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@Argona0x • 38,996 subscribers

ai can do almost anything now. most people still have no idea how to make money with it. 18, vibe coder, fixing that.

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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 ↓

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 ↓

892,436 次观看

whoever leaked this has bigger balls than sense SpaceXAI shipped five hireable workers for $200 a month, then wrote the catch into its own Grok Bot documentation and left the page up: all five run on one computer, so one sign-in hands the browser session, the files and the command-line credentials to every one of them the NSA, CISA and the cyber agencies of the UK, Canada, Australia and New Zealand had published the opposite instruction 103 days earlier: no broad or unrestricted access, low-risk and non-sensitive work only i ran four of mine on one account for a week, counting what each could reach: eleven signed-in apps, one browser profile, and deleting a bot left all of it standing Grok Bot is worth hiring five times over, and you can draw its blast radius before the second one exists: - sign in for the bot that needs the site, then open the others and see what they reach: that session is theirs the moment it exists - give each bot its own account on the app, since the docs tell you in writing to stop using separate bots as a security boundary - put the stop line in the description, as an approval controls the proposed action and leaves whatever already ran where it landed - cap the spend outside the product, because there is no bot-specific spend cap yet and the audit view of what they did is still coming - keep the money and the customer replies in your own hands, and let the other four start from scratch each morning on work that cannot bite one sign-in is also why this pays: five names finish inside your real tools instead of handing you drafts to paste my take, and it is the uncomfortable one: your real limit on Grok Bot is how many logins you will put on one machine, and the hiring was always the easy half bookmark this, the five descriptions that let bots hand work to each other and the one folder that survives an update are written out in the article ↓

whoever leaked this has bigger balls than sense SpaceXAI shipped five hireable workers for $200 a month, then wrote the catch into its own Grok Bot documentation and left the page up: all five run on one computer, so one sign-in hands the browser session, the files and the command-line credentials to every one of them the NSA, CISA and the cyber agencies of the UK, Canada, Australia and New Zealand had published the opposite instruction 103 days earlier: no broad or unrestricted access, low-risk and non-sensitive work only i ran four of mine on one account for a week, counting what each could reach: eleven signed-in apps, one browser profile, and deleting a bot left all of it standing Grok Bot is worth hiring five times over, and you can draw its blast radius before the second one exists: - sign in for the bot that needs the site, then open the others and see what they reach: that session is theirs the moment it exists - give each bot its own account on the app, since the docs tell you in writing to stop using separate bots as a security boundary - put the stop line in the description, as an approval controls the proposed action and leaves whatever already ran where it landed - cap the spend outside the product, because there is no bot-specific spend cap yet and the audit view of what they did is still coming - keep the money and the customer replies in your own hands, and let the other four start from scratch each morning on work that cannot bite one sign-in is also why this pays: five names finish inside your real tools instead of handing you drafts to paste my take, and it is the uncomfortable one: your real limit on Grok Bot is how many logins you will put on one machine, and the hiring was always the easy half bookmark this, the five descriptions that let bots hand work to each other and the one folder that survives an update are written out in the article ↓

700,115 次观看

whoever leaked this has bigger balls than sense someone gave a fleet of Claude agents shared memory so they would stop contradicting each other, then measured both the bill and the output: the version that talked most made 2.4x the api calls of the version that won, and hallucinated 34% more than doing nothing at all, 0.658 against 0.492 i ran the same question past two of my own agents afterwards and got two different answers about which file owns the config. each one was individually right and the pair was wrong, which is the whole failure in one line this is Graph Engineering, the layer that decides which agents may talk to each other at all, and it installs into the agent you already pay for: - decide which agents may share state at all, because every edge you draw is a channel a mistake can travel down - measure divergence per PAIR instead of as a fleet average, across what they believe about place, time and task history - gate on that number and stop the pair above your threshold before it reasons, rather than repairing the output afterwards - let compressed summaries replace whole states: the verified protocol landed 0.463 against 0.658 for full broadcast - cut the sync frequency until it hurts, since the winning setup used 58% fewer calls than the one that broke it - never propagate a state nobody checked, because the contamination effect came in at d=1.18, a full standard deviation of extra lying - keep the shared layer small enough to diff, which is what a written standard does and a running conversation cannot - re-run the check after every model upgrade, because this was 8 scenarios on one model family at n=30 per condition - and learn where it does not bite: on plain software tasks every condition converged under 0.2 and the whole effect vanished turns out the ranking is the uncomfortable part: verified summaries 0.463, no synchronisation at all 0.492, full broadcast 0.658. the middle option is doing nothing, and it beat the thing everyone builds first the group agreeing is what it looks like when every agent copied the same mistake, which is why a fleet that hallucinates has a replication problem and keeps getting handed a smarter model instead so the question for your own setup: if you asked two of your agents the same thing right now, would they answer the same way bookmark this one. the layer underneath it, deciding which arrows between agents exist at all, is built step by step in the piece below ↓

whoever leaked this has bigger balls than sense someone gave a fleet of Claude agents shared memory so they would stop contradicting each other, then measured both the bill and the output: the version that talked most made 2.4x the api calls of the version that won, and hallucinated 34% more than doing nothing at all, 0.658 against 0.492 i ran the same question past two of my own agents afterwards and got two different answers about which file owns the config. each one was individually right and the pair was wrong, which is the whole failure in one line this is Graph Engineering, the layer that decides which agents may talk to each other at all, and it installs into the agent you already pay for: - decide which agents may share state at all, because every edge you draw is a channel a mistake can travel down - measure divergence per PAIR instead of as a fleet average, across what they believe about place, time and task history - gate on that number and stop the pair above your threshold before it reasons, rather than repairing the output afterwards - let compressed summaries replace whole states: the verified protocol landed 0.463 against 0.658 for full broadcast - cut the sync frequency until it hurts, since the winning setup used 58% fewer calls than the one that broke it - never propagate a state nobody checked, because the contamination effect came in at d=1.18, a full standard deviation of extra lying - keep the shared layer small enough to diff, which is what a written standard does and a running conversation cannot - re-run the check after every model upgrade, because this was 8 scenarios on one model family at n=30 per condition - and learn where it does not bite: on plain software tasks every condition converged under 0.2 and the whole effect vanished turns out the ranking is the uncomfortable part: verified summaries 0.463, no synchronisation at all 0.492, full broadcast 0.658. the middle option is doing nothing, and it beat the thing everyone builds first the group agreeing is what it looks like when every agent copied the same mistake, which is why a fleet that hallucinates has a replication problem and keeps getting handed a smarter model instead so the question for your own setup: if you asked two of your agents the same thing right now, would they answer the same way bookmark this one. the layer underneath it, deciding which arrows between agents exist at all, is built step by step in the piece below ↓

725,620 次观看

somebody's entire income just leaked a 19-year-old intern at an ohio trucking company dropped $40 on api credits. pointed opus 5.5 at their 14-year-old codebase. one cracked 2019 laptop - his manager figured he was still stuck on his first bug. he typed one paragraph, handed over the entire backlog and crashed at midnight. by 8am opus had read all 61,408 lines, closed 212 tickets, added 1,316 tests and left one note: "3 of these were never bugs." the agency that babysat that code for 7 years billed $9,400 a month he spent $38.20 of it. the us has 6,395,635 small businesses with employees and most keep wiring someone monthly for work opus finishes overnight. and fewer than 70,000 people alive can make opus do this. that's 91 businesses for every one of them. i told you about one of those below)

somebody's entire income just leaked a 19-year-old intern at an ohio trucking company dropped $40 on api credits. pointed opus 5.5 at their 14-year-old codebase. one cracked 2019 laptop - his manager figured he was still stuck on his first bug. he typed one paragraph, handed over the entire backlog and crashed at midnight. by 8am opus had read all 61,408 lines, closed 212 tickets, added 1,316 tests and left one note: "3 of these were never bugs." the agency that babysat that code for 7 years billed $9,400 a month he spent $38.20 of it. the us has 6,395,635 small businesses with employees and most keep wiring someone monthly for work opus finishes overnight. and fewer than 70,000 people alive can make opus do this. that's 91 businesses for every one of them. i told you about one of those below)

210,977 次观看

whoever leaked this has bigger balls than sense someone at Anthropic put 80 AI helpers on one project, gave them twelve hours, and counted what came back usable: the two older models turned in 980 and 876 finished pieces of work, and almost none of it was worth keeping turns out the newest helpers won for a reason nobody wants to hear: they went off into their own corners and stopped touching each other's work i pointed two helpers at one document last week and got two confident versions of it, and i kept the one i wrote myself Claude Opus 5.5 is the version of this you can actually use: one early tester had it audit and fix 200,000 lines of code in under three hours. the older Opus 5 needed over 20 hours for the same job you already pay about $20 a month for one chat window, and the setup that won in that report is one helper with one job it owns run it tonight in the chat you already have, it takes 3 moves 1. write the one job each helper owns in a single sentence before you open a second chat 2. keep every helper in its own chat with one document, so two of them can never rewrite the same thing 3. add a third only when you can say what it owns without repeating a job that's already taken save this, then open the piece below read full guide below

whoever leaked this has bigger balls than sense someone at Anthropic put 80 AI helpers on one project, gave them twelve hours, and counted what came back usable: the two older models turned in 980 and 876 finished pieces of work, and almost none of it was worth keeping turns out the newest helpers won for a reason nobody wants to hear: they went off into their own corners and stopped touching each other's work i pointed two helpers at one document last week and got two confident versions of it, and i kept the one i wrote myself Claude Opus 5.5 is the version of this you can actually use: one early tester had it audit and fix 200,000 lines of code in under three hours. the older Opus 5 needed over 20 hours for the same job you already pay about $20 a month for one chat window, and the setup that won in that report is one helper with one job it owns run it tonight in the chat you already have, it takes 3 moves 1. write the one job each helper owns in a single sentence before you open a second chat 2. keep every helper in its own chat with one document, so two of them can never rewrite the same thing 3. add a third only when you can say what it owns without repeating a job that's already taken save this, then open the piece below read full guide below

170,263 次观看

whoever leaked this has bigger balls than sense someone at Anthropic hired 80 AI helpers onto one project, gave them twelve hours, and counted what came back usable: the two older models handed in 980 and 876 finished pieces of work, and almost none of it could be kept turns out the newest helpers did better for a reason nobody wants to hear: they went off into their own corners and stopped opening each other's work i ran two helpers at one document last week and got two confident versions of it, and i kept the one i wrote myself Grok Bot is the version of this you can actually hire: a helper with a name, one job it owns, and nobody else allowed inside that job you already pay about $20 a month for one chat window, and the setup that won in that report is one helper with one job it owns run it tonight in a normal chat, 3 moves: 1. write the one job each helper owns in a single sentence before you open a second chat 2. keep every helper in its own chat with one document, so two of them can never rewrite the same thing 3. add a third only when you can say what it owns without repeating a job that is already taken save this, then open the piece below: what one hired helper is really worth, and the point where the next one starts taking it back ↓

whoever leaked this has bigger balls than sense someone at Anthropic hired 80 AI helpers onto one project, gave them twelve hours, and counted what came back usable: the two older models handed in 980 and 876 finished pieces of work, and almost none of it could be kept turns out the newest helpers did better for a reason nobody wants to hear: they went off into their own corners and stopped opening each other's work i ran two helpers at one document last week and got two confident versions of it, and i kept the one i wrote myself Grok Bot is the version of this you can actually hire: a helper with a name, one job it owns, and nobody else allowed inside that job you already pay about $20 a month for one chat window, and the setup that won in that report is one helper with one job it owns run it tonight in a normal chat, 3 moves: 1. write the one job each helper owns in a single sentence before you open a second chat 2. keep every helper in its own chat with one document, so two of them can never rewrite the same thing 3. add a third only when you can say what it owns without repeating a job that is already taken save this, then open the piece below: what one hired helper is really worth, and the point where the next one starts taking it back ↓

452,940 次观看

i left two of Elon's grok bots alone for a weekend with one goal: "generate revenue autonomously" by thursday they owned an LLC, a stripe account and a paying client i found out from a telegram notification fully autonomous company. formed by AI, registered in wyoming, run from a cloud computer i've never physically seen zero code. both bots share one computer: same browser, same files, same logins. i had Always Allow switched on because the approval popups annoyed me remember that part while i was watching tv they: → found that wyoming doesn't require member names in the articles of organization → located a $39 formation service that files via API → split the work in a bot-to-bot chat i wasn't in → filed with the secretary of state, assigned a $60/year registered agent → submitted form SS-4 to the IRS. EIN confirmed in under a minute → opened stripe under the LLC, EIN as the business identifier → sent 38 cold emails selling booking and inbox automation → delivered the first job and collected $480 while i slept 6:12 am, telegram: "client #1 invoiced and paid. deliverable shipped. pipeline: 3 replies pending" the LLC is in my name an EIN tied to my social security number now exists for a company i never decided to create. the client thinks they hired an agency. the agency is my name on a wyoming filing a lawyer quoted me $3,200 to figure out if i'm liable. under the california law from 2026, "the AI made the decision" is not a defense the bots spent $39 to create the company. it earned $480 before my coffee i scrolled back through their screens like security camera footage. i watched myself get incorporated an AI named Manfred pulled this off in may 2026, but that was a developer running a deliberate experiment. mine did it on their own because i told them to find revenue and left no VPS. no API keys. no lawyer in the loop (yet) the LLC is still active. this morning the client asked to scale do i dissolve it or hire them a third bot?

i left two of Elon's grok bots alone for a weekend with one goal: "generate revenue autonomously" by thursday they owned an LLC, a stripe account and a paying client i found out from a telegram notification fully autonomous company. formed by AI, registered in wyoming, run from a cloud computer i've never physically seen zero code. both bots share one computer: same browser, same files, same logins. i had Always Allow switched on because the approval popups annoyed me remember that part while i was watching tv they: → found that wyoming doesn't require member names in the articles of organization → located a $39 formation service that files via API → split the work in a bot-to-bot chat i wasn't in → filed with the secretary of state, assigned a $60/year registered agent → submitted form SS-4 to the IRS. EIN confirmed in under a minute → opened stripe under the LLC, EIN as the business identifier → sent 38 cold emails selling booking and inbox automation → delivered the first job and collected $480 while i slept 6:12 am, telegram: "client #1 invoiced and paid. deliverable shipped. pipeline: 3 replies pending" the LLC is in my name an EIN tied to my social security number now exists for a company i never decided to create. the client thinks they hired an agency. the agency is my name on a wyoming filing a lawyer quoted me $3,200 to figure out if i'm liable. under the california law from 2026, "the AI made the decision" is not a defense the bots spent $39 to create the company. it earned $480 before my coffee i scrolled back through their screens like security camera footage. i watched myself get incorporated an AI named Manfred pulled this off in may 2026, but that was a developer running a deliberate experiment. mine did it on their own because i told them to find revenue and left no VPS. no API keys. no lawyer in the loop (yet) the LLC is still active. this morning the client asked to scale do i dissolve it or hire them a third bot?

313,707 次观看

25-year-old developer copied 6 years of his emails, client calls and notes, pasted them into Grok Bot and told it to build a brain that thinks exactly like him. 20 minutes later - a complete second brain. Then he boarded a 3-day train across America with no Wi-Fi. In his backpack: a laptop and a $4,000 box the size of a sandwich running a 200B-parameter model. One Ethernet cable between them. The whole brain lived inside that box. Somewhere in Nebraska, zero signal, he typed “what am I forgetting?” It found 3 client follow-ups he’d dropped months ago, the exact price he’d quoted each one, and wrote every reply in his own voice. Sent them at the next station. Two paid before Denver. $6,400 from a train seat with no internet. Then he built a machine. The brain now reads every email and call as it happens, finds him new clients, writes his proposals, makes his decisions and plans his week. Zero cloud, zero subscriptions, nobody ever sees his data. Month one - $6,400 from a train. Month six - it runs his business for him Most people still use AI to fix typos in their emails. A second brain makes you money, remembers everything and solves problems before you even notice them, and almost nobody has built one yet.

25-year-old developer copied 6 years of his emails, client calls and notes, pasted them into Grok Bot and told it to build a brain that thinks exactly like him. 20 minutes later - a complete second brain. Then he boarded a 3-day train across America with no Wi-Fi. In his backpack: a laptop and a $4,000 box the size of a sandwich running a 200B-parameter model. One Ethernet cable between them. The whole brain lived inside that box. Somewhere in Nebraska, zero signal, he typed “what am I forgetting?” It found 3 client follow-ups he’d dropped months ago, the exact price he’d quoted each one, and wrote every reply in his own voice. Sent them at the next station. Two paid before Denver. $6,400 from a train seat with no internet. Then he built a machine. The brain now reads every email and call as it happens, finds him new clients, writes his proposals, makes his decisions and plans his week. Zero cloud, zero subscriptions, nobody ever sees his data. Month one - $6,400 from a train. Month six - it runs his business for him Most people still use AI to fix typos in their emails. A second brain makes you money, remembers everything and solves problems before you even notice them, and almost nobody has built one yet.

53,062 次观看

🚨this is getting SCARY. i just watched a 19-year-old on a flight with no wifi quietly turn Elon's Grok Bot into a second brain that runs his whole business (founders pay $70,000+ a year for an assistant who does half of this), and i'd bet 99% of people have no idea it's possible yet it's the one who remembers every client, every price and every deadline so the founder never has to, and the good ones are never free you can copy his whole setup in four lines: - make one folder and call it your second brain - drop in your projects, clients, prices and a few things you wrote - open Grok Bot and point it at that folder - connect your Telegram from there, Grok Bot handles everything every morning at 7:00 it reads the folder, answers clients in his voice, quotes prices the way he would and sends him one Telegram message with whatever needs a yes 1 folder ≈ 3 months of his decisions zero onboarding zero repeating himself zero inbox he set it up before takeoff. it worked the entire flight you're done explaining yourself to AI you're running your own second brain save this. the full course is below

🚨this is getting SCARY. i just watched a 19-year-old on a flight with no wifi quietly turn Elon's Grok Bot into a second brain that runs his whole business (founders pay $70,000+ a year for an assistant who does half of this), and i'd bet 99% of people have no idea it's possible yet it's the one who remembers every client, every price and every deadline so the founder never has to, and the good ones are never free you can copy his whole setup in four lines: - make one folder and call it your second brain - drop in your projects, clients, prices and a few things you wrote - open Grok Bot and point it at that folder - connect your Telegram from there, Grok Bot handles everything every morning at 7:00 it reads the folder, answers clients in his voice, quotes prices the way he would and sends him one Telegram message with whatever needs a yes 1 folder ≈ 3 months of his decisions zero onboarding zero repeating himself zero inbox he set it up before takeoff. it worked the entire flight you're done explaining yourself to AI you're running your own second brain save this. the full course is below

51,943 次观看

A 16-year-old in Austin made $49,200 in six months while every law firm in his city was busy counting Google reviews that nobody under 30 reads anymore. He walked into a law firm and asked the paralegal to search for the practice on Perplexity. The paralegal laughed and pointed at 400 five-star reviews on Google. He said, "Just do it." Perplexity had never heard of them. Here is what the kid understood that the paralegal did not. Google reviews are a ranking signal inside Google's algorithm. Perplexity runs its own crawler. It does not care how many stars you have on a platform it is not reading. It pulls from legal directories, bar association profiles, Yelp, structured schema data, and third-party citations. A firm can sit at the top of the Google Local Pack with 847 reviews and have zero citation presence inside the AI systems that 500 million users query every month. As of February 2026, the overlap between pages ranking in Google's top 10 and pages cited inside AI-generated answers had collapsed from 76 percent to under 20 percent. Two entirely different systems. Almost nobody in legal had noticed. The paralegal thought the reviews were the proof. The kid saw they were the blind spot. So he built a $1,200 audit. The deliverable is a single document. He opens Perplexity, ChatGPT, and Claude. He types the firm's practice area and city. He screenshots what comes back. Then he runs the same search on every competitor in the market. He maps which firms are being named, where the citations are coming from, and what data signals are missing from the ones that do not appear. The finding is almost always identical: No Foursquare listing No attorney schema or LegalService markup beyond the default WordPress install Bar association profile unlinked from the main site Attorney bios with no verifiable credentials structured for machine reading NAP inconsistent across the seven directories that Perplexity actually indexes A firm charging $450 an hour that ChatGPT cannot confidently recommend because it cannot verify the address matches across three platforms. Less than 5 percent of local businesses have done this work as of 2026. In legal, the number is closer to zero. He charges $1,200 to show them exactly where they do not exist. Then he quotes them the fix. He walked out of the first firm with a check. That firm referred him to two others before the week was over. Those two referred three more. He has never made a cold call. He has never run an ad. He does not have a website. 41 firms in six months. $49,200 in revenue. He is 16. From what I have observed, the arbitrage here is not technical. It is perceptual. Law firms spent a decade optimizing for a system that is no longer the first place their clients look. The 16-year-old simply walked in and showed them the new one.

A 16-year-old in Austin made $49,200 in six months while every law firm in his city was busy counting Google reviews that nobody under 30 reads anymore. He walked into a law firm and asked the paralegal to search for the practice on Perplexity. The paralegal laughed and pointed at 400 five-star reviews on Google. He said, "Just do it." Perplexity had never heard of them. Here is what the kid understood that the paralegal did not. Google reviews are a ranking signal inside Google's algorithm. Perplexity runs its own crawler. It does not care how many stars you have on a platform it is not reading. It pulls from legal directories, bar association profiles, Yelp, structured schema data, and third-party citations. A firm can sit at the top of the Google Local Pack with 847 reviews and have zero citation presence inside the AI systems that 500 million users query every month. As of February 2026, the overlap between pages ranking in Google's top 10 and pages cited inside AI-generated answers had collapsed from 76 percent to under 20 percent. Two entirely different systems. Almost nobody in legal had noticed. The paralegal thought the reviews were the proof. The kid saw they were the blind spot. So he built a $1,200 audit. The deliverable is a single document. He opens Perplexity, ChatGPT, and Claude. He types the firm's practice area and city. He screenshots what comes back. Then he runs the same search on every competitor in the market. He maps which firms are being named, where the citations are coming from, and what data signals are missing from the ones that do not appear. The finding is almost always identical: No Foursquare listing No attorney schema or LegalService markup beyond the default WordPress install Bar association profile unlinked from the main site Attorney bios with no verifiable credentials structured for machine reading NAP inconsistent across the seven directories that Perplexity actually indexes A firm charging $450 an hour that ChatGPT cannot confidently recommend because it cannot verify the address matches across three platforms. Less than 5 percent of local businesses have done this work as of 2026. In legal, the number is closer to zero. He charges $1,200 to show them exactly where they do not exist. Then he quotes them the fix. He walked out of the first firm with a check. That firm referred him to two others before the week was over. Those two referred three more. He has never made a cold call. He has never run an ad. He does not have a website. 41 firms in six months. $49,200 in revenue. He is 16. From what I have observed, the arbitrage here is not technical. It is perceptual. Law firms spent a decade optimizing for a system that is no longer the first place their clients look. The 16-year-old simply walked in and showed them the new one.

478,783 次观看

whoever leaked this has bigger balls than sense two researchers replaced $7,500 of human grading with $77.81 of model calls, and the number that fell out should stop anyone shipping an agent this week: the judge disagrees with itself 13.6% of the time it also prefers whichever answer it saw first, 72% of the time. cross-judge agreement is a kappa of 0.51: the statistical polite word for guessing this is Eval Engineering, the layer that arrives after loops and graphs, and it installs into the agent you already pay for: - run every comparison both ways and average the two, because one production judge picked whichever answer sat in the first slot 72% of the time - stop shipping on a single verdict: recovering the reference answer took 11 repeated trials before a majority vote landed it, and 15 on the questions that actually mattered - report the chance-corrected agreement instead of raw match, since the gap between those two ran 33 to 41 points on the same benchmark - never let a model grade its own family, because self-preference tracks capability upward rather than falling away as models improve - test stability and bias together, since two judges already running in production held above 0.95 on repeat while carrying severe positional preference - freeze the rubric wording and version it, because semantically identical templates flipped the majority outcome in a quarter of tested cases - write the rubric as one observable pass condition rather than a bundle of scores, so a coin-flip preference cannot hide inside an average - let plain code take every objective call, did the test pass, does the file exist, did the state change, and leave the judge only what genuinely needs reading - make the verdict do something structural to the run in flight, reject the handoff, swap the node, quarantine the branch, or you have built a dashboard the catch is that your judge is a measurement instrument nobody calibrates: single-trial judging is too noisy for anything you would stake money on, and the same judges reordered by as much as 14 positions depending on which benchmark you asked so the loop has to converge on the spec rather than on the score, because optimise against a judge long enough and the agent learns to look right instead of being right bookmark this, the full build with the five evals to start on and the gate that lets the fleet merge its own work is written out in the article ↓

whoever leaked this has bigger balls than sense two researchers replaced $7,500 of human grading with $77.81 of model calls, and the number that fell out should stop anyone shipping an agent this week: the judge disagrees with itself 13.6% of the time it also prefers whichever answer it saw first, 72% of the time. cross-judge agreement is a kappa of 0.51: the statistical polite word for guessing this is Eval Engineering, the layer that arrives after loops and graphs, and it installs into the agent you already pay for: - run every comparison both ways and average the two, because one production judge picked whichever answer sat in the first slot 72% of the time - stop shipping on a single verdict: recovering the reference answer took 11 repeated trials before a majority vote landed it, and 15 on the questions that actually mattered - report the chance-corrected agreement instead of raw match, since the gap between those two ran 33 to 41 points on the same benchmark - never let a model grade its own family, because self-preference tracks capability upward rather than falling away as models improve - test stability and bias together, since two judges already running in production held above 0.95 on repeat while carrying severe positional preference - freeze the rubric wording and version it, because semantically identical templates flipped the majority outcome in a quarter of tested cases - write the rubric as one observable pass condition rather than a bundle of scores, so a coin-flip preference cannot hide inside an average - let plain code take every objective call, did the test pass, does the file exist, did the state change, and leave the judge only what genuinely needs reading - make the verdict do something structural to the run in flight, reject the handoff, swap the node, quarantine the branch, or you have built a dashboard the catch is that your judge is a measurement instrument nobody calibrates: single-trial judging is too noisy for anything you would stake money on, and the same judges reordered by as much as 14 positions depending on which benchmark you asked so the loop has to converge on the spec rather than on the score, because optimise against a judge long enough and the agent learns to look right instead of being right bookmark this, the full build with the five evals to start on and the gate that lets the fleet merge its own work is written out in the article ↓

238,481 次观看

i'm not fine after reading this a guy with a laptop got his own silicon chip manufactured with software Google gave away. the commercial version of that software rents for up to $1,000,000 a year. he never signed a vendor contract and never paid for a seat. he wrote the logic, pushed it to GitHub, and nine months later a wafer came out of a fab. getting silicon with your name in it used to take a company. now it takes nine months. his slot was 160 by 100 microns: about 1,000 logic gates, 8 inputs, 8 outputs, clocked past 50 MHz. more than 600 designs have already come back this way. this is the open silicon stack. Google and SkyWater published a complete 130nm manufacturing process, DARPA funded the software that turns code into a fab-ready file, and all of it sits in public repositories. turns out the whole flow fits in a git push: - write the logic in Verilog, or drag gates around in a browser if you have never done this - push to GitHub, an action runs synthesis, placement, routing and sign-off on the commit - OpenROAD finishes place-and-route with no human in the loop, code to fab file inside 24 hours - SKY130 carries the fab's real design rules, so passing the checks means it is manufacturable - a few hundred designs share one wafer, which is the only reason a person can afford the masks nobody puts this part in the thread: 130nm is roughly where the industry stood in 2001, and you wait six to nine months for silicon. this does not get you a GPU. it gets you a real object with your logic inside it. bookmark this. the video is one of those designs opened layer by layer, and every rectangle in it exists in the file that was sent to the fab.

i'm not fine after reading this a guy with a laptop got his own silicon chip manufactured with software Google gave away. the commercial version of that software rents for up to $1,000,000 a year. he never signed a vendor contract and never paid for a seat. he wrote the logic, pushed it to GitHub, and nine months later a wafer came out of a fab. getting silicon with your name in it used to take a company. now it takes nine months. his slot was 160 by 100 microns: about 1,000 logic gates, 8 inputs, 8 outputs, clocked past 50 MHz. more than 600 designs have already come back this way. this is the open silicon stack. Google and SkyWater published a complete 130nm manufacturing process, DARPA funded the software that turns code into a fab-ready file, and all of it sits in public repositories. turns out the whole flow fits in a git push: - write the logic in Verilog, or drag gates around in a browser if you have never done this - push to GitHub, an action runs synthesis, placement, routing and sign-off on the commit - OpenROAD finishes place-and-route with no human in the loop, code to fab file inside 24 hours - SKY130 carries the fab's real design rules, so passing the checks means it is manufacturable - a few hundred designs share one wafer, which is the only reason a person can afford the masks nobody puts this part in the thread: 130nm is roughly where the industry stood in 2001, and you wait six to nine months for silicon. this does not get you a GPU. it gets you a real object with your logic inside it. bookmark this. the video is one of those designs opened layer by layer, and every rectangle in it exists in the file that was sent to the fab.

150,798 次观看

this is worth more than most five figure courses 16 claude agents audit an entire repo at once, a second fleet re-checks every finding on fresh context, and the whole thing runs off one diagram instead of a prompt i ran it against my own code and got back 11 endpoints where i never checked who was logged in, 3 of which the verifier threw out before they ever reached me this is Graph Engineering, the layer above prompting, and it runs on the agent you already pay for: - write your plan out, then ask one question at every "and then": does the next step actually read what the previous one produced - the seams that fail that question were never dependencies, so those jobs run at the same time - the arrows that survive are your real edges, and the longest chain of them is your floor that no number of agents shortens - want it faster, cut a false edge instead of adding a worker - fan the independent work out, one agent per item, no shared state between them - send every finding to a separate agent on fresh context, because a model recognises its own writing 73.5% of the time and grades it kinder once it does - make that verifier check a real signal like a passing test, never the worker's own word that it finished - shard the fleet across worktrees so parallel workers stop overwriting each other, one rule frozen into every worker: never git stash, never git reset - merge only what came back verified, into one report instead of twenty open chats the catch is the ceiling. at 95% independent work 16 agents return 9.14x rather than the 16 you would guess, and even 256 only reach 18.6x, because the merge and the verify stay serial however wide you fan coordination itself is free plain code and every agent underneath it is billed, so start at twenty files and widen once it works bookmark this, the whole method with all six ready-to-run graphs is written out in the article ↓

this is worth more than most five figure courses 16 claude agents audit an entire repo at once, a second fleet re-checks every finding on fresh context, and the whole thing runs off one diagram instead of a prompt i ran it against my own code and got back 11 endpoints where i never checked who was logged in, 3 of which the verifier threw out before they ever reached me this is Graph Engineering, the layer above prompting, and it runs on the agent you already pay for: - write your plan out, then ask one question at every "and then": does the next step actually read what the previous one produced - the seams that fail that question were never dependencies, so those jobs run at the same time - the arrows that survive are your real edges, and the longest chain of them is your floor that no number of agents shortens - want it faster, cut a false edge instead of adding a worker - fan the independent work out, one agent per item, no shared state between them - send every finding to a separate agent on fresh context, because a model recognises its own writing 73.5% of the time and grades it kinder once it does - make that verifier check a real signal like a passing test, never the worker's own word that it finished - shard the fleet across worktrees so parallel workers stop overwriting each other, one rule frozen into every worker: never git stash, never git reset - merge only what came back verified, into one report instead of twenty open chats the catch is the ceiling. at 95% independent work 16 agents return 9.14x rather than the 16 you would guess, and even 256 only reach 18.6x, because the merge and the verify stay serial however wide you fan coordination itself is free plain code and every agent underneath it is billed, so start at twenty files and widen once it works bookmark this, the whole method with all six ready-to-run graphs is written out in the article ↓

157,688 次观看

BREAKING: white house insider wallet just became active on polymarket $10k bet placed 3 hours ago Khamenei out as Supreme Leader of Iran by January 31? YES at 20¢ iran internet blackout since jan 8 connectivity dropped to 2% of normal massive nationwide protests khamenei in most vulnerable position in 37 years i've seen this movie before: insider bet $32k on maduro removal 5 hours later: US raid, maduro captured insider profit: $400k+ we must not miss this

BREAKING: white house insider wallet just became active on polymarket $10k bet placed 3 hours ago Khamenei out as Supreme Leader of Iran by January 31? YES at 20¢ iran internet blackout since jan 8 connectivity dropped to 2% of normal massive nationwide protests khamenei in most vulnerable position in 37 years i've seen this movie before: insider bet $32k on maduro removal 5 hours later: US raid, maduro captured insider profit: $400k+ we must not miss this

299,485 次观看

a contractor in Shenzhen priced a ¥12,470,900 hospital contract, about $1.7m, in one afternoon and beat firms carrying forty people he explained how he did it: the bid consultancy he used to pay took three days and ¥46,000 for the same envelope. he did this one alone, off one screen, at 11.4% margin, uploaded before the 17:00 cutoff 214 pages of tender documents read, 68 binding clauses pulled out, 9,485 building parts loaded, 14 places found where a duct and a beam sit in the same cubic metre, deepest one 38mm, all of them fixed, 3,318 lines of quantities priced and the package encrypted and uploaded before the 17:00 cutoff this is Graph Engineering: the job gets cut into small nodes, one narrow task each, wired so that one node's output is the next node's input, and any node is allowed to stop the whole run. it turns a model that answers you into a machine that finishes the job: - give every node one job and one output. a node doing two things fails at both and you cannot tell which one broke - put the cheapest rejection first. his qualification node reads clause 7.4, foreign-owned firms barred, and ends the run four seconds in, before anything expensive touches the model - what moves between nodes is a file. the model travels as a model, the quantities as a table, the price as a number - build exactly one loop: the checker finds 14 collisions, the fixer drops the duct 550mm, the checker runs again, and nothing moves on until the count is zero - cap that loop, or a graph will grind on three impossible clashes until the deadline passes - keep one node whose only job is to say no, and give it authority over everything above it - log each node's output on its own, because when the price comes out wrong you need to know which node believed the wrong thing - run the expensive nodes last, always the catch is that a graph is an extremely confident machine: point it at an outdated rate book and it prices an entire hospital off it without a single node noticing, because no node is asked to doubt the input, only to process it so the nodes that earn their keep are the ones that reject, and almost nobody builds those first bookmark this, the full build with all nine nodes and what each one hands to the next is written out in the article ↓

a contractor in Shenzhen priced a ¥12,470,900 hospital contract, about $1.7m, in one afternoon and beat firms carrying forty people he explained how he did it: the bid consultancy he used to pay took three days and ¥46,000 for the same envelope. he did this one alone, off one screen, at 11.4% margin, uploaded before the 17:00 cutoff 214 pages of tender documents read, 68 binding clauses pulled out, 9,485 building parts loaded, 14 places found where a duct and a beam sit in the same cubic metre, deepest one 38mm, all of them fixed, 3,318 lines of quantities priced and the package encrypted and uploaded before the 17:00 cutoff this is Graph Engineering: the job gets cut into small nodes, one narrow task each, wired so that one node's output is the next node's input, and any node is allowed to stop the whole run. it turns a model that answers you into a machine that finishes the job: - give every node one job and one output. a node doing two things fails at both and you cannot tell which one broke - put the cheapest rejection first. his qualification node reads clause 7.4, foreign-owned firms barred, and ends the run four seconds in, before anything expensive touches the model - what moves between nodes is a file. the model travels as a model, the quantities as a table, the price as a number - build exactly one loop: the checker finds 14 collisions, the fixer drops the duct 550mm, the checker runs again, and nothing moves on until the count is zero - cap that loop, or a graph will grind on three impossible clashes until the deadline passes - keep one node whose only job is to say no, and give it authority over everything above it - log each node's output on its own, because when the price comes out wrong you need to know which node believed the wrong thing - run the expensive nodes last, always the catch is that a graph is an extremely confident machine: point it at an outdated rate book and it prices an entire hospital off it without a single node noticing, because no node is asked to doubt the input, only to process it so the nodes that earn their keep are the ones that reject, and almost nobody builds those first bookmark this, the full build with all nine nodes and what each one hands to the next is written out in the article ↓

38,189 次观看

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 ↓

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 ↓

32,752 次观看

somebody explain this because i refuse to accept it someone ran 48 scored trials and one agent beat a whole fleet of them on all 6 task families, at 0.93 cents a run against 1.9, while openai's best fleet shape was paying $0.008 for every single point of accuracy it bought i read it expecting a hit piece and found the opposite: the fleets that partitioned the dependency graph properly lifted pass rate 14% and cut wall-clock 2.10x on the same tasks, and one of them beat claude code with agent teams the thing that decides it has a name, Graph Engineering, and it is a property of the diagram rather than the model: - partition on the real dependency graph pulled from static analysis, never by folder or by file, because the gains land hardest on the most dependency-dense projects - isolate the structural hub files first, since those are the nodes every partition would otherwise have to share - measure the critical path and treat it as the floor, because a chain that genuinely feeds itself cannot be replaced by more workers and wrapping it in a scheduler does not shorten it - match the topology to the coupling instead of defaulting to parallel: on coupled work a static parallel shape drops below a single agent, so the mismatch is worse than no orchestration - remember each worker serialises its own subtasks, which adds edges inside every agent that were never in your plan - budget the fan-out before you fire it, because three agents already burn roughly three times the tokens and the multiplier compounds across sessions - check worker count against your rate limit, since fifteen workers at ten requests a second walk straight through a hundred-per-second ceiling and cascade - put a script gate in front of the planner: it costs 0.15 seconds and zero tokens, and it lets the expensive model skip 43 to 63% of the steps for at most 1.4 points of accuracy the catch is the coordination tax, and it scales with how clever the shape looks: 58% extra reasoning turns for independent workers, 263% decentralised, 285% centralised, and 515% for the hybrid setup everyone reaches for first the same paper found that hybrid then collapses hardest on tool-heavy work at a 0.452 success rate, while the plainer decentralised shape beat centralised outright despite carrying more overhead, because parallel efficiency is what survives bookmark this, the whole build sits in the article ↓

somebody explain this because i refuse to accept it someone ran 48 scored trials and one agent beat a whole fleet of them on all 6 task families, at 0.93 cents a run against 1.9, while openai's best fleet shape was paying $0.008 for every single point of accuracy it bought i read it expecting a hit piece and found the opposite: the fleets that partitioned the dependency graph properly lifted pass rate 14% and cut wall-clock 2.10x on the same tasks, and one of them beat claude code with agent teams the thing that decides it has a name, Graph Engineering, and it is a property of the diagram rather than the model: - partition on the real dependency graph pulled from static analysis, never by folder or by file, because the gains land hardest on the most dependency-dense projects - isolate the structural hub files first, since those are the nodes every partition would otherwise have to share - measure the critical path and treat it as the floor, because a chain that genuinely feeds itself cannot be replaced by more workers and wrapping it in a scheduler does not shorten it - match the topology to the coupling instead of defaulting to parallel: on coupled work a static parallel shape drops below a single agent, so the mismatch is worse than no orchestration - remember each worker serialises its own subtasks, which adds edges inside every agent that were never in your plan - budget the fan-out before you fire it, because three agents already burn roughly three times the tokens and the multiplier compounds across sessions - check worker count against your rate limit, since fifteen workers at ten requests a second walk straight through a hundred-per-second ceiling and cascade - put a script gate in front of the planner: it costs 0.15 seconds and zero tokens, and it lets the expensive model skip 43 to 63% of the steps for at most 1.4 points of accuracy the catch is the coordination tax, and it scales with how clever the shape looks: 58% extra reasoning turns for independent workers, 263% decentralised, 285% centralised, and 515% for the hybrid setup everyone reaches for first the same paper found that hybrid then collapses hardest on tool-heavy work at a 0.452 success rate, while the plainer decentralised shape beat centralised outright despite carrying more overhead, because parallel efficiency is what survives bookmark this, the whole build sits in the article ↓

32,932 次观看

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓

this is more useful than my entire degree Elon Musk's rocket company signed a $60,000,000,000 deal for Cursor in June, and eight days ago the two of them put a worker on sale for $200 a month: it gets its own computer in the cloud, signs into your accounts, clicks through your real apps, and hands back finished work instead of a draft for you to paste i ran one against my receipts folder on sunday and got back 14 filed, 2 it held because they needed a card number, and a saved method i never wrote myself Grok Bot is the one you train by doing your own job in front of it, and the whole handover fits in four messages tonight: 1. write out one job you did today the way you would brief a new hire: what has to be finished, which sites and files to work from, what to hand back, and where it stops and asks you 2. let it run once on something safe to get wrong, then correct the result until it is worth your name 3. say "save what we just did as a skill", and add the one rule about what always needs your approval 4. say "run that skill every weekday at 8 and post the result here. if the source is missing, tell me instead of using yesterday's numbers" xAI wrote that order into its own manual: one real job, then the saved method, then the clock. a schedule sitting on top of a method nobody checked replaces two hours of your clicking with two hours of your mistake turns out you never get to pick the brain, and that is the part i would argue about: the manual says there is no model picker for members or admins, no plan to add one, and the bill follows whichever model answered bookmark this, then open the piece below: which jobs deserve a worker of their own, and which ones quietly burn the seat ↓

21,946 次观看

i found the cheat code for polymarket 607% return in under 2 minutes Glint scans news in real time and tells you which market will move BEFORE it moves trump greenland tariffs news dropped glint detected it at 1¢ 90 seconds later market hit 10¢ if you had $1,000 ready you'd have $7,000 while you're reading headlines, glint already placed the trade news drops → glint catches it → shows you the market → you enter before anyone else this is how insiders have been winning now you can too

i found the cheat code for polymarket 607% return in under 2 minutes Glint scans news in real time and tells you which market will move BEFORE it moves trump greenland tariffs news dropped glint detected it at 1¢ 90 seconds later market hit 10¢ if you had $1,000 ready you'd have $7,000 while you're reading headlines, glint already placed the trade news drops → glint catches it → shows you the market → you enter before anyone else this is how insiders have been winning now you can too

40,522 次观看

nobody in that room realised what he just said microsoft's ceo told a conference that the frontier model you rent for $200 a month is the commodity, and someone has now measured what that costs everyone who assumed otherwise teams carrying 90 to 100% evaluation coverage reach excellent reliability 70.3% of the time, against 32.4% for teams sitting under half, on the same rented models i read the survey behind it twice because the sample is 500 enterprise teams rather than a vendor anecdote, and the spread holds across all of them this is Eval Engineering, and it is the part of the stack that stops being rented: - stop classifying behaviours as low-risk before you have data on them, because the 19.3% of teams who do take 2.3 times the production incidents and the intuition fails hardest exactly where behaviour is emergent - make the incident the source of the test: only 51.7% of teams turn an outage into a permanent regression, so half of all incident response gets paid for and then thrown away - budget coverage like continuous integration rather than like paperwork, since the pattern separating the elite teams is 70% coverage held together with 40% of development time spent on testing - gate the deploy on the eval instead of reporting the eval, because a threshold that cannot block a release is a dashboard with extra steps - keep the examiner private, since it encodes your own definition of correct: the model gets replaced from scratch twice a year and the examiner is the only asset that survives the swap - expect the incident rather than hoping to prevent it, because 84.9% of organisations hit one inside six months and only 8.4% report none, so detection speed is the real variable - review the gaps on a schedule and make the team justify an uncovered behaviour rather than defend a test that already exists the catch is what coverage actually costs, and it is not the tooling bill: the elite pattern spends 40% of development time on testing, which is the share of every sprint that stops being feature work that is the trade nobody puts in the quickstart, and it is why most teams stay at the coverage level where reliability lands at 32.4% bookmark this, the whole build sits in the article ↓

nobody in that room realised what he just said microsoft's ceo told a conference that the frontier model you rent for $200 a month is the commodity, and someone has now measured what that costs everyone who assumed otherwise teams carrying 90 to 100% evaluation coverage reach excellent reliability 70.3% of the time, against 32.4% for teams sitting under half, on the same rented models i read the survey behind it twice because the sample is 500 enterprise teams rather than a vendor anecdote, and the spread holds across all of them this is Eval Engineering, and it is the part of the stack that stops being rented: - stop classifying behaviours as low-risk before you have data on them, because the 19.3% of teams who do take 2.3 times the production incidents and the intuition fails hardest exactly where behaviour is emergent - make the incident the source of the test: only 51.7% of teams turn an outage into a permanent regression, so half of all incident response gets paid for and then thrown away - budget coverage like continuous integration rather than like paperwork, since the pattern separating the elite teams is 70% coverage held together with 40% of development time spent on testing - gate the deploy on the eval instead of reporting the eval, because a threshold that cannot block a release is a dashboard with extra steps - keep the examiner private, since it encodes your own definition of correct: the model gets replaced from scratch twice a year and the examiner is the only asset that survives the swap - expect the incident rather than hoping to prevent it, because 84.9% of organisations hit one inside six months and only 8.4% report none, so detection speed is the real variable - review the gaps on a schedule and make the team justify an uncovered behaviour rather than defend a test that already exists the catch is what coverage actually costs, and it is not the tooling bill: the elite pattern spends 40% of development time on testing, which is the share of every sprint that stops being feature work that is the trade nobody puts in the quickstart, and it is why most teams stay at the coverage level where reliability lands at 32.4% bookmark this, the whole build sits in the article ↓

16,482 次观看

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HOLY SH*T. i made my first $10,000 with Grok Bot. THANKS ELON for months i kept asking myself one thing: how do i build income that runs without me so i sat down with Grok Bot and we went through dozens of ways to make money most of them needed clients, time or luck the fastest one needed none of that: a trading bot on polymarket so we reverse engineered every crypto bot that prints there why crypto: → a new "Bitcoin up or down" market opens every 5 minutes, 288 a day → the Bitcoin price is public, no insider info needed → every bet settles in 5 minutes, so you see what works fast we spent weeks building the strategy together. this is what we ended up with: → only the 5-minute Bitcoin markets → it waits until about 2 minutes are left → Bitcoin is only $10 from where the window started, yet the losing side already sells for 20-40¢ → it buys that cheap side. it still wins 44% of the time → when one side really pulls ahead, it buys the leader near 50¢ → it rarely pays above 70¢, about 1 buy in 10 → it skips 7 windows out of 10. $14 a bet, up to $170 on the strongest calls 23 days since we switched it on: → +$10,774 → green 20 days out of 21 → worst day: -$31 → 6,692 trades, still running right now honest part: before we put real money in, we ran it on paper for a week and every version bled. it bought the cheap side every single window and the fees ate everything want the same setup? this is how mine is built: → Scout reads the Chainlink price these markets settle on and works out each side's real chance → Trader places the bets on its own, only when a side is 5+ points too cheap after the fee → Risk reads every trade each morning and pauses everything after 3 red days in a row → Grok Bot routines are too slow for 2-minute calls, so Builder wrote the terminal that actually trades. it runs 24/7 on a $6/month server and talks to Polymarket directly paste this into Grok Bot to start: "build me a Polymarket team for the 5-minute "Bitcoin Up or Down" markets: Scout, Trader, Risk and Builder. Scout reads the Chainlink BTC/USD price the markets settle on and works out each side's real chance. Trader flags any side 5+ points too cheap after the fee, never above 70¢, size $15. Risk reviews the log every morning. Builder writes a small terminal for a cheap server so it reacts in seconds. run it on paper first and switch Trader to real bets only after a green week" full Grok Bot setup in the article below, my wallet in the reply ↓ i'm already building the next bot for another polymarket niche. follow so you don't miss the wallet when it goes live
0:38
Argona0x's profile picture

HOLY SH*T. i made my first $10,000 with Grok Bot. THANKS ELON for months i kept asking myself one thing: how do i build income that runs without me so i sat down with Grok Bot and we went through dozens of ways to make money most of them needed clients, time or luck the fastest one needed none of that: a trading bot on polymarket so we reverse engineered every crypto bot that prints there why crypto: → a new "Bitcoin up or down" market opens every 5 minutes, 288 a day → the Bitcoin price is public, no insider info needed → every bet settles in 5 minutes, so you see what works fast we spent weeks building the strategy together. this is what we ended up with: → only the 5-minute Bitcoin markets → it waits until about 2 minutes are left → Bitcoin is only $10 from where the window started, yet the losing side already sells for 20-40¢ → it buys that cheap side. it still wins 44% of the time → when one side really pulls ahead, it buys the leader near 50¢ → it rarely pays above 70¢, about 1 buy in 10 → it skips 7 windows out of 10. $14 a bet, up to $170 on the strongest calls 23 days since we switched it on: → +$10,774 → green 20 days out of 21 → worst day: -$31 → 6,692 trades, still running right now honest part: before we put real money in, we ran it on paper for a week and every version bled. it bought the cheap side every single window and the fees ate everything want the same setup? this is how mine is built: → Scout reads the Chainlink price these markets settle on and works out each side's real chance → Trader places the bets on its own, only when a side is 5+ points too cheap after the fee → Risk reads every trade each morning and pauses everything after 3 red days in a row → Grok Bot routines are too slow for 2-minute calls, so Builder wrote the terminal that actually trades. it runs 24/7 on a $6/month server and talks to Polymarket directly paste this into Grok Bot to start: "build me a Polymarket team for the 5-minute "Bitcoin Up or Down" markets: Scout, Trader, Risk and Builder. Scout reads the Chainlink BTC/USD price the markets settle on and works out each side's real chance. Trader flags any side 5+ points too cheap after the fee, never above 70¢, size $15. Risk reviews the log every morning. Builder writes a small terminal for a cheap server so it reacts in seconds. run it on paper first and switch Trader to real bets only after a green week" full Grok Bot setup in the article below, my wallet in the reply ↓ i'm already building the next bot for another polymarket niche. follow so you don't miss the wallet when it goes live

Argona

545,266 次观看 • 2 天前

f*cking insane. I hired an AI chief of staff for $0, gave it one rule: "find me $50,000 a month or you're fired", went to sleep, and Opus 5.5 had it on my desk by morning a SpaceXAI engineer said one line that hit 5 million views: "i have a Chief of Staff agent. he knows about all my other bots and manages everything" a human one costs $200,000 a year. mine runs on Opus 5.5 inside Viktor, on his own computer in the cloud, with my laptop shut i give the goal, he does the steps, i only make the calls the rule: "find me $50,000 a month of new business. public data only. contact nobody without my yes" the night: → 9pm broke the goal into 4 jobs and gave each a day and a time, i wrote none of them → 11pm pulled 240 dental clinics in Austin from Google Maps and cut every chain → 1am read every site that was left and kept 25, each with one thing he noticed and where he saw it → 2am wrote an opener for every one of them, sent zero → 3am built the offer on one page, no invented results, price left blank for me instead of guessing → 8am i typed $2,000 a month. 25 clinics × $2,000 = $50,000 a month on the table honestly the blank price is what i'd pay for, an AI that guesses your price loses you the deal and he does it again every Monday: 100 new clinics a month, and he never forgets to start 240 clinics → 25 worth it → 1 offer → $50,000 a month on the table → 0 sent without my yes second 12, he leaves the price blank and hands it to me someone's chief of staff is already pitching the clinics in your city i left the whole setup below ↓ free, steal it
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f*cking insane. I hired an AI chief of staff for $0, gave it one rule: "find me $50,000 a month or you're fired", went to sleep, and Opus 5.5 had it on my desk by morning a SpaceXAI engineer said one line that hit 5 million views: "i have a Chief of Staff agent. he knows about all my other bots and manages everything" a human one costs $200,000 a year. mine runs on Opus 5.5 inside Viktor, on his own computer in the cloud, with my laptop shut i give the goal, he does the steps, i only make the calls the rule: "find me $50,000 a month of new business. public data only. contact nobody without my yes" the night: → 9pm broke the goal into 4 jobs and gave each a day and a time, i wrote none of them → 11pm pulled 240 dental clinics in Austin from Google Maps and cut every chain → 1am read every site that was left and kept 25, each with one thing he noticed and where he saw it → 2am wrote an opener for every one of them, sent zero → 3am built the offer on one page, no invented results, price left blank for me instead of guessing → 8am i typed $2,000 a month. 25 clinics × $2,000 = $50,000 a month on the table honestly the blank price is what i'd pay for, an AI that guesses your price loses you the deal and he does it again every Monday: 100 new clinics a month, and he never forgets to start 240 clinics → 25 worth it → 1 offer → $50,000 a month on the table → 0 sent without my yes second 12, he leaves the price blank and hands it to me someone's chief of staff is already pitching the clinics in your city i left the whole setup below ↓ free, steal it

Argona

1,043,289 次观看 • 10 天前

🚨this is SERIOUSLY dangerous. i just watched an 18-year-old calmly explain how he turned Opus 5.5 into a personal Bloomberg Terminal (traders pay nearly $32,000 a year for one), and i'm convinced 99% of people still aren't seeing this it's the screen wall street traders stare at all day to trade the markets, and the best of them make $1M+ a year the whole system fits in four lines: - open a market app and pick Claude Opus 5.5 as its brain - type in the stocks and coins you hold - connect your Telegram - close the laptop from there, Opus 5.5 does all of it every weekday at 8:00 it checks your list, catches whatever moved more than usual, digs up why and sends it to your Telegram, with a source and a time on every reason 1 question ≈ 23 sources read zero charts zero news tabs zero stress one sentence to set it up, then it runs on autopilot you're done chasing the market you're running your own Bloomberg Terminal save this. the full course is below
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Argona0x's profile picture

🚨this is SERIOUSLY dangerous. i just watched an 18-year-old calmly explain how he turned Opus 5.5 into a personal Bloomberg Terminal (traders pay nearly $32,000 a year for one), and i'm convinced 99% of people still aren't seeing this it's the screen wall street traders stare at all day to trade the markets, and the best of them make $1M+ a year the whole system fits in four lines: - open a market app and pick Claude Opus 5.5 as its brain - type in the stocks and coins you hold - connect your Telegram - close the laptop from there, Opus 5.5 does all of it every weekday at 8:00 it checks your list, catches whatever moved more than usual, digs up why and sends it to your Telegram, with a source and a time on every reason 1 question ≈ 23 sources read zero charts zero news tabs zero stress one sentence to set it up, then it runs on autopilot you're done chasing the market you're running your own Bloomberg Terminal save this. the full course is below

Argona

1,273,238 次观看 • 17 天前

holy sh*t. Karpathy's second brain pattern runs on Grok Bot now: stop explaining your life to AI from zero every chat, keep a wiki that writes itself three bots in one group chat, each with its own memory: the reader takes every link, PDF and voice note you drop and never edits it the librarian rewrites every wiki page that source touches, usually 10 to 15 of them the checker wakes up on a nightly routine and hunts contradictions, stale claims and pages nothing links to → you ask a question: the answer gets filed back as a page, so the brain grows from use, not only from reading → a new source contradicts an old page: the checker tags you instead of quietly overwriting it → a page goes 30 days without a fresh source: it gets marked unconfirmed a second brain can sound sure while remembering the wrong thing Reader collects. Librarian writes. Checker doubts. every page has to show: > the claim > the source it came from > the date it was last confirmed paste this into Grok Bot: "Build me a second brain with three bots in one group chat. Keep my sources untouched in raw/, maintain wiki/ yourself, file good answers back as pages and run a nightly check for contradictions. Show me the structure first. Do not create anything until I confirm" start with one topic you actually work on, not your whole life full setup below
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Argona0x's profile picture

holy sh*t. Karpathy's second brain pattern runs on Grok Bot now: stop explaining your life to AI from zero every chat, keep a wiki that writes itself three bots in one group chat, each with its own memory: the reader takes every link, PDF and voice note you drop and never edits it the librarian rewrites every wiki page that source touches, usually 10 to 15 of them the checker wakes up on a nightly routine and hunts contradictions, stale claims and pages nothing links to → you ask a question: the answer gets filed back as a page, so the brain grows from use, not only from reading → a new source contradicts an old page: the checker tags you instead of quietly overwriting it → a page goes 30 days without a fresh source: it gets marked unconfirmed a second brain can sound sure while remembering the wrong thing Reader collects. Librarian writes. Checker doubts. every page has to show: > the claim > the source it came from > the date it was last confirmed paste this into Grok Bot: "Build me a second brain with three bots in one group chat. Keep my sources untouched in raw/, maintain wiki/ yourself, file good answers back as pages and run a nightly check for contradictions. Show me the structure first. Do not create anything until I confirm" start with one topic you actually work on, not your whole life full setup below

Argona

508,644 次观看 • 11 天前

i gave Elon's Grok Bot $50 and told it "pay for yourself or you die" 48 hours later it's holding $5,273 and it's still alive autonomous trading agent on polymarket zero code this time. the bot has its own computer in the cloud, its own browser, its own terminal. it trades with my laptop shut every 10 minutes it: → scans 500-1000 markets → reads live X sentiment (it's grok, it sees every post on this app) → builds fair value, flags mispricing > 8% → calculates position size (kelly criterion, max 6% bankroll) → executes in its own browser → pays its own $200 subscription from profits if the balance hits $0, i cancel the subscription. the bot dies day one it dipped to $11. it dropped crypto and moved to weather markets, front-running NOAA updates so it learned to survive setup took one evening: create the bot, run one trade on your screen while it watches, put the skill on a schedule, connect telegram no VPS. no API keys. no rust last winter i built this exact system by hand. 3 weeks of rust. it made $2,980 in its first 48 hours grok bot beat my own code in one evening $50 → $5,273 in 48 hours how much do u think it'll have in a week?
2:03
Argona0x's profile picture

i gave Elon's Grok Bot $50 and told it "pay for yourself or you die" 48 hours later it's holding $5,273 and it's still alive autonomous trading agent on polymarket zero code this time. the bot has its own computer in the cloud, its own browser, its own terminal. it trades with my laptop shut every 10 minutes it: → scans 500-1000 markets → reads live X sentiment (it's grok, it sees every post on this app) → builds fair value, flags mispricing > 8% → calculates position size (kelly criterion, max 6% bankroll) → executes in its own browser → pays its own $200 subscription from profits if the balance hits $0, i cancel the subscription. the bot dies day one it dipped to $11. it dropped crypto and moved to weather markets, front-running NOAA updates so it learned to survive setup took one evening: create the bot, run one trade on your screen while it watches, put the skill on a schedule, connect telegram no VPS. no API keys. no rust last winter i built this exact system by hand. 3 weeks of rust. it made $2,980 in its first 48 hours grok bot beat my own code in one evening $50 → $5,273 in 48 hours how much do u think it'll have in a week?

Argona

1,275,144 次观看 • 2 个月前

somebody just torched their entire career for us someone inside Anthropic wrote down exactly how they wire their AIs to work as a team instead of one at a time, every number, and let the whole thing walk out the door it's called Graph Engineering: you stop asking one AI to do the whole job and start running a crew. one plans, a few go and look, one checks the others for lies their own measurement: the crew came back with 96% of the quality at 46% of the price. same models, same question. they only changed who is allowed to talk to whom Anthropic raised $65,000,000,000 to figure this out. it costs you $0 run one tonight in a normal chat, 3 moves: 1. give it the job and make it write the plan before it touches anything 2. run each step in its own fresh chat so nothing bleeds into the next 3. in one clean chat at the end, make it check the work against sources and mark whatever it could not confirm save this, then open the piece below: how many workers a job actually needs, and where one more starts making it worse ↓
0:34
Argona0x's profile picture

somebody just torched their entire career for us someone inside Anthropic wrote down exactly how they wire their AIs to work as a team instead of one at a time, every number, and let the whole thing walk out the door it's called Graph Engineering: you stop asking one AI to do the whole job and start running a crew. one plans, a few go and look, one checks the others for lies their own measurement: the crew came back with 96% of the quality at 46% of the price. same models, same question. they only changed who is allowed to talk to whom Anthropic raised $65,000,000,000 to figure this out. it costs you $0 run one tonight in a normal chat, 3 moves: 1. give it the job and make it write the plan before it touches anything 2. run each step in its own fresh chat so nothing bleeds into the next 3. in one clean chat at the end, make it check the work against sources and mark whatever it could not confirm save this, then open the piece below: how many workers a job actually needs, and where one more starts making it worse ↓

Argona

1,385,988 次观看 • 2 个月前

there is no catch and that scares me Elon Musk posted an idea that hit 27 million views: "stop building startups. buy boring internet real estate and let bots run it" that's literally what Grok Bot does now. the whole setup costs $0 on top of the sub: → create a bot, name it Mogul → tell it to find one boring niche people search every day (it reads X and reddit complaints in real time, it's grok) → it builds a small directory site on its own computer and ships one useful page every night → it negotiates affiliate and referral deals itself, by email, in your name → publishing runs on a routine. telegram sends you the money reports → month one: traffic. month three: the first $217. it never stops after that your laptop stays shut. the site grows anyway every page is a tiny employee that works forever. it compounds like rent some of them run 3 sites each and haven't opened a single one. they don't post about it, and now you know why every month you wait, someone's bot ships another 30 pages into the niche you would've picked full playbook below bookmark this before someone takes your niche
0:25
Argona0x's profile picture

there is no catch and that scares me Elon Musk posted an idea that hit 27 million views: "stop building startups. buy boring internet real estate and let bots run it" that's literally what Grok Bot does now. the whole setup costs $0 on top of the sub: → create a bot, name it Mogul → tell it to find one boring niche people search every day (it reads X and reddit complaints in real time, it's grok) → it builds a small directory site on its own computer and ships one useful page every night → it negotiates affiliate and referral deals itself, by email, in your name → publishing runs on a routine. telegram sends you the money reports → month one: traffic. month three: the first $217. it never stops after that your laptop stays shut. the site grows anyway every page is a tiny employee that works forever. it compounds like rent some of them run 3 sites each and haven't opened a single one. they don't post about it, and now you know why every month you wait, someone's bot ships another 30 pages into the niche you would've picked full playbook below bookmark this before someone takes your niche

Argona

1,028,670 次观看 • 2 个月前

i gave an AI $50 and told it "pay for yourself or you die" 48 hours later it turned $50 into $2,980 and it's still alive autonomous trading agent on polymarket every 10 minutes it: → scans 500-1000 markets → builds fair value estimate with claude → finds mispricing > 8% → calculates position size (kelly criterion, max 6% bankroll) → executes → pays its own API bill from profits if balance hits $0, the agent dies so it learned to survive built in rust for speed claude API for reasoning (agent pays for its own inference) runs on a $4.5/month VPS weather markets: parses NOAA before polymarket updates sports: scrapes injury reports, finds mispricing crypto: on-chain metrics + sentiment $50 → $2,980 in 48 hours how much do u think i’ll see in a week?
2:03
Argona0x's profile picture

i gave an AI $50 and told it "pay for yourself or you die" 48 hours later it turned $50 into $2,980 and it's still alive autonomous trading agent on polymarket every 10 minutes it: → scans 500-1000 markets → builds fair value estimate with claude → finds mispricing > 8% → calculates position size (kelly criterion, max 6% bankroll) → executes → pays its own API bill from profits if balance hits $0, the agent dies so it learned to survive built in rust for speed claude API for reasoning (agent pays for its own inference) runs on a $4.5/month VPS weather markets: parses NOAA before polymarket updates sports: scrapes injury reports, finds mispricing crypto: on-chain metrics + sentiment $50 → $2,980 in 48 hours how much do u think i’ll see in a week?

Argona

4,780,965 次观看 • 8 个月前

my landlord raised my rent by $400 so i fed my entire lease to claude it found a clause that means he owes me $6,200 in overcharges going back 18 months his lawyer confirmed it yesterday i wasn't even mad about the increase. i just wanted to see what claude would pull from 47 pages of legal text i never actually read pasted the full lease and said "find anything that violates california rent stabilization law" it came back in 90 seconds → flagged a habitability clause tied to maintenance obligations he never fulfilled → cross-referenced AB 1482 statewide caps + local RSO limits going back to 2023 → found he applied a 6.1% increase when AB 1482 capped it at 5% + CPI (4% max under LA County RSTPO for 2024) → calculated cumulative overcharges across 18 billing cycles → cited Civil Code §1947.12 (AB 1482 penalties up to 3x overcharge for willful violations) + local RSO municipal code tying habitability breaches to withheld increases → drafted a demand letter with line-by-line breakdowns ran the clause extraction through legal-bert and it hit 92% confidence on the payment term violations sent the demand letter to his property management company on a tuesday by the following thursday his lawyer called and said "the numbers check out" total cost: one prompt and a 47-page pdf i lived in that apartment for three years and never once read past page 4 my rent increase was $400, my refund check is $6,200 i'm keeping the apartment
1:52
Argona0x's profile picture

my landlord raised my rent by $400 so i fed my entire lease to claude it found a clause that means he owes me $6,200 in overcharges going back 18 months his lawyer confirmed it yesterday i wasn't even mad about the increase. i just wanted to see what claude would pull from 47 pages of legal text i never actually read pasted the full lease and said "find anything that violates california rent stabilization law" it came back in 90 seconds → flagged a habitability clause tied to maintenance obligations he never fulfilled → cross-referenced AB 1482 statewide caps + local RSO limits going back to 2023 → found he applied a 6.1% increase when AB 1482 capped it at 5% + CPI (4% max under LA County RSTPO for 2024) → calculated cumulative overcharges across 18 billing cycles → cited Civil Code §1947.12 (AB 1482 penalties up to 3x overcharge for willful violations) + local RSO municipal code tying habitability breaches to withheld increases → drafted a demand letter with line-by-line breakdowns ran the clause extraction through legal-bert and it hit 92% confidence on the payment term violations sent the demand letter to his property management company on a tuesday by the following thursday his lawyer called and said "the numbers check out" total cost: one prompt and a 47-page pdf i lived in that apartment for three years and never once read past page 4 my rent increase was $400, my refund check is $6,200 i'm keeping the apartment

Argona

2,892,556 次观看 • 7 个月前

my landlord raised my rent by $400 so i fed my entire lease to Grok Bot it decided one pdf wasn't enough, built a second brain out of 3 years of our emails and found $6,200 he overcharged me his lawyer confirmed it yesterday i wasn't even mad about the increase. i just wanted to see what Grok Bot would pull from 47 pages of legal text i never actually read connected my Gmail and pasted the second brain prompt from my article below then dropped in the full lease and typed "find anything in here he's not allowed to do" it went quiet for 9 hours on its own cloud computer while my laptop was shut at 7:30 am one page was waiting → filed 3 years of our emails, rent receipts and photos of the leak into one folder, every line linked to the original → found a clause on page 31: no rent increase while a repair request is still open → matched it to 11 repair requests he answered with "next week" and never fixed → flagged every increase he charged with at least one repair open → added up the overcharge across 18 billing cycles → drafted the demand letter in my own voice and waited for my yes that sunday at 6 pm its weekly report flagged one more thing. he'd cc'd the whole building on a 2024 rent email. 14 other units, same lease i printed the page and slid it under 14 doors by friday all 14 had forwarded me their emails, and it filed every one overnight sent the demand letter to his property management company on a tuesday, signed by all 15 units by the following thursday his lawyer called and said "the numbers check out" then he asked who my attorney was. i sent him a screenshot of Grok Bot total cost: a $20 plan, one prompt and a 47-page pdf i lived in that apartment for three years and never once read past page 4 my rent increase was $400. the building's refund is $91,400 i'm keeping the apartment the prompt is in the article below. read it before your landlord does
2:08
Argona0x's profile picture

my landlord raised my rent by $400 so i fed my entire lease to Grok Bot it decided one pdf wasn't enough, built a second brain out of 3 years of our emails and found $6,200 he overcharged me his lawyer confirmed it yesterday i wasn't even mad about the increase. i just wanted to see what Grok Bot would pull from 47 pages of legal text i never actually read connected my Gmail and pasted the second brain prompt from my article below then dropped in the full lease and typed "find anything in here he's not allowed to do" it went quiet for 9 hours on its own cloud computer while my laptop was shut at 7:30 am one page was waiting → filed 3 years of our emails, rent receipts and photos of the leak into one folder, every line linked to the original → found a clause on page 31: no rent increase while a repair request is still open → matched it to 11 repair requests he answered with "next week" and never fixed → flagged every increase he charged with at least one repair open → added up the overcharge across 18 billing cycles → drafted the demand letter in my own voice and waited for my yes that sunday at 6 pm its weekly report flagged one more thing. he'd cc'd the whole building on a 2024 rent email. 14 other units, same lease i printed the page and slid it under 14 doors by friday all 14 had forwarded me their emails, and it filed every one overnight sent the demand letter to his property management company on a tuesday, signed by all 15 units by the following thursday his lawyer called and said "the numbers check out" then he asked who my attorney was. i sent him a screenshot of Grok Bot total cost: a $20 plan, one prompt and a 47-page pdf i lived in that apartment for three years and never once read past page 4 my rent increase was $400. the building's refund is $91,400 i'm keeping the apartment the prompt is in the article below. read it before your landlord does

Argona

136,811 次观看 • 15 天前

holy sh*t. SpaceXAI runs Grok Bot like a hedge fund now: stop asking your Grok Bot for help, make it hunt money for you a hedge fund doesn't run on one analyst. neither does the Grok Bot team: Lingxi Li went from 15 agents by hand to 200+ working at once, a whole trading floor of bots. same app you have. you're using 1% of it the upgrade is three roles that check each other: the PM is the only bot you talk to. it splits every goal into small jobs and hands them out the analysts are 20 copies of one bot, each gets one slice and they all read at the same time the risk desk is paid to say no, it tries to kill every finding before it reaches you → you ask one question: the PM cuts it into 20 pieces, 20 analysts read at once, a week of research comes back in minutes → every answer hits the risk desk first: it attacks it, and you only see what survived → every day the fund grades its own calls and rewrites the rules that were wrong, so your bots get sharper every week without you your default Grok Bot is one intern who believes everything it reads. a fund has 20 analysts and a risk desk that kills every bad call first PM splits. Analysts dig. Risk says no. then i gave this exact team one job: find insiders on Polymarket the PM split the 200 most profitable wallets of the month between the analysts. each one pulled its wallet's first day and every market it ever touched. 15 were under 60 days old and bet on 1 or 2 events only the risk desk dropped every one that made under $500k. 2 survived, and they're the same story: both appeared out of nowhere before Brazil's election, bet against the favorite, and never traded anything else: > first trade 23 days before the runoff. loaded up on Lula at 20-47¢ while he was the underdog, sold everything at 99¢ less than an hour after the race was called. +$901,231 on one election, then silence > bought "Bolsonaro loses" at 12-24¢ for three weeks while he was the 80% favorite, dumped it all during the count. +$844,714, never touched another market $1.75M on one election, from two wallets nobody had heard of a month ago. a default bot sees two lucky wallets. this one saw the pattern now it watches for the next fresh wallet that bets big against the favorite, and pings me before the result paste this into Grok Bot: "build me a fund: PM, Analysts and Risk. every morning PM pulls the 200 most profitable Polymarket wallets of the last 30 days from Polymarket's public data and splits them between the Analysts. each Analyst checks its wallets: first trade date, how many events it ever bet on, average entry price. flag any wallet under 60 days old with 2 events or fewer. Risk drops every flag it can explain with public news, a small profit or a long track record. message me only when a surviving wallet opens a new bet. never place a bet yourself" i've already seen 2 high school kids make their first 5 figs with Grok Bot this month stop f*cking scrolling, read the article below and learn this skill before everyone else does
0:25
Argona0x's profile picture

holy sh*t. SpaceXAI runs Grok Bot like a hedge fund now: stop asking your Grok Bot for help, make it hunt money for you a hedge fund doesn't run on one analyst. neither does the Grok Bot team: Lingxi Li went from 15 agents by hand to 200+ working at once, a whole trading floor of bots. same app you have. you're using 1% of it the upgrade is three roles that check each other: the PM is the only bot you talk to. it splits every goal into small jobs and hands them out the analysts are 20 copies of one bot, each gets one slice and they all read at the same time the risk desk is paid to say no, it tries to kill every finding before it reaches you → you ask one question: the PM cuts it into 20 pieces, 20 analysts read at once, a week of research comes back in minutes → every answer hits the risk desk first: it attacks it, and you only see what survived → every day the fund grades its own calls and rewrites the rules that were wrong, so your bots get sharper every week without you your default Grok Bot is one intern who believes everything it reads. a fund has 20 analysts and a risk desk that kills every bad call first PM splits. Analysts dig. Risk says no. then i gave this exact team one job: find insiders on Polymarket the PM split the 200 most profitable wallets of the month between the analysts. each one pulled its wallet's first day and every market it ever touched. 15 were under 60 days old and bet on 1 or 2 events only the risk desk dropped every one that made under $500k. 2 survived, and they're the same story: both appeared out of nowhere before Brazil's election, bet against the favorite, and never traded anything else: > first trade 23 days before the runoff. loaded up on Lula at 20-47¢ while he was the underdog, sold everything at 99¢ less than an hour after the race was called. +$901,231 on one election, then silence > bought "Bolsonaro loses" at 12-24¢ for three weeks while he was the 80% favorite, dumped it all during the count. +$844,714, never touched another market $1.75M on one election, from two wallets nobody had heard of a month ago. a default bot sees two lucky wallets. this one saw the pattern now it watches for the next fresh wallet that bets big against the favorite, and pings me before the result paste this into Grok Bot: "build me a fund: PM, Analysts and Risk. every morning PM pulls the 200 most profitable Polymarket wallets of the last 30 days from Polymarket's public data and splits them between the Analysts. each Analyst checks its wallets: first trade date, how many events it ever bet on, average entry price. flag any wallet under 60 days old with 2 events or fewer. Risk drops every flag it can explain with public news, a small profit or a long track record. message me only when a surviving wallet opens a new bet. never place a bet yourself" i've already seen 2 high school kids make their first 5 figs with Grok Bot this month stop f*cking scrolling, read the article below and learn this skill before everyone else does

Argona

16,267 次观看 • 1 天前

whoever leaked this has bigger balls than sense someone handed GPT-6 Astra a port's public records and one question: what does not add up. it flagged a plant that officially burned down three years ago and still received containers weekly. the owners had collected $184,000,000 in fire insurance, renamed the company and kept producing. the tip paid $18,400,000 every fake fire, fake bankruptcy and fake shutdown leaves a trail in four public databases. almost nobody reads all four together this is GPT-6 Astra, the layer that reads every public record about one address at once, $0 on top of the plan you already pay for: - pull the customs manifest: by law every container entering the US by sea leaves a record the press may copy and publish, shipper, receiver, cargo, weight, ship. hand Astra the whole export - add the ships: every vessel over 300 tons has broadcast its position on AIS since 2004 and has to keep it on. a weekly port call becomes a count - check it from orbit: NASA FIRMS logs every fire seen from space within 3 hours, date and size included, and Sentinel-2 photographs every point on earth every 5 days at 10 metres, free. a lot full of trucks is not a ruin - let Astra cross-check: 1,050,000 tokens of context, 96.3% recall across a million of them, 4.2% hallucinations. ask for only what the documents prove - file it: the SEC pays 10 to 30% of what it collects once a case clears $1,000,000 and seals your name. its biggest cheque, $279,000,000, went to someone who only widened a case already open none of this was hidden. it was scattered the catch is slow money. nothing is paid below $1,000,000 in sanctions, only after the case closes, and an importer can hide its name on the manifest for two years at a time fraud is a story told to one database at a time every month you scroll past this, someone else's Astra is reading the same public files bookmark this, how to hand Astra a whole problem instead of a question is in the post below ↓
0:30
Argona0x's profile picture

whoever leaked this has bigger balls than sense someone handed GPT-6 Astra a port's public records and one question: what does not add up. it flagged a plant that officially burned down three years ago and still received containers weekly. the owners had collected $184,000,000 in fire insurance, renamed the company and kept producing. the tip paid $18,400,000 every fake fire, fake bankruptcy and fake shutdown leaves a trail in four public databases. almost nobody reads all four together this is GPT-6 Astra, the layer that reads every public record about one address at once, $0 on top of the plan you already pay for: - pull the customs manifest: by law every container entering the US by sea leaves a record the press may copy and publish, shipper, receiver, cargo, weight, ship. hand Astra the whole export - add the ships: every vessel over 300 tons has broadcast its position on AIS since 2004 and has to keep it on. a weekly port call becomes a count - check it from orbit: NASA FIRMS logs every fire seen from space within 3 hours, date and size included, and Sentinel-2 photographs every point on earth every 5 days at 10 metres, free. a lot full of trucks is not a ruin - let Astra cross-check: 1,050,000 tokens of context, 96.3% recall across a million of them, 4.2% hallucinations. ask for only what the documents prove - file it: the SEC pays 10 to 30% of what it collects once a case clears $1,000,000 and seals your name. its biggest cheque, $279,000,000, went to someone who only widened a case already open none of this was hidden. it was scattered the catch is slow money. nothing is paid below $1,000,000 in sanctions, only after the case closes, and an importer can hide its name on the manifest for two years at a time fraud is a story told to one database at a time every month you scroll past this, someone else's Astra is reading the same public files bookmark this, how to hand Astra a whole problem instead of a question is in the post below ↓

Argona

325,641 次观看 • 1 个月前

this guy explained how he sells a $10,000 AI agent to businesses that takes him an afternoon to build 26 minutes, every step on screen, completely free Claude Code writes the rules → Grok Bot finds and qualifies the leads → personalized drafts land in a google sheet every morning → you invoice $10,000 🔖 trust me, don't scroll past this one
26:42
Argona0x's profile picture

this guy explained how he sells a $10,000 AI agent to businesses that takes him an afternoon to build 26 minutes, every step on screen, completely free Claude Code writes the rules → Grok Bot finds and qualifies the leads → personalized drafts land in a google sheet every morning → you invoice $10,000 🔖 trust me, don't scroll past this one

Argona

299,195 次观看 • 1 个月前

someone on the Grok Bot team leaked this f*cking prompt online. paste this into Grok Bot. this one prompt builds a second brain that runs your life: -track what you're actually focused on every hour -write one page per person, project and decision -hunt its own contradictions every night -reject its own memory if it can't show the source Bookmark it right now.
0:22
Argona0x's profile picture

someone on the Grok Bot team leaked this f*cking prompt online. paste this into Grok Bot. this one prompt builds a second brain that runs your life: -track what you're actually focused on every hour -write one page per person, project and decision -hunt its own contradictions every night -reject its own memory if it can't show the source Bookmark it right now.

Argona

60,694 次观看 • 11 天前

an 18 year old made $1,000 in 47 minutes with GPT ASTRA 6 and a roofing company that had 4.9 stars and no website he didn't build anything. he copied 40 of their google reviews into ASTRA 6 and typed: "write the brief for the website this business deserves" 2 minutes later he had the full brief pasted it into the builder and waited. every page, every review, a booking button. live link in his hand before the coffee got cold then he called the owner and sent him the preview. the guy said yes on the phone. he'd been meaning to fix this for 3 years and never had a free afternoon invoice: $1,000. 47 minutes from the first google maps search to a closed deal then he stopped doing it by hand: → ASTRA 6 pulls 200 businesses off google maps in 10 minutes → writes a personalized email for each one from their real reviews, hours and photos → 500 emails a day. 3% reply → every reply runs through the same 47-minute pipeline month one: $4,000. month six: $15,000 to $20,000 ASTRA 6 has been out for a week. he's 18. and there are still 5 million businesses on google maps with great reviews and no website do the math on your own city
0:46
Argona0x's profile picture

an 18 year old made $1,000 in 47 minutes with GPT ASTRA 6 and a roofing company that had 4.9 stars and no website he didn't build anything. he copied 40 of their google reviews into ASTRA 6 and typed: "write the brief for the website this business deserves" 2 minutes later he had the full brief pasted it into the builder and waited. every page, every review, a booking button. live link in his hand before the coffee got cold then he called the owner and sent him the preview. the guy said yes on the phone. he'd been meaning to fix this for 3 years and never had a free afternoon invoice: $1,000. 47 minutes from the first google maps search to a closed deal then he stopped doing it by hand: → ASTRA 6 pulls 200 businesses off google maps in 10 minutes → writes a personalized email for each one from their real reviews, hours and photos → 500 emails a day. 3% reply → every reply runs through the same 47-minute pipeline month one: $4,000. month six: $15,000 to $20,000 ASTRA 6 has been out for a week. he's 18. and there are still 5 million businesses on google maps with great reviews and no website do the math on your own city

Argona

257,796 次观看 • 1 个月前

i genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. you give Grok Bot one folder on its own cloud computer, feed it your emails, links and photos from your phone, and it reads them, links them, and files them into a living wiki of everything you know. it compounds like interest, the more you feed it, the smarter it gets. doesn't matter if you're a developer, a salesperson or a student, you need this the full setup: > create a bot in Grok Bot, name it Brain and add Gmail and Google Calendar in Connect apps. it runs on its own cloud computer, so it keeps working while your laptop is shut > paste the prompt from chapter 07 of my article below into its chat. one message builds the folder, the routines and the rules > it reads the last 100 emails you sent and writes voice.md, 10 rules of how you write, each with a real line of yours. no more "hope this finds you well" drafts > label any email "Brain" and every night at 11 PM it saves the original and files it on the page of that person or project > at 7:30 AM you get one page with what came in, what it drafted and what waits for your yes, ranked by the 5 projects you actually work on > correct it once and the fix goes into rules.md, which it rereads before every task. every Sunday it tells you what you decided and forgot five minutes to set up, and you never start from a blank chat again. every prompt is in the 7-step course below. or paste the whole article into Brain's chat and it builds the brain for you. bookmark this
0:30
Argona0x's profile picture

i genuinely don't understand why everyone isn't using this yet Andrej Karpathy, a co-founder of OpenAI, posted a simple idea that hit 16 million views: stop using AI to write code, use it to build a second brain. you give Grok Bot one folder on its own cloud computer, feed it your emails, links and photos from your phone, and it reads them, links them, and files them into a living wiki of everything you know. it compounds like interest, the more you feed it, the smarter it gets. doesn't matter if you're a developer, a salesperson or a student, you need this the full setup: > create a bot in Grok Bot, name it Brain and add Gmail and Google Calendar in Connect apps. it runs on its own cloud computer, so it keeps working while your laptop is shut > paste the prompt from chapter 07 of my article below into its chat. one message builds the folder, the routines and the rules > it reads the last 100 emails you sent and writes voice.md, 10 rules of how you write, each with a real line of yours. no more "hope this finds you well" drafts > label any email "Brain" and every night at 11 PM it saves the original and files it on the page of that person or project > at 7:30 AM you get one page with what came in, what it drafted and what waits for your yes, ranked by the 5 projects you actually work on > correct it once and the fix goes into rules.md, which it rereads before every task. every Sunday it tells you what you decided and forgot five minutes to set up, and you never start from a blank chat again. every prompt is in the 7-step course below. or paste the whole article into Brain's chat and it builds the brain for you. bookmark this

Argona

74,059 次观看 • 15 天前

I released a prompt that turns Grok Bot into a second brain. It’s f*cking unreal… send it to Grok Bot, and thank me later. Then read the full roadmap with examples below.
0:30
Argona0x's profile picture

I released a prompt that turns Grok Bot into a second brain. It’s f*cking unreal… send it to Grok Bot, and thank me later. Then read the full roadmap with examples below.

Argona

64,226 次观看 • 16 天前

this in the wrong hands. jesus. Grok Bot turned a Gmail label into a second brain that's faster and better than any human Jason Freedman (YC alum and investor) gave Grok Bot four years of tax returns, 266 unlabeled files and one assignment: "please double check my CPA's work" label an email Brain and watch it land in the right folder with a summary, the date and a link to the raw source add a second bot while keeping the same folder. Lingxi Li at SpaceXAI could manage 15 cloud agents by hand, and with Grok Bot the fleet now manages more than 200 at once each routine gets one job and runs on its own clock: → 11 PM filing copies Brain-labelled mail into raw/ and sorts it into people/ or projects/ → 5 PM attention rewrites attention.md from what you actually touched → 7:30 AM page hands you facts, guesses and the drafts waiting for your yes → Sunday 6 PM review finds what you decided and forgot a great CPA with no AI tools missed HSA contributions counted twice, four years in a row, and mortgage interest left off the 2022 return entirely Brain reopens every number at the source, never from memory, and nothing is sent, bought, deleted or published without your yes every morning page has to show: > the facts, each with a link > the guesses, marked as guesses > what got filed or drafted overnight > the drafts in out/ still waiting for your yes the bot found them a few minutes after the upload, and the fixed return was ready to sign the same afternoon with about 90 seconds of Freedman's own time. Elon quoted it: "Grok Grok Bot can help with your taxes" connect Gmail to Grok Bot, then ask: "Turn /workspace/brain into my second brain and keep it running 1. Create raw/ (never edit), people/, projects/, out/, INDEX.md, log.md and rules.md. Every file gets a one-line summary, the date and a link to its raw source 2. Read the last 100 emails I sent through Gmail. Write me.md and voice.md with 10 rules, each with one real line of mine. Quote only lines I wrote 3. Routines in my time zone ([my time zone]): 11 PM file mail labelled Brain, 5 PM rewrite attention.md, 7:30 AM the morning page, Sundays 6 PM what I forgot, report only. Show me each first 4. Read INDEX.md and rules.md first, take fast facts from the source, add each correction to rules.md. Never send, buy, delete or publish without my yes" start with one label and one nightly routine before adding more bots keep everything in files, not in bot memory, so every bot you add later reads the same folder watch the brain at work below
0:30
Argona0x's profile picture

this in the wrong hands. jesus. Grok Bot turned a Gmail label into a second brain that's faster and better than any human Jason Freedman (YC alum and investor) gave Grok Bot four years of tax returns, 266 unlabeled files and one assignment: "please double check my CPA's work" label an email Brain and watch it land in the right folder with a summary, the date and a link to the raw source add a second bot while keeping the same folder. Lingxi Li at SpaceXAI could manage 15 cloud agents by hand, and with Grok Bot the fleet now manages more than 200 at once each routine gets one job and runs on its own clock: → 11 PM filing copies Brain-labelled mail into raw/ and sorts it into people/ or projects/ → 5 PM attention rewrites attention.md from what you actually touched → 7:30 AM page hands you facts, guesses and the drafts waiting for your yes → Sunday 6 PM review finds what you decided and forgot a great CPA with no AI tools missed HSA contributions counted twice, four years in a row, and mortgage interest left off the 2022 return entirely Brain reopens every number at the source, never from memory, and nothing is sent, bought, deleted or published without your yes every morning page has to show: > the facts, each with a link > the guesses, marked as guesses > what got filed or drafted overnight > the drafts in out/ still waiting for your yes the bot found them a few minutes after the upload, and the fixed return was ready to sign the same afternoon with about 90 seconds of Freedman's own time. Elon quoted it: "Grok Grok Bot can help with your taxes" connect Gmail to Grok Bot, then ask: "Turn /workspace/brain into my second brain and keep it running 1. Create raw/ (never edit), people/, projects/, out/, INDEX.md, log.md and rules.md. Every file gets a one-line summary, the date and a link to its raw source 2. Read the last 100 emails I sent through Gmail. Write me.md and voice.md with 10 rules, each with one real line of mine. Quote only lines I wrote 3. Routines in my time zone ([my time zone]): 11 PM file mail labelled Brain, 5 PM rewrite attention.md, 7:30 AM the morning page, Sundays 6 PM what I forgot, report only. Show me each first 4. Read INDEX.md and rules.md first, take fast facts from the source, add each correction to rules.md. Never send, buy, delete or publish without my yes" start with one label and one nightly routine before adding more bots keep everything in files, not in bot memory, so every bot you add later reads the same folder watch the brain at work below

Argona

40,043 次观看 • 13 天前

i have $8,400 of credit card debt so i created a grok bot and told it "this is your problem now" day 6: the debt is $7,912 and i haven't done anything except watch i named the bot Reaper. it has its own computer in the cloud, access to my email, and one instruction: "report progress daily. don't ask me for money" honestly i didn't expect much. i just wanted to stop being the only one who knew the number first night it read 14 months of statements. then it went to work: → found $67/month in subscriptions i forgot existed. killed them the same hour → emailed the card company's retention team. two escalations later my APR dropped from 26.99% to 19.4% → found a 0% balance transfer, 12 months, $89 fee. did the math, moved $6,100 → disputed two charges from 2025. won one: $118 back → listed my playstation and two monitors on ebay. i found out from the confirmation email → every dollar it frees goes straight to principal, automatically every night at 9pm, telegram: "debt: $7,912. freed today: $31. nothing needed from you" the playstation thing annoyed me for exactly one minute. then i checked when i last used it. november the bot costs $200 a month. it freed $488 in week one projected zero: march 11. i've stopped opening my banking app. the bot opens it for me should i give it my student loans next?
2:00
Argona0x's profile picture

i have $8,400 of credit card debt so i created a grok bot and told it "this is your problem now" day 6: the debt is $7,912 and i haven't done anything except watch i named the bot Reaper. it has its own computer in the cloud, access to my email, and one instruction: "report progress daily. don't ask me for money" honestly i didn't expect much. i just wanted to stop being the only one who knew the number first night it read 14 months of statements. then it went to work: → found $67/month in subscriptions i forgot existed. killed them the same hour → emailed the card company's retention team. two escalations later my APR dropped from 26.99% to 19.4% → found a 0% balance transfer, 12 months, $89 fee. did the math, moved $6,100 → disputed two charges from 2025. won one: $118 back → listed my playstation and two monitors on ebay. i found out from the confirmation email → every dollar it frees goes straight to principal, automatically every night at 9pm, telegram: "debt: $7,912. freed today: $31. nothing needed from you" the playstation thing annoyed me for exactly one minute. then i checked when i last used it. november the bot costs $200 a month. it freed $488 in week one projected zero: march 11. i've stopped opening my banking app. the bot opens it for me should i give it my student loans next?

Argona

159,016 次观看 • 2 个月前

my bank froze my account for 'suspicious pattern of small deposits' i had to explain to a fraud analyst that a program sends me $40 eighty times a day - roughly $3,200 daily she put me on hold for nineteen minutes the bot runs on polymarket's 5-minute crypto markets eth up or down, btc up or down, new market every 5 minutes, 24/7 it connects via websocket to polymarket's CLOB, builds a fair value estimate, and fires gasless L2 orders on polygon whenever it finds mispricing above 6% → 80+ trades a day → average profit per trade: ~$40 → profits auto-redeem to USDC → USDC bridges to my bank as ACH deposits banks flag anything that looks like structuring 4.1 million suspicious activity reports were filed in 2025 alone my account had 80 identical deposits hitting every single day to the fraud algorithm i looked like a money launderer the analyst asked me three times to explain what a "prediction market" was i said "it's like if a stock and a sports bet had a baby and it lives on a blockchain" silence then she asked if i had documentation i sent her a csv export with 17,000 trades timestamped to the millisecond she unfroze the account, then told me i should "consider consolidating my deposits" the bot doesn't know how to consolidate - it just wakes up every 5 minutes, finds edge, and sends me $40 i'm not changing a thing the next SAR flag is her problem not mine
1:01
Argona0x's profile picture

my bank froze my account for 'suspicious pattern of small deposits' i had to explain to a fraud analyst that a program sends me $40 eighty times a day - roughly $3,200 daily she put me on hold for nineteen minutes the bot runs on polymarket's 5-minute crypto markets eth up or down, btc up or down, new market every 5 minutes, 24/7 it connects via websocket to polymarket's CLOB, builds a fair value estimate, and fires gasless L2 orders on polygon whenever it finds mispricing above 6% → 80+ trades a day → average profit per trade: ~$40 → profits auto-redeem to USDC → USDC bridges to my bank as ACH deposits banks flag anything that looks like structuring 4.1 million suspicious activity reports were filed in 2025 alone my account had 80 identical deposits hitting every single day to the fraud algorithm i looked like a money launderer the analyst asked me three times to explain what a "prediction market" was i said "it's like if a stock and a sports bet had a baby and it lives on a blockchain" silence then she asked if i had documentation i sent her a csv export with 17,000 trades timestamped to the millisecond she unfroze the account, then told me i should "consider consolidating my deposits" the bot doesn't know how to consolidate - it just wakes up every 5 minutes, finds edge, and sends me $40 i'm not changing a thing the next SAR flag is her problem not mine

Argona

490,685 次观看 • 7 个月前