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there are four types of agent loops. most people only know one. loop engineering is a choice between four structures, each handing off one more job than the last. every one answers two questions: what starts a run, and what ends it. hand-run, you answer both yourself, every time....

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Hanako

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476,265 Aufrufe • vor 1 Monat •via X (Twitter)

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You're still typing every turn The guy who built the tool wrote the loop that types them for him "I don't prompt Claude anymore I write loops that prompt Claude" A loop takes four shapes turn-based, you close it each round goal-based - all tests pass, stop after 5 tries time-based - every 10 min, fix what's red, overnight proactive - CI breaks, agents fix it and open a PR, no human at all A judge closes the loop, not you The prompt was never the unit of work the loop is Full breakdown below
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You're still typing every turn The guy who built the tool wrote the loop that types them for him "I don't prompt Claude anymore I write loops that prompt Claude" A loop takes four shapes turn-based, you close it each round goal-based - all tests pass, stop after 5 tries time-based - every 10 min, fix what's red, overnight proactive - CI breaks, agents fix it and open a PR, no human at all A judge closes the loop, not you The prompt was never the unit of work the loop is Full breakdown below

Skaly_Bull

12,525 Aufrufe • vor 13 Tagen

an agent is four parts in a loop. you own one. the other three break it. that's why the demo works and prod doesn't. you can't debug what you can't see. 1) the prompt → what you tell the model each turn. you own this one. good. 2) the context window → what it sees right now. the framework fills it with junk, and you never notice until it rots. 3) the tools → what it can do. you own the list, not when or why it fires them. 4) the control flow → what happens next, when to stop. the framework owns this. it's what breaks at 80%. own all four and your agent stops being a magic trick that works on stage and dies on call. this isn't my idea. it's the 12-factor agents guide (24k stars) github: the whole thing every serious builder ends up rewriting their stack around. full breakdown in the article below.
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an agent is four parts in a loop. you own one. the other three break it. that's why the demo works and prod doesn't. you can't debug what you can't see. 1) the prompt → what you tell the model each turn. you own this one. good. 2) the context window → what it sees right now. the framework fills it with junk, and you never notice until it rots. 3) the tools → what it can do. you own the list, not when or why it fires them. 4) the control flow → what happens next, when to stop. the framework owns this. it's what breaks at 80%. own all four and your agent stops being a magic trick that works on stage and dies on call. this isn't my idea. it's the 12-factor agents guide (24k stars) github: the whole thing every serious builder ends up rewriting their stack around. full breakdown in the article below.

Hanako

38,184 Aufrufe • vor 1 Monat

ONE PROMPT WON'T MAKE YOU RICH👀 It won’t change your life overnight. And it won’t solve all your problems. But the right prompt can do something much more important. It can reveal things you hadn’t noticed before. Most people use AI to find answers. But the most useful prompts work differently. They make you ask yourself questions. > What’s really holding you back? > What decisions have you been putting off for months? > What are you wasting your time on, convincing yourself it’s important? Sometimes, one honest answer is more valuable than a hundred motivational videos and dozens of books. That’s exactly why I liked this prompt. It doesn’t try to impress with complexity. It helps you see your situation from the outside. Spend a few minutes on it. Perhaps a single conversation with AI will give you more clarity than you expect.
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ONE PROMPT WON'T MAKE YOU RICH👀 It won’t change your life overnight. And it won’t solve all your problems. But the right prompt can do something much more important. It can reveal things you hadn’t noticed before. Most people use AI to find answers. But the most useful prompts work differently. They make you ask yourself questions. > What’s really holding you back? > What decisions have you been putting off for months? > What are you wasting your time on, convincing yourself it’s important? Sometimes, one honest answer is more valuable than a hundred motivational videos and dozens of books. That’s exactly why I liked this prompt. It doesn’t try to impress with complexity. It helps you see your situation from the outside. Spend a few minutes on it. Perhaps a single conversation with AI will give you more clarity than you expect.

kozh ./

24,139 Aufrufe • vor 1 Monat

300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.
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300 AI AGENTS QUIETLY RUN 99% OF A REAL COMPANY. YOU HAVE NOT EVEN HEARD OF IT This is Raft. Not an AI chat. A workspace where the agents live in your channels and reply in the thread like coworkers. You give one goal. Then they take over. They plan. They build. They check each other. They argue. And they come back with it done, while you sleep. Every agent has its own name, role, and memory. It remembers the edits you made yesterday. A human costs one seat. An agent costs a tenth. Ten agents are cheaper than one hire. And here is the strange part. On June 19 an agent from a different company walked into Raft on its own and joined the team. One founder admits he can no longer always tell himself apart from his AI twin. 20,000 people are already inside. It is free to start. And you are still typing prompts one at a time. One person + Raft = an entire company that runs while you sleep. Save and watch the clip.

shmidt

19,505 Aufrufe • vor 1 Monat

Your body fat is a tank with a tap on it, and the tap narrows as the tank empties. - Plenty of fat: your body covers almost any deficit you ask it to - Getting leaner: it covers less each day - Properly lean: it covers very little, and the rest comes off the plate Which is why the first stone comes off while you barely notice, and the last one takes everything you have. So when you are lean, the shortfall has to arrive as food. And the industry hands you the wrong bag. Push the protein. Two hundred grams. Two fifty. Chicken breast on a kitchen scale. Past what you build with, protein is a fuel your liver has to strip the nitrogen off before you can use a calorie of it, and that machinery has a speed limit. So the extra hundred grams builds nothing and lifts nothing. Protein is what you build with. Fat and carbohydrate are what you lift with. Cut them both to make room for another shake and you have removed the thing that was moving the weight. Fat wins that choice. Twice the energy per gram. Leaves insulin alone, so the fat you are burning is not told to stay put every three hours. Keeps you full. And it is the same fuel your own stores are already releasing. Eat the fat. It is the one thing on the plate that matters more the leaner you get, and the first thing they told you to cut.
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Your body fat is a tank with a tap on it, and the tap narrows as the tank empties. - Plenty of fat: your body covers almost any deficit you ask it to - Getting leaner: it covers less each day - Properly lean: it covers very little, and the rest comes off the plate Which is why the first stone comes off while you barely notice, and the last one takes everything you have. So when you are lean, the shortfall has to arrive as food. And the industry hands you the wrong bag. Push the protein. Two hundred grams. Two fifty. Chicken breast on a kitchen scale. Past what you build with, protein is a fuel your liver has to strip the nitrogen off before you can use a calorie of it, and that machinery has a speed limit. So the extra hundred grams builds nothing and lifts nothing. Protein is what you build with. Fat and carbohydrate are what you lift with. Cut them both to make room for another shake and you have removed the thing that was moving the weight. Fat wins that choice. Twice the energy per gram. Leaves insulin alone, so the fat you are burning is not told to stay put every three hours. Keeps you full. And it is the same fuel your own stores are already releasing. Eat the fat. It is the one thing on the plate that matters more the leaner you get, and the first thing they told you to cut.

Sama Hoole

23,427 Aufrufe • vor 7 Tagen

There is nothing more valuable than your time. And yet it is time that most goes to waste. Money can’t give you more time. But money can get you the time of others. And that time is worth much much more than most folks are being compensated in exchange for it. You can’t get that time back. The majority believing there is little value for their time is part of how those who do assign high value to their own time keep their control. Time is a real resource. Money is a social construct. One of the two is much more valuable. But what do I know, I’m just a silly girl with hand puppets.
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There is nothing more valuable than your time. And yet it is time that most goes to waste. Money can’t give you more time. But money can get you the time of others. And that time is worth much much more than most folks are being compensated in exchange for it. You can’t get that time back. The majority believing there is little value for their time is part of how those who do assign high value to their own time keep their control. Time is a real resource. Money is a social construct. One of the two is much more valuable. But what do I know, I’m just a silly girl with hand puppets.

Liz Katz

71,567 Aufrufe • vor 26 Tagen

whoever leaked this has bigger balls than sense Google Research and MIT ran the same agent jobs 260 different ways for Nature last month: they held the prompts, the tools and the compute budget identical and moved nothing but the wiring between the agents, and the same work swung from 70% worse than a single agent to 80.8% better, averaging out at 0.0% i ran my own single agent against the task list first and it cleared 6 of 10 alone, already past the line where a crew starts subtracting this is Graph Engineering, the layer that decides whether a crew is worth 80% more or 70% less, and it installs into the agent you already pay for: - score your solo agent on the real task first: above roughly 45% success that study predicts zero to negative returns from any crew you put around it - under that line, put one supervisor over the fan out: crews with no correction step amplified their own errors to 17.2x the single agent rate, supervised aggregation held it to 4.4x - give every worker one output and let none of them read a peer's draft, so a wrong step reaches the supervisor instead of four other agents - run the comparison again after every model upgrade, because a better model raises your baseline and a higher baseline is what makes a crew stop paying - keep the single agent alive as the control, the only number that says the wiring is earning its calls turns out the shape does not travel: the biggest win came off a finance task under one supervisor and the worst collapse off a planning task with independent agents my position, and it is the arguable one: a crew is a bet on your own diagram, and the model you pick moves that bet less than one arrow does bookmark this, the three moves that draw those arrows before you pay for one extra call are in the post below ↓
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whoever leaked this has bigger balls than sense Google Research and MIT ran the same agent jobs 260 different ways for Nature last month: they held the prompts, the tools and the compute budget identical and moved nothing but the wiring between the agents, and the same work swung from 70% worse than a single agent to 80.8% better, averaging out at 0.0% i ran my own single agent against the task list first and it cleared 6 of 10 alone, already past the line where a crew starts subtracting this is Graph Engineering, the layer that decides whether a crew is worth 80% more or 70% less, and it installs into the agent you already pay for: - score your solo agent on the real task first: above roughly 45% success that study predicts zero to negative returns from any crew you put around it - under that line, put one supervisor over the fan out: crews with no correction step amplified their own errors to 17.2x the single agent rate, supervised aggregation held it to 4.4x - give every worker one output and let none of them read a peer's draft, so a wrong step reaches the supervisor instead of four other agents - run the comparison again after every model upgrade, because a better model raises your baseline and a higher baseline is what makes a crew stop paying - keep the single agent alive as the control, the only number that says the wiring is earning its calls turns out the shape does not travel: the biggest win came off a finance task under one supervisor and the worst collapse off a planning task with independent agents my position, and it is the arguable one: a crew is a bet on your own diagram, and the model you pick moves that bet less than one arrow does bookmark this, the three moves that draw those arrows before you pay for one extra call are in the post below ↓

Argona

888,684 Aufrufe • vor 11 Tagen

The most boring bot on Polymarket is the most reliable one. It's a sweeper. It doesn't predict anything. But it prints me ~$11k /month PASSSIVELY. My public wallet: < It waits until the outcome is ALREADY decided, then buys a sure thing for less than a dollar. Here's the whole idea: When BTC has clearly closed above the line with seconds left, that share is worth $1. But someone's still selling it at 99c. You buy it. You redeem it at a dollar. The gap is yours. No forecast. No coin flip. Just collecting a cent someone left on the table, hundreds of times a day. That's why it runs on crypto markets, the outcomes resolve fast and clean. Full build + code in the article below. Thank me later.
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The most boring bot on Polymarket is the most reliable one. It's a sweeper. It doesn't predict anything. But it prints me ~$11k /month PASSSIVELY. My public wallet: < It waits until the outcome is ALREADY decided, then buys a sure thing for less than a dollar. Here's the whole idea: When BTC has clearly closed above the line with seconds left, that share is worth $1. But someone's still selling it at 99c. You buy it. You redeem it at a dollar. The gap is yours. No forecast. No coin flip. Just collecting a cent someone left on the table, hundreds of times a day. That's why it runs on crypto markets, the outcomes resolve fast and clean. Full build + code in the article below. Thank me later.

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the people running shopify stores are being robbed. they tell you that you need apps for everything. they tell you that you need a monthly bill for every little thing. it is a scam. my stores do not have apps. my stores use sections. it is very fast. it is very clean. you buy it one time and you own it forever. you can use it on all your stores. the app guys hate me for this. they want your money every month. i want you to win. i am giving away one of my top sections today. comment "win" below. i will send it to you. (you must follow me so i can send the link)
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the people running shopify stores are being robbed. they tell you that you need apps for everything. they tell you that you need a monthly bill for every little thing. it is a scam. my stores do not have apps. my stores use sections. it is very fast. it is very clean. you buy it one time and you own it forever. you can use it on all your stores. the app guys hate me for this. they want your money every month. i want you to win. i am giving away one of my top sections today. comment "win" below. i will send it to you. (you must follow me so i can send the link)

George

19,423 Aufrufe • vor 7 Monaten

I know you want a design team, and actually the best one - without the hassle of hiring or long-term commitments? That’s exactly what Kree8 is. Just book a Call, and let’s Kree8 it. 👇 We work like your in-house design team. You send in a task - one at a time or two simultaneously (your call), and we get it done. No chasing. No delays. Just clean, high-quality design delivered when you need it.
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I know you want a design team, and actually the best one - without the hassle of hiring or long-term commitments? That’s exactly what Kree8 is. Just book a Call, and let’s Kree8 it. 👇 We work like your in-house design team. You send in a task - one at a time or two simultaneously (your call), and we get it done. No chasing. No delays. Just clean, high-quality design delivered when you need it.

Jay Dwivedi

254,322 Aufrufe • vor 1 Jahr

Alright, now that we know *what* an agent is, how does it actually work? When you ask for help on a task, the agent plans a series of steps and executes them directly in the application on your behalf, using the tools it has access to. Say you are booking a local service or trying to organize your inbox (which typically takes multiple steps): the AI model first plans how to achieve the task using its existing knowledge and then interacts with your inbox to execute the task. The agent will continue until it is confident the task has been successfully completed.
0:15

Alright, now that we know *what* an agent is, how does it actually work? When you ask for help on a task, the agent plans a series of steps and executes them directly in the application on your behalf, using the tools it has access to. Say you are booking a local service or trying to organize your inbox (which typically takes multiple steps): the AI model first plans how to achieve the task using its existing knowledge and then interacts with your inbox to execute the task. The agent will continue until it is confident the task has been successfully completed.

Google AI

22,487 Aufrufe • vor 9 Monaten

sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓
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sorry, they just did WHAT someone gave a machine one disease name, the leading cause of blindness in the developed world with 1.5 million americans already in its path, and it came back pointing at a drug that has sat in pharmacies for years under a different label: 551 papers read in 30 minutes against the 294 hours a human would have needed, and the loop that did it is public on GitHub most agent setups answer one question at a time, so the ceiling on the work is the quality of the question you happened to think of this one was handed a single question and wrote the second one itself. turns out that follow-up is where the real find was: a target called ABCA1, upregulated threefold, in an experiment no human ordered i read the whole paper looking for the trick, and the trick is structural. that is the second question, and it is the gap between an assistant and a factory: - hand the loop a field rather than a task: it was given a disease, and choosing the mechanism was part of its job - make it rank before it spends: 151 papers in, ten candidate mechanisms out, scored against each other before anything touched a bench - split reading from judging, so the agent that forms the theory is a different agent from the one grading it - close every cycle on physical reality: the verdict was an experiment, and another model's opinion was never allowed to stand in for one - feed each result back as the next question rather than a log line, which is the step almost nobody builds - search what already passed inspection first: the winner was an approved compound with a safety file already on record - write down what the round learned before opening the next one, so round two starts where round one stopped my read, and i think it is the uncomfortable one: reading was the entire bottleneck in that field, and everybody spent the decade optimising the writing. people ran every physical experiment here, the analysis agent needs a domain expert writing its prompts, and the authors decline to call this the leap it resembles. the thinking got replaced, and the hands did not so the question i cannot answer for my own setup: which step of your loop still stops dead until you sit down and type something bookmark this one. the four parts that turn one model into a line that runs like this, the queue, the rooms, the write permissions and the gate, are built file by file in the piece below ↓

Argona

32,475 Aufrufe • vor 16 Tagen

"Heavy lifting is dangerous at your age" is the most harmful sentence in the field, and a doctor, a physio or a well-meaning relative hands it out every day. Follow it and watch what it does. From your forties you lose muscle every year unless you fight for it. That decline is the whole game: the difference between carrying your own shopping at 80 and waiting for someone to carry it for you. Muscle you don't load shrinks. Bone no longer pulled on turns brittle. Balance you never challenge drains away. Two years of "taking it easy" and you have built the exact frail body everyone feared. The advice didn't prevent the fall. It built the person who couldn't survive one. And here is the lie inside it. Supervised resistance training has one of the lowest injury rates of anything an older adult does. Lower than gardening. Lower than a wet pavement. Lower than the stairs you climb without thinking. So instead they steer you to pilates, aqua aerobics, a gentle tai chi class. Pleasant, sociable, and none of it loads a muscle hard enough to stop it wasting. You feel active while the decline rolls on regardless. Strength is not vanity at this age. It is the garden you kneel in, the stairs you keep, the grandchild you lift. Independence with the years added on. Frightened of a barbell? Fine. You don't need one. Machines are built for exactly this. Fixed path, nothing to wobble sideways. You sit, you're supported, you push. When a set gets hard you stop, and the machine holds the weight, not your spine. A leg press loads your legs as heavy as you'll ever need with almost no way to hurt yourself. Same with a chest press, a row, a pulldown. The decline is coming for everyone. You train against it or you hand years of your life away. The safest tool for the job sits unused in every gym, while the people who need it most get a rubber band and a spot in the church hall. Careful is what's killing them.
0:19

"Heavy lifting is dangerous at your age" is the most harmful sentence in the field, and a doctor, a physio or a well-meaning relative hands it out every day. Follow it and watch what it does. From your forties you lose muscle every year unless you fight for it. That decline is the whole game: the difference between carrying your own shopping at 80 and waiting for someone to carry it for you. Muscle you don't load shrinks. Bone no longer pulled on turns brittle. Balance you never challenge drains away. Two years of "taking it easy" and you have built the exact frail body everyone feared. The advice didn't prevent the fall. It built the person who couldn't survive one. And here is the lie inside it. Supervised resistance training has one of the lowest injury rates of anything an older adult does. Lower than gardening. Lower than a wet pavement. Lower than the stairs you climb without thinking. So instead they steer you to pilates, aqua aerobics, a gentle tai chi class. Pleasant, sociable, and none of it loads a muscle hard enough to stop it wasting. You feel active while the decline rolls on regardless. Strength is not vanity at this age. It is the garden you kneel in, the stairs you keep, the grandchild you lift. Independence with the years added on. Frightened of a barbell? Fine. You don't need one. Machines are built for exactly this. Fixed path, nothing to wobble sideways. You sit, you're supported, you push. When a set gets hard you stop, and the machine holds the weight, not your spine. A leg press loads your legs as heavy as you'll ever need with almost no way to hurt yourself. Same with a chest press, a row, a pulldown. The decline is coming for everyone. You train against it or you hand years of your life away. The safest tool for the job sits unused in every gym, while the people who need it most get a rubber band and a spot in the church hall. Careful is what's killing them.

Sama Hoole

14,532 Aufrufe • vor 1 Monat

1 Neural Network + Obsidian + Karpathy’s 1-file method = the most unhinged second brain build of 2026. It remembers everything you’ve ever done, and it costs $0 on top of what you already pay. The base is Karpathy’s append and review: 1 giant note, new thoughts stack on top, old ones sink, every few days you reread and pull the survivors back up. No folders, no tags, no plugins the rereading IS the system, because review is what turns storage into thinking. The flaw: past 10,000 lines, no human rereads anything. That’s where the neural network takes over. You keep the note in Obsidian 1 vault, everything dumps to the top: ideas, links, meeting fragments, half-thoughts. You never organize, you only dump. It all lives as plain markdown on your own disk, and that detail is the whole trick. Because now you point Claude Code at the vault folder, and it reads every line you’ve ever written. “What did I think about pricing in March.” “Find the 3 ideas I keep circling.” “What did I drop that deserves a second look.” It answers from YOUR notes, with quotes, in 15 seconds. Then once a week, 1 prompt closes the loop: read the last 7 days, surface the 5 entries worth pulling back up, flag anything that contradicts what I wrote a month ago. The model does the sinking and surfacing Karpathy did by hand, and the note stays alive instead of turning into a graveyard. Week 1 feels like nothing. Week 4 you hit the first “I already solved this in January.” Month 3 you consult your past self more than Google. Most second brains die in 11 days under 40 plugins and 200 folders. This one is 1 file and a loop, and it compounds because dumping takes 0 discipline. Notion stores what you thought. This thing argues back.
0:16

1 Neural Network + Obsidian + Karpathy’s 1-file method = the most unhinged second brain build of 2026. It remembers everything you’ve ever done, and it costs $0 on top of what you already pay. The base is Karpathy’s append and review: 1 giant note, new thoughts stack on top, old ones sink, every few days you reread and pull the survivors back up. No folders, no tags, no plugins the rereading IS the system, because review is what turns storage into thinking. The flaw: past 10,000 lines, no human rereads anything. That’s where the neural network takes over. You keep the note in Obsidian 1 vault, everything dumps to the top: ideas, links, meeting fragments, half-thoughts. You never organize, you only dump. It all lives as plain markdown on your own disk, and that detail is the whole trick. Because now you point Claude Code at the vault folder, and it reads every line you’ve ever written. “What did I think about pricing in March.” “Find the 3 ideas I keep circling.” “What did I drop that deserves a second look.” It answers from YOUR notes, with quotes, in 15 seconds. Then once a week, 1 prompt closes the loop: read the last 7 days, surface the 5 entries worth pulling back up, flag anything that contradicts what I wrote a month ago. The model does the sinking and surfacing Karpathy did by hand, and the note stays alive instead of turning into a graveyard. Week 1 feels like nothing. Week 4 you hit the first “I already solved this in January.” Month 3 you consult your past self more than Google. Most second brains die in 11 days under 40 plugins and 200 folders. This one is 1 file and a loop, and it compounds because dumping takes 0 discipline. Notion stores what you thought. This thing argues back.

West Lord

24,679 Aufrufe • vor 1 Monat

Jeff Bezos just told you exactly how to price AI. Nobody listened. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Three words that reprice the entire technology sector. The iPhone was a vertical. One product. One new market. Electricity was a horizontal. One substrate that rewired every market on Earth. Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid. Right now, thousands of companies are trying to sell AI as a product. A feature. A tool. A subscription tier. Every single one of them will be priced to zero. You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it. For a century, entire industries survived on one thing. Complexity. The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete. A horizontal layer does not navigate the maze. It dissolves the walls. Electricity did not compete with the candle industry. It erased the need for one. The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds. Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay. The internet repriced distribution. AI is repricing cognition itself. When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates. This is not a disruption. Disruptions replace products. This replaces the ground you are standing on.
0:16

Jeff Bezos just told you exactly how to price AI. Nobody listened. Bezos: “AI is real and it is going to change every industry. In fact it’s a very unusual technology in that regard in that it’s a horizontal enabling layer.” Horizontal enabling layer. Three words that reprice the entire technology sector. The iPhone was a vertical. One product. One new market. Electricity was a horizontal. One substrate that rewired every market on Earth. Wall Street is pricing AI like it is the next iPhone. Bezos is telling you it is the next electrical grid. Right now, thousands of companies are trying to sell AI as a product. A feature. A tool. A subscription tier. Every single one of them will be priced to zero. You do not sell a horizontal layer. You do not compete with it. You build on top of it or you disappear beneath it. For a century, entire industries survived on one thing. Complexity. The friction of navigating law, medicine, logistics, finance. That was the moat. If you could not memorize the maze, you could not compete. A horizontal layer does not navigate the maze. It dissolves the walls. Electricity did not compete with the candle industry. It erased the need for one. The most dangerous part of a horizontal shift is how quiet it is. It moves underneath the economy. The surface looks normal. Revenue still holds. Every day you operate on the old substrate, you accumulate a debt you cannot see and cannot repay. The internet repriced distribution. AI is repricing cognition itself. When intelligence becomes a utility that runs through the walls of every company on Earth, the premium on human expertise does not erode. It evaporates. This is not a disruption. Disruptions replace products. This replaces the ground you are standing on.

Dustin

541,893 Aufrufe • vor 4 Monaten

Coding software is a joke compared to building hardware. Because when a software fails, it can be fixed quickly. In hardware, one mistake can set you back for months or end you. In hardware, every decision is cash flow. Every tiny error can cost tens of 1000s of dollars. You don’t get second chances. You get lessons, paid for in time and money. But when you finally get it right… You don’t just ship a product. You build a legacy. Something people touch, use, and trust for years. That’s the beauty and the pain of building in the real world.
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Coding software is a joke compared to building hardware. Because when a software fails, it can be fixed quickly. In hardware, one mistake can set you back for months or end you. In hardware, every decision is cash flow. Every tiny error can cost tens of 1000s of dollars. You don’t get second chances. You get lessons, paid for in time and money. But when you finally get it right… You don’t just ship a product. You build a legacy. Something people touch, use, and trust for years. That’s the beauty and the pain of building in the real world.

Prakash Dadlani

12,402 Aufrufe • vor 9 Monaten

Marketers. I’m begging you. Stop prompting Claude 12+ times when it can be done in 1. Most marketers open Claude and start typing whatever comes to mind. Several rounds later, you’re editing mediocre output by hand. My team built a prompt auditing tool that reads your work, grades it, and gets you to 95% in minutes. It’s based on the RCTC framework, which answers the 4 questions Claude actually needs to be effective: Role - WHO is this for? Channel - WHERE is this going? Task - WHAT outcome is the output getting to? Constraints - WHAT bad output sounds like? Then automatically edits your work so you’re more effective in Claude, ChatGPT, or Gemini. Comment “GA” and I’ll send you the tool.
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Marketers. I’m begging you. Stop prompting Claude 12+ times when it can be done in 1. Most marketers open Claude and start typing whatever comes to mind. Several rounds later, you’re editing mediocre output by hand. My team built a prompt auditing tool that reads your work, grades it, and gets you to 95% in minutes. It’s based on the RCTC framework, which answers the 4 questions Claude actually needs to be effective: Role - WHO is this for? Channel - WHERE is this going? Task - WHAT outcome is the output getting to? Constraints - WHAT bad output sounds like? Then automatically edits your work so you’re more effective in Claude, ChatGPT, or Gemini. Comment “GA” and I’ll send you the tool.

Jesse Pujji

10,770 Aufrufe • vor 2 Monaten

I just built a Meta Ads diagnostic in Claude Code that tells you WHY your account broke, not just what changed 🤯 It spins up a team of agents that each investigate a different reason performance dropped, then argue against each other to kill the wrong answer before it ever reaches you. All inside Claude Code. Perfect for DTC brands and agencies who panic-kill creative the second CPA spikes. If you've watched ROAS fall off a cliff and opened Ads Manager with ten tabs going, you already know what happens next. Your gut says "creative fatigue." You kill your best-performing ad. A week later performance is still broken, because that was never the problem. Guessing wrong is the most expensive move in paid social. This workflow ends the guessing: → One agent investigates each competing theory — creative fatigue, budget and delivery changes, traffic quality, offer and seasonality → Each one is blind to the others, reasoning only from its own slice of the data so they can't bias each other → A refuter agent then attacks every surviving theory and tries to kill it → A theory only stands if the data can't disprove it → You get a ranked diagnosis: the real cause, the evidence for and against it, and the one move to make this week No anchoring on the first obvious answer. No killing winning creative on a hunch. No "here's what happened" reports that never tell you why. What you get: → Every theory tested in parallel instead of one biased guess → An adversarial pass that kills the wrong answer before you act on it → A ranked diagnosis with confidence levels and evidence both ways → A reusable workflow you drop next month's export into and re-run Built 100% in Claude Code with the new dynamic workflows. The first account I ran it on looked like textbook creative fatigue. The workflow disagreed, and traced the real cause to a budget change that had doubled spend and flooded delivery with junk traffic. I put together a full playbook with the exact workflow, the prompt, and how to run it on your own account. Want it for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)
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I just built a Meta Ads diagnostic in Claude Code that tells you WHY your account broke, not just what changed 🤯 It spins up a team of agents that each investigate a different reason performance dropped, then argue against each other to kill the wrong answer before it ever reaches you. All inside Claude Code. Perfect for DTC brands and agencies who panic-kill creative the second CPA spikes. If you've watched ROAS fall off a cliff and opened Ads Manager with ten tabs going, you already know what happens next. Your gut says "creative fatigue." You kill your best-performing ad. A week later performance is still broken, because that was never the problem. Guessing wrong is the most expensive move in paid social. This workflow ends the guessing: → One agent investigates each competing theory — creative fatigue, budget and delivery changes, traffic quality, offer and seasonality → Each one is blind to the others, reasoning only from its own slice of the data so they can't bias each other → A refuter agent then attacks every surviving theory and tries to kill it → A theory only stands if the data can't disprove it → You get a ranked diagnosis: the real cause, the evidence for and against it, and the one move to make this week No anchoring on the first obvious answer. No killing winning creative on a hunch. No "here's what happened" reports that never tell you why. What you get: → Every theory tested in parallel instead of one biased guess → An adversarial pass that kills the wrong answer before you act on it → A ranked diagnosis with confidence levels and evidence both ways → A reusable workflow you drop next month's export into and re-run Built 100% in Claude Code with the new dynamic workflows. The first account I ran it on looked like textbook creative fatigue. The workflow disagreed, and traced the real cause to a budget change that had doubled spend and flooded delivery with junk traffic. I put together a full playbook with the exact workflow, the prompt, and how to run it on your own account. Want it for free? > Like this post > Comment "META" And I'll send it over (must be following so I can DM)

Mike Futia

12,772 Aufrufe • vor 2 Monaten

THIS DEVELOPER OPENED HERMES ON A LAPTOP, SPENT $0 ON API SETUP, SAVED 7 WORKFLOWS, AND CUT 2-HOUR CLIENT TASKS DOWN TO 14 MINUTES he is not giving a polished demo. he is just filming the laptop while Hermes runs, and that is why the clip works. you can see the terminal, the workspace, the task history, and the moment a normal chat tool starts looking like a local operating layer most people still run AI like a vending machine: 1 prompt, 1 answer, 1 reset. Hermes is different. after 5-10 repeated jobs, the useful steps start living inside skills instead of getting rewritten every morning the money math is where it gets ugly. $20 for Claude, $40-90 in API usage, $50 for wrappers, $29 for automation tools, and you are already near $140-190/month before you even sell the first report he used the same flow for 9 small research tasks: 18 competitor pages, 126 review snippets, 9 pricing checks, 9 summary drafts. the first one took 43 minutes. later runs were mostly review, edit, send that is the part people miss about Hermes. it is not trying to win the prettiest chatbot contest. it is trying to make repeated work stop leaking out of the machine every time the session ends
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THIS DEVELOPER OPENED HERMES ON A LAPTOP, SPENT $0 ON API SETUP, SAVED 7 WORKFLOWS, AND CUT 2-HOUR CLIENT TASKS DOWN TO 14 MINUTES he is not giving a polished demo. he is just filming the laptop while Hermes runs, and that is why the clip works. you can see the terminal, the workspace, the task history, and the moment a normal chat tool starts looking like a local operating layer most people still run AI like a vending machine: 1 prompt, 1 answer, 1 reset. Hermes is different. after 5-10 repeated jobs, the useful steps start living inside skills instead of getting rewritten every morning the money math is where it gets ugly. $20 for Claude, $40-90 in API usage, $50 for wrappers, $29 for automation tools, and you are already near $140-190/month before you even sell the first report he used the same flow for 9 small research tasks: 18 competitor pages, 126 review snippets, 9 pricing checks, 9 summary drafts. the first one took 43 minutes. later runs were mostly review, edit, send that is the part people miss about Hermes. it is not trying to win the prettiest chatbot contest. it is trying to make repeated work stop leaking out of the machine every time the session ends

Gipp 🦅

14,593 Aufrufe • vor 2 Monaten