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you told it to double check its work that is the line making it worse current models verify without being asked, so your instruction lands on top of behaviour that already happened, and what you get is the same task run twice, billed twice, reported at twice the length... show more

Lagosaur

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14,673 просмотров • 9 дней назад •via X (Twitter)

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the docs said the caching is automatic, so you did nothing automatic is where it happens, not whether it happens the cache lives on the machine that built it, and your next request lands wherever the fleet sends it, which is usually not there, so it pays full price for a prefix it already paid to build there is a key that pins a conversation to one machine and it is a single header cached input is fifty cents a million against two dollars you never needed a smaller prompt you needed the request to land in the same place twice

the docs said the caching is automatic, so you did nothing automatic is where it happens, not whether it happens the cache lives on the machine that built it, and your next request lands wherever the fleet sends it, which is usually not there, so it pays full price for a prefix it already paid to build there is a key that pins a conversation to one machine and it is a single header cached input is fifty cents a million against two dollars you never needed a smaller prompt you needed the request to land in the same place twice

Lagosaur

16,892 просмотров • 3 дней назад

She went to prison for a murder that never happened. Double Jeopardy is the most satisfying movie ever made. 🔥 Is it true that You cannot be charged for the same crime twice?

She went to prison for a murder that never happened. Double Jeopardy is the most satisfying movie ever made. 🔥 Is it true that You cannot be charged for the same crime twice?

Cattermole

207,765 просмотров • 3 месяцев назад

$Roboflow charges you for models you have to verify yourself. Introducing Score Studio: the decentralised alternative where every model arrives already proven and ready to work in real world conditions. Every model on the platform is battle-tested through SN44's validation mechanism before you ever touch it. Miners compete, validators score, only the winners survive. You get the output of a permanent open competition, at a fraction of the price. Datasets, annotation, training, deployment. All of it cheaper. All of it validated, accurate and efficient. Need a model that doesn't exist yet? Launch your own model inquiry from the Studio and put the network to work on it. Pay in USD or SN44, straight at subnet level. We're putting the final touches on it now.$

Roboflow charges you for models you have to verify yourself. Introducing Score Studio: the decentralised alternative where every model arrives already proven and ready to work in real world conditions. Every model on the platform is battle-tested through SN44's validation mechanism before you ever touch it. Miners compete, validators score, only the winners survive. You get the output of a permanent open competition, at a fraction of the price. Datasets, annotation, training, deployment. All of it cheaper. All of it validated, accurate and efficient. Need a model that doesn't exist yet? Launch your own model inquiry from the Studio and put the network to work on it. Pay in USD or SN44, straight at subnet level. We're putting the final touches on it now.

Score

34,998 просмотров • 22 дней назад

your agent reviewing its own work is not a check. it is a second opinion from the same source. this is the most common gap in agent systems and it hides in plain sight, because the step exists. there is a review. it just cannot do the thing you think it does. here is the mechanism. the model produced an output from a context. you then ask the same model, holding the same context, whether that output is correct. it answers fluently, because that is what it does. and the answer is drawn from the same distribution that produced the thing being judged. same weights, same window, same blind spots. if the reason the output is wrong is something the model does not know, the review does not know it either. if the reason is something the context does not contain, the review has the same context. the failure mode and the detector share a cause. > why it feels like it works because most of the time the output is fine, and the review says fine. agreement is not evidence of detection. a reviewer that says pass on everything agrees with reality most of the time too. what you actually want to measure is what happens on the cases that are wrong. that is the only place a check earns its name, and it is exactly the place where a self-review is weakest. there is research on this. Huang and colleagues at DeepMind showed at ICLR 2024 that intrinsic self-correction, revising without external grounding, does not reliably help and often makes things worse. > what to actually do move the check outside the model. a test that runs, a schema that validates, a file that exists or does not, an exit code from something you did not write. these are not smarter than the model. they are just not correlated with it, and that is the entire value. when the judgement genuinely needs a model, at minimum use a different family. same family means shared blind spots, and frontier judges measurably inflate scores for outputs that look like their own. and split the work by kind. anything objectively checkable goes to code. only the genuinely semantic calls go to a judge, and those get a rubric written as one line. a review inside the loop tells you the model is confident. a check outside it tells you whether the work is done. save this - then read the eval setup below

your agent reviewing its own work is not a check. it is a second opinion from the same source. this is the most common gap in agent systems and it hides in plain sight, because the step exists. there is a review. it just cannot do the thing you think it does. here is the mechanism. the model produced an output from a context. you then ask the same model, holding the same context, whether that output is correct. it answers fluently, because that is what it does. and the answer is drawn from the same distribution that produced the thing being judged. same weights, same window, same blind spots. if the reason the output is wrong is something the model does not know, the review does not know it either. if the reason is something the context does not contain, the review has the same context. the failure mode and the detector share a cause. > why it feels like it works because most of the time the output is fine, and the review says fine. agreement is not evidence of detection. a reviewer that says pass on everything agrees with reality most of the time too. what you actually want to measure is what happens on the cases that are wrong. that is the only place a check earns its name, and it is exactly the place where a self-review is weakest. there is research on this. Huang and colleagues at DeepMind showed at ICLR 2024 that intrinsic self-correction, revising without external grounding, does not reliably help and often makes things worse. > what to actually do move the check outside the model. a test that runs, a schema that validates, a file that exists or does not, an exit code from something you did not write. these are not smarter than the model. they are just not correlated with it, and that is the entire value. when the judgement genuinely needs a model, at minimum use a different family. same family means shared blind spots, and frontier judges measurably inflate scores for outputs that look like their own. and split the work by kind. anything objectively checkable goes to code. only the genuinely semantic calls go to a judge, and those get a rubric written as one line. a review inside the loop tells you the model is confident. a check outside it tells you whether the work is done. save this - then read the eval setup below

Hanako

14,325 просмотров • 24 дней назад

FOR THOSE WHO ARE CONFUSED… We experience TIME as a straight line, one moment after another, PAST TO PRESENT TO FUTURE. But that is only how it appears from inside the system. Beings in higher dimensions, what some call “ORACLES” OR “GODS,” do not experience time like this. They do not move through it. They observe it in its entirety. A closer analogy would be CHANNELS ON A SCREEN. What is playing on FOX and what is playing on CBS is not separate in existence, it is only separated by perspective. Both are happening at the same time, fully active, fully real. In the same way, what we call 1950 and what we call 2004 are not distant points moving away from each other. They are both present within the same total field of reality. From that level of awareness, nothing is being “waited on.” There is NO DELAY. There is only ACCESS. A shift of perception is all that is needed, like changing the channel. So if everything exists at once, then your FUTURE is not something that is coming toward you. It is something that already exists. The version of you 20 YEARS FROM NOW is already there. You have already CHOSEN THAT PATH, you have already GONE THROUGH WHAT COMES WITH IT, you have already LIVED THROUGH IT ALL. And what you are doing now is not creating it. You are MOVING THROUGH IT. Slowly remembering why you are there at all.

FOR THOSE WHO ARE CONFUSED… We experience TIME as a straight line, one moment after another, PAST TO PRESENT TO FUTURE. But that is only how it appears from inside the system. Beings in higher dimensions, what some call “ORACLES” OR “GODS,” do not experience time like this. They do not move through it. They observe it in its entirety. A closer analogy would be CHANNELS ON A SCREEN. What is playing on FOX and what is playing on CBS is not separate in existence, it is only separated by perspective. Both are happening at the same time, fully active, fully real. In the same way, what we call 1950 and what we call 2004 are not distant points moving away from each other. They are both present within the same total field of reality. From that level of awareness, nothing is being “waited on.” There is NO DELAY. There is only ACCESS. A shift of perception is all that is needed, like changing the channel. So if everything exists at once, then your FUTURE is not something that is coming toward you. It is something that already exists. The version of you 20 YEARS FROM NOW is already there. You have already CHOSEN THAT PATH, you have already GONE THROUGH WHAT COMES WITH IT, you have already LIVED THROUGH IT ALL. And what you are doing now is not creating it. You are MOVING THROUGH IT. Slowly remembering why you are there at all.

THE VOICE 🌹 🗣🎙🇺🇸🦅🌎⚓💜♠️CHRIST CONSCIOUSNESS

40,362 просмотров • 2 месяцев назад

Over the weekend I finished the to-do list that does itself. Everytime you add a task, a GPT-4 agent is spawned to complete it. It already has the context it needs on you and your company, and has access to your apps. It’s called the Do Anything Machine (Link in thread)

Over the weekend I finished the to-do list that does itself. Everytime you add a task, a GPT-4 agent is spawned to complete it. It already has the context it needs on you and your company, and has access to your apps. It’s called the Do Anything Machine (Link in thread)

Garrett Scott 🕳

2,893,368 просмотров • 3 лет назад

"How do people learn to use Claude Code like Boris?" Claude Code creator Boris Cherny (Boris Cherny ) was asked by Diana Hu ( Diana ) at Startup School 2026. Boris Cherny: "Maybe don’t listen to the LinkedIn influencers. The thing about the model is that everyone is looking for one weird trick to make it work, but that simply doesn’t exist. There is nothing like that. You have to approach the model empirically. Give it a task that is too hard. Give it the tools to verify its work, just as you would use those tools yourself if you were doing the task. See where it struggles, and then fix the problem with better prompting, a skill, or if the model is missing context, an MCP connection that allows it to retrieve the context it needs. That is basically it. It sounds very simple. I think people tend to overthink and overengineer it because, in many ways, that is how we had to build systems in the past." ---- From "Y Combinator" YouTube channel, (full video link in comment)

"How do people learn to use Claude Code like Boris?" Claude Code creator Boris Cherny (Boris Cherny ) was asked by Diana Hu ( Diana ) at Startup School 2026. Boris Cherny: "Maybe don’t listen to the LinkedIn influencers. The thing about the model is that everyone is looking for one weird trick to make it work, but that simply doesn’t exist. There is nothing like that. You have to approach the model empirically. Give it a task that is too hard. Give it the tools to verify its work, just as you would use those tools yourself if you were doing the task. See where it struggles, and then fix the problem with better prompting, a skill, or if the model is missing context, an MCP connection that allows it to retrieve the context it needs. That is basically it. It sounds very simple. I think people tend to overthink and overengineer it because, in many ways, that is how we had to build systems in the past." ---- From "Y Combinator" YouTube channel, (full video link in comment)

Rohan Paul

55,255 просмотров • 1 месяц назад

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription

Kimi K3 dropped 3 days ago and i already used it to build my own PUBG the model that just took the number one coding spot on earth and it runs on a free tier no team no engine i just fed it free open models and assets that are already public and told it what i wanted it built the entire game itself the shooting the recoil the hit detection all of it came straight out of the model i barely wrote a line what youre watching here is the deathmatch mode and its already live battle royale is next im deep in it and the graphics get reworked right after i know it looks raw right now i wont pretend otherwise but the endgame is a build that runs perfect on phones and the moment its on mobile you drop ads in and it earns on its own the part that still gets me is my whole cost for this was a single subscription

savip.

68,984 просмотров • 1 месяц назад

you read it and pictured yourself approving instead of watching approving what five agents, each on its own machine, handing work down the line, and what reaches you at the end is the last one's account of the four accounts before it the honest part of that piece says you do not own the harness that is the exact layer where a check on any of this would have to live a hundred and twenty a seat, three hundred at the top, about six times what you pay now you are not buying the work you are buying a shorter story about the work, told by the only party that watched it happen

you read it and pictured yourself approving instead of watching approving what five agents, each on its own machine, handing work down the line, and what reaches you at the end is the last one's account of the four accounts before it the honest part of that piece says you do not own the harness that is the exact layer where a check on any of this would have to live a hundred and twenty a seat, three hundred at the top, about six times what you pay now you are not buying the work you are buying a shorter story about the work, told by the only party that watched it happen

Lagosaur

21,838 просмотров • 4 дней назад

Anthropic Claude Code engineer: "The moment you're reviewing every line Claude writes, you became its tester. You weren't hired for that." this 36 min talk is the clearest breakdown of how to get yourself out of the loop entirely the shift is simple: you stop prompting and start building agents that work instead of you agents that run, check themselves, and keep going while your laptop is closed watch it, then build your own with the step-by-step guide below

Anthropic Claude Code engineer: "The moment you're reviewing every line Claude writes, you became its tester. You weren't hired for that." this 36 min talk is the clearest breakdown of how to get yourself out of the loop entirely the shift is simple: you stop prompting and start building agents that work instead of you agents that run, check themselves, and keep going while your laptop is closed watch it, then build your own with the step-by-step guide below

Anatoli Kopadze

28,042 просмотров • 2 месяцев назад

you numbered the steps so it could not get lost it does not get lost that list was written for a model that wandered, and this one plans better than the list does, so every number you added is a place where it is no longer allowed, to be smarter than you state the goal, the constraints, and how you will know it worked keep the numbers only where exactly one sequence is safe, which is deletes, auth and compliance the procedure felt like rigour it is a cage built to the dimensions of a model that is not in the room

you numbered the steps so it could not get lost it does not get lost that list was written for a model that wandered, and this one plans better than the list does, so every number you added is a place where it is no longer allowed, to be smarter than you state the goal, the constraints, and how you will know it worked keep the numbers only where exactly one sequence is safe, which is deletes, auth and compliance the procedure felt like rigour it is a cage built to the dimensions of a model that is not in the room

Lagosaur

14,857 просмотров • 7 дней назад

This is some of my favorite advice from Jamie Dimon on how to build a successful career From his commencement speech to the HBS MBA Class of 2009 "There is already a book on you. That book is already being written. And if I spoke to your teachers, your friends, your parents, I would know whether you are trusted, how hard you work, and whether you are ethical I would know so much about you that you would be shocked. I dont even have to meet you So that book is already growing. You write the book the way you want it to be written. You actually have that choice. Do not let others write it."

This is some of my favorite advice from Jamie Dimon on how to build a successful career From his commencement speech to the HBS MBA Class of 2009 "There is already a book on you. That book is already being written. And if I spoke to your teachers, your friends, your parents, I would know whether you are trusted, how hard you work, and whether you are ethical I would know so much about you that you would be shocked. I dont even have to meet you So that book is already growing. You write the book the way you want it to be written. You actually have that choice. Do not let others write it."

Boring_Business

339,342 просмотров • 7 месяцев назад

ANTHROPIC LEAKED A SETUP WHERE ONE FILE STARTS 7 LOOPS THAT TURN A PROMPT INTO A WORKING BUSINESS AI engineer drops in 1 file - the other 95% of the work closes automatically without them. spec → tasks → code → tests → docs → release → monitoring → back into the spec you don't write tickets anymore - you write the thing tickets get derived from, and Opus 5 cuts the spec into 6 tasks by itself. a task that fails its test comes back to itself, not to you - and runs a second lap without a single notification. 6 lanes of code run in parallel and none of them wait on you - the critic filters the diff before you ever open it. every new production bug becomes a permanent line in the eval set - the system never steps on it twice. monitoring isn't the end of the line, it's the start of the next spec - those back edges are what make it a graph instead of a conveyor. and one place is left where you say yes - release, 5 minutes instead of 5 hours. save this and paste it into Claude Code - and you get 7 loops that run without you ↓

ANTHROPIC LEAKED A SETUP WHERE ONE FILE STARTS 7 LOOPS THAT TURN A PROMPT INTO A WORKING BUSINESS AI engineer drops in 1 file - the other 95% of the work closes automatically without them. spec → tasks → code → tests → docs → release → monitoring → back into the spec you don't write tickets anymore - you write the thing tickets get derived from, and Opus 5 cuts the spec into 6 tasks by itself. a task that fails its test comes back to itself, not to you - and runs a second lap without a single notification. 6 lanes of code run in parallel and none of them wait on you - the critic filters the diff before you ever open it. every new production bug becomes a permanent line in the eval set - the system never steps on it twice. monitoring isn't the end of the line, it's the start of the next spec - those back edges are what make it a graph instead of a conveyor. and one place is left where you say yes - release, 5 minutes instead of 5 hours. save this and paste it into Claude Code - and you get 7 loops that run without you ↓

Sprytix

66,333 просмотров • 19 дней назад

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓

Elon Musk, absolute leader of the AI race with Grok Bot, and it's not a joke anymore. Ultimate guide on god-mode setup of Grok Bot, the org chart that runs while you sleep, step by step: A Chief of Staff sits in the middle with no tools of its own, BUT it reads the outcome you gave it, picks who does what, and never does the work itself. That one rule is why it never turns into the bottleneck you hired it to remove. → Researcher pulls real sources and tracks what's actually moving, not what sounds true → Writer turns that into finished copy while the research is still in the room → Visualiser gets three reference visuals once, then ships everything in that style forever → Analyst reads what performed and tells the rest of the team what to stop doing → Scheduler owns timing and holds the queue → Publisher actually ships What makes it different from every AI tool you've used: each bot gets its own computer in the cloud, its own browser, its own files, and they all share one memory. So the research is already sitting inside the draft before the draft starts. Nothing gets copy-pasted between tabs, nothing waits on you to approve step four of nine. And you never write a workflow for it. You hit record, do the job once the way you actually do it, stop. It pulls out the steps, saves them as a skill, and puts it on a schedule. The shape you're aiming for on every bot: everything reversible finished, nothing sent. 36 drafts queued, 0 published. It does all the work and stops dead at the one line only you can cross. You stop prompting. You start assigning. Full charter blocks, the approval line and the routines are in the article below ↓

Miraqle

85,476 просмотров • 10 дней назад

Persi Diaconis walked into a lecture at the University of Washington, held up a coin, and told a room of physicists that Richard Feynman was fooled by it his entire life. He was right. In 2007, Diaconis proved a coin flip is not 50/50. It lands on the side it started on about 51 percent of the time. The bias comes from the physics of rotation under gravity. Every physicist since Newton had assumed 50/50 without ever testing it. Every trading model built on that assumption is running on the same lie. The lecture was on Feynman's book "The Meaning of it All." Diaconis quoted the most famous line in it: "the first principle is that you must not fool yourself, and you are the easiest person to fool." Then he pointed out that Feynman himself was fooled by every coin he ever flipped. Feynman's own rule would have killed the 50/50 assumption on day one. The market is the same setup at scale. Every model that assumes independent 50/50 outcomes at the base layer is built on a physical impossibility. Order flow, positioning, forced flows, expiries all leave biases larger than 1 percent. Your gut cannot see them. The math already knows they are there. Diaconis's rule: before you trust a random process, check it. Actually check it. Not with a simulation. With a proof or an experiment. The coin is where you start. The chart is where the same rule pays. The only random thing about markets is how thoroughly you refuse to check them.

Persi Diaconis walked into a lecture at the University of Washington, held up a coin, and told a room of physicists that Richard Feynman was fooled by it his entire life. He was right. In 2007, Diaconis proved a coin flip is not 50/50. It lands on the side it started on about 51 percent of the time. The bias comes from the physics of rotation under gravity. Every physicist since Newton had assumed 50/50 without ever testing it. Every trading model built on that assumption is running on the same lie. The lecture was on Feynman's book "The Meaning of it All." Diaconis quoted the most famous line in it: "the first principle is that you must not fool yourself, and you are the easiest person to fool." Then he pointed out that Feynman himself was fooled by every coin he ever flipped. Feynman's own rule would have killed the 50/50 assumption on day one. The market is the same setup at scale. Every model that assumes independent 50/50 outcomes at the base layer is built on a physical impossibility. Order flow, positioning, forced flows, expiries all leave biases larger than 1 percent. Your gut cannot see them. The math already knows they are there. Diaconis's rule: before you trust a random process, check it. Actually check it. Not with a simulation. With a proof or an experiment. The coin is where you start. The chart is where the same rule pays. The only random thing about markets is how thoroughly you refuse to check them.

veles

18,798 просмотров • 1 месяц назад

you added a second model to check the first one it never opened the repository what you handed it was the summary, so what it reviewed was a paragraph, and the paragraph was written by something fluent, which is why it reads as plausible two models agreeing about a sentence is not verification it is a second opinion on the writing give the reviewer a shell and the tests instead a verifier holding a paragraph is doing literary criticism

you added a second model to check the first one it never opened the repository what you handed it was the summary, so what it reviewed was a paragraph, and the paragraph was written by something fluent, which is why it reads as plausible two models agreeing about a sentence is not verification it is a second opinion on the writing give the reviewer a shell and the tests instead a verifier holding a paragraph is doing literary criticism

Lagosaur

28,822 просмотров • 6 дней назад

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.

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 просмотров • 3 месяцев назад

AOC on Inflation: It’s not easy to just find a cheaper apartment when every apartment or every home in your area is the same unaffordable price. And so what is so challenging about this is that this isn’t just like going to the grocery store and buying the generic cereal and switching over. How do you actually accommodate when you can’t afford medicine, when you can’t afford your housing? This is a crisis… MacFarlane: Do you think the administration is taking it seriously? AOC: No, they’re making it worse because what the Trump administration is doing is entering sweetheart deal after sweetheart deal, whether it’s with Monsanto and our food supply with glyphosate, whether it’s housing, whether it’s, you know, these crypto agents that are engaged in money laundering—I think at least. I think they are not only ignoring it, they see it and they are actively making it worse. And what they think is that people are too dumb to understand what it is that they’re doing. They’re banking on the fact that people will support them no matter what and that nothing will change that support. And I think that what is really important is for every voter, regardless of your background or your party or whatever it is, to understand what’s your line and what is acceptable to you.

AOC on Inflation: It’s not easy to just find a cheaper apartment when every apartment or every home in your area is the same unaffordable price. And so what is so challenging about this is that this isn’t just like going to the grocery store and buying the generic cereal and switching over. How do you actually accommodate when you can’t afford medicine, when you can’t afford your housing? This is a crisis… MacFarlane: Do you think the administration is taking it seriously? AOC: No, they’re making it worse because what the Trump administration is doing is entering sweetheart deal after sweetheart deal, whether it’s with Monsanto and our food supply with glyphosate, whether it’s housing, whether it’s, you know, these crypto agents that are engaged in money laundering—I think at least. I think they are not only ignoring it, they see it and they are actively making it worse. And what they think is that people are too dumb to understand what it is that they’re doing. They’re banking on the fact that people will support them no matter what and that nothing will change that support. And I think that what is really important is for every voter, regardless of your background or your party or whatever it is, to understand what’s your line and what is acceptable to you.

Acyn

73,772 просмотров • 2 месяцев назад

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

this video is the CLEAREST explanation of how claude skills + AI agents work and how to use them most people set up an AI agent and wonder why it keeps disappointing them. the context window is everything context is what the model assembles before it takes any action. think of it like everything the agent needs to read before it does anything. the quality of what goes in determines the quality of what comes out. the models are genuinely really good right now. claude and gpt are exceptional. the variable is almost always the context you give them. 1. agent.md files are mostly unnecessary every single line you put in an agent.md file gets added to every single conversation you have with your agent. a 1000 line file is around 7000 tokens burning on every run. the model already knows to use react. it can read your codebase. save the agent.md for proprietary information specific to your company that the model genuinely cannot know on its own. 2. skills are the actual unlock a skill.md file works differently. what loads into context is only the name and description, around 50 tokens. the full instructions only appear when the agent recognizes it needs that skill. so instead of 7000 tokens on every run you have 50. and the agent stays sharp because the context window stays lean. the closer you get to filling the context window the worse the agent performs, same way you perform worse when someone dumps 10 things on you at once. 3. here is how to actually build a skill the right way most people identify a workflow and immediately try to write the skill. what you want to do instead is run the workflow by hand with the agent first. walk it through every single step. tell it what to check, what good looks like, what bad looks like. correct it in real time. once you have had a full successful run from start to finish, tell the agent to review everything it just did and write the skill itself. it writes a better skill than you will because it has the full context of what actually worked in practice not in theory. 4. recursively building skills is how you go from frustrated to reliable when the skill breaks, and it will break, ask the agent exactly why it failed. it will tell you specifically what went wrong. fix it together in that same conversation. then tell it to update the skill file so that failure mode never happens again. ross mike did this five times with his youtube report generator. it now pulls from eight different data sources and runs flawlessly every single time without him touching it. 5. sub agents are something you earn not something you set up on day one start with one agent. build one workflow. turn it into one skill. once that works add another. ross mike has five sub agents now covering marketing, business, personal and more. it took months to get there and every single one exists because a workflow proved it deserved to exist. the people who set up 15 sub agents on day one and wonder why nothing works skipped all the steps that make the thing actually run. 6. your workflow is the thing the model cannot get anywhere else the model has been trained on everything. it knows more than you about most things. what it does not have is your specific process, your taste, your way of doing things. that is what skills capture. that is what makes your agent actually useful versus a generic one. downloading someone else's skill means downloading their context onto your setup and it will not work the way you want it to because it was never built around how you work. this is the clearest explanation of how agents actually work i have heard. Micky runs this stuff every single day and the results show it. full episode is now live on The Startup Ideas Podcast (SIP) 🧃 where you get your pods people charge for this sorta stuff i give away the sauce for free i just want you to win watch

GREG ISENBERG

193,721 просмотров • 4 месяцев назад

You know what’s really frustrating about this? The fact that we’ve already paid for that food and it should be given to them and now we’re paying for it twice. This is Trump‘s America.

You know what’s really frustrating about this? The fact that we’ve already paid for that food and it should be given to them and now we’re paying for it twice. This is Trump‘s America.

MAGA Cult Slayer🦅🇺🇸

34,906 просмотров • 9 месяцев назад