delegates almost everything else. 4. Musk delegates almost everything. Andreessen is clear about this. He is not involved in most of what his companies are doing. He is involved in the one thing that is the biggest problem right now. Once that is fixed, he moves to the next biggest problem. Everything else by definition, is running better than the bottleneck, so it does not need him. 5. When Musk identifies the bottleneck, he goes directly to the engineer who actually understands it. not the VP of engineering, not the director, not the manager. The individual contributor who has the actual technical knowledge. He sits in the room with that person and fixes the problem alongside them. He does not ask for a report to be reviewed in three weeks. he shows up at the keyboard or on the manufacturing line and works through it overnight if necessary. 6. This is why technical people who work for Musk say it was the best experience of their lives. Andreessen's framing: if you are stuck on a problem you cannot solve, Elon Musk is going to show up in his Gulfstream, sit with you in front of the keyboard, and help you figure it out. For an engineer who genuinely cares about the work, that is an almost incomprehensible level of support from the CEO of the company. 7. Business school teaches the opposite of this: management as a generic skill applicable to any industry. Soup company or a rocket company, the management principles are the same. process, balance sheet, meeting schedules, compliance, executive motivation, interpersonal conflict resolution. Andreessen says those skills are useful in many contexts. They just give you nothing; you need to do what Musk does. And Musk pushes as far as he can away from all of that so he can spend all of his time doing the things only he can do.
5:40

Marc Andreessen went on Chris Williamson's podcast and broke down exactly how Elon Musk runs multiple companies at once No other CEO on Earth does this: 1. Every week, Musk shows up at each of his companies, identifies the single biggest problem that company is having that week, and fixes it. Then he does that for 52 weeks in a row. At the end of the year, each company has solved its 52 biggest problems. Meanwhile, most large companies are still having the planning meeting for the pre-planning meeting for the board presentation with the compliance review and the legal review attached. 2. This is not a new operating method. It is actually how the great industrialists of the late 1800s and early 1900s ran their companies. Henry Ford, Andrew Carnegie, Thomas Watson, who built IBM. Total devotion from the leader to fully and deeply understand what the company does, be in the trenches, talk directly to the people doing the work, and be the lead problem solver in the organization. Andreessen says he is not aware of another current CEO who operates this way. 3. The framework Musk uses is the bottleneck. In any manufacturing chain, there is always one thing holding everything up. Sometimes it is raw materials at the start. Sometimes it is warehousing at the end. Sometimes it is in the middle. The job is to find it and remove it. Musk has universalized this concept across every company he runs. In any given week, there is one main bottleneck. He micromanages the solution to that one thing and delegates almost everything else. 4. Musk delegates almost everything. Andreessen is clear about this. He is not involved in most of what his companies are doing. He is involved in the one thing that is the biggest problem right now. Once that is fixed, he moves to the next biggest problem. Everything else by definition, is running better than the bottleneck, so it does not need him. 5. When Musk identifies the bottleneck, he goes directly to the engineer who actually understands it. not the VP of engineering, not the director, not the manager. The individual contributor who has the actual technical knowledge. He sits in the room with that person and fixes the problem alongside them. He does not ask for a report to be reviewed in three weeks. he shows up at the keyboard or on the manufacturing line and works through it overnight if necessary. 6. This is why technical people who work for Musk say it was the best experience of their lives. Andreessen's framing: if you are stuck on a problem you cannot solve, Elon Musk is going to show up in his Gulfstream, sit with you in front of the keyboard, and help you figure it out. For an engineer who genuinely cares about the work, that is an almost incomprehensible level of support from the CEO of the company. 7. Business school teaches the opposite of this: management as a generic skill applicable to any industry. Soup company or a rocket company, the management principles are the same. process, balance sheet, meeting schedules, compliance, executive motivation, interpersonal conflict resolution. Andreessen says those skills are useful in many contexts. They just give you nothing; you need to do what Musk does. And Musk pushes as far as he can away from all of that so he can spend all of his time doing the things only he can do.

Jaynit

269,909 views • 15 days ago

A DEVELOPER MADE A REAL COMMIT WITHOUT EVER TYPING GIT ADD OR GIT COMMIT -- JUST TO PROVE THE COMMANDS YOU LIVE BY ARE A THIN SHELL OVER A DATABASE YOU'VE NEVER ONCE OPENED 55 minutes from Tim Berglund, a longtime Git teacher and GitHub evangelist, taking the tool apart down to the raw objects almost nobody who uses it every day has ever touched. -> The moment it clicks, Git stops being a pile of memorized commands and becomes what it actually is underneath: a tiny content-addressed database of blobs, trees and commits. git add and git commit are just polite wrappers around writing objects into it by hand. Every commit you've ever made was Git hashing a snapshot and filing it by fingerprint. Branches are just labels pointing at one of those objects. The work you thought you destroyed with a bad reset is still sitting in the reflog. Once you can see that graph, the commands that used to terrify you stop being scary at all. Memorizing commands was never the skill -> reading the object graph in your head is. And with an AI agent now committing and rebasing on your machine faster than you can follow, the one person who can untangle the mess it leaves is the one who knows what's really stored down there. There's a person on every team everyone runs to when Git breaks. This is the talk that quietly turns you into them. You'll reach for it the next time a rebase goes sideways. Bookmark & Watch it today ↓
55:19

A DEVELOPER MADE A REAL COMMIT WITHOUT EVER TYPING GIT ADD OR GIT COMMIT -- JUST TO PROVE THE COMMANDS YOU LIVE BY ARE A THIN SHELL OVER A DATABASE YOU'VE NEVER ONCE OPENED 55 minutes from Tim Berglund, a longtime Git teacher and GitHub evangelist, taking the tool apart down to the raw objects almost nobody who uses it every day has ever touched. -> The moment it clicks, Git stops being a pile of memorized commands and becomes what it actually is underneath: a tiny content-addressed database of blobs, trees and commits. git add and git commit are just polite wrappers around writing objects into it by hand. Every commit you've ever made was Git hashing a snapshot and filing it by fingerprint. Branches are just labels pointing at one of those objects. The work you thought you destroyed with a bad reset is still sitting in the reflog. Once you can see that graph, the commands that used to terrify you stop being scary at all. Memorizing commands was never the skill -> reading the object graph in your head is. And with an AI agent now committing and rebasing on your machine faster than you can follow, the one person who can untangle the mess it leaves is the one who knows what's really stored down there. There's a person on every team everyone runs to when Git breaks. This is the talk that quietly turns you into them. You'll reach for it the next time a rebase goes sideways. Bookmark & Watch it today ↓

slash1s

236,545 views • 1 month ago