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The Matrix launch video lands on one line; in Matrix, anyone can become a CEO. That’s the real claim. Not one assistant doing one task. A company that keeps running after the first prompt, routing intent through a CEO Office, into OKRs, down to departments that do the work... show more

Iseunife The First

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19,414 просмотров • 3 месяцев назад •via X (Twitter)

Образование Наука и технологии

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If you're interested in Lovable, we have a surprise: 1. $100 in credits 2. A 16-page prompt engineering guide to mastering vibe coding Get your credits, read the guide, sit down on one weekend, and become a builder. Quote RT the first tweet and we'll send both to you:

If you're interested in Lovable, we have a surprise: 1. $100 in credits 2. A 16-page prompt engineering guide to mastering vibe coding Get your credits, read the guide, sit down on one weekend, and become a builder. Quote RT the first tweet and we'll send both to you:

Anton Osika

61,397 просмотров • 1 год назад

Vorflux has opened its new cloud platform, allowing users to run tasks from a plan to a merged PR on a dedicated machine. It can plan, build, test, and review on its own. > Diff reviews are done by a different model family than the one that wrote it by default. > First boot is saved as a snapshot, with all subsequent sessions waking up from that same starting point. > A browser agent walks through the real user flow, and the recording is included in the pull request. Video proof in the PR 👀

Vorflux has opened its new cloud platform, allowing users to run tasks from a plan to a merged PR on a dedicated machine. It can plan, build, test, and review on its own. > Diff reviews are done by a different model family than the one that wrote it by default. > First boot is saved as a snapshot, with all subsequent sessions waking up from that same starting point. > A browser agent walks through the real user flow, and the recording is included in the pull request. Video proof in the PR 👀

🚨 AI News | TestingCatalog

12,162 просмотров • 1 месяц назад

Meet LightVela, a 24/7 cloud AI assistant that also lives in the apps you already use, Telegram, WhatsApp, Discord. Create a bot in seconds. Nothing to configure. Or create a few: one for work, one for learning, one for the kids. Each keeps its own memory and its own schedule. Your laptop can be off. LightVela keeps the lights on. First month free, with 4,500 credits included. Come break it:

Meet LightVela, a 24/7 cloud AI assistant that also lives in the apps you already use, Telegram, WhatsApp, Discord. Create a bot in seconds. Nothing to configure. Or create a few: one for work, one for learning, one for the kids. Each keeps its own memory and its own schedule. Your laptop can be off. LightVela keeps the lights on. First month free, with 4,500 credits included. Come break it:

Tencent AI

11,326 просмотров • 1 день назад

What stuck with me in 2022 is that the Roomba photos weren’t leaked. They were sent out normally, as intended, to contractors who were paid to review them one by one. A woman sitting in the bathroom of her own home ended up in a Facebook group because "someone thought it was funny". Matic can’t do that even if it wanted to. The processing stays inside the robot. Cut the Wi-Fi and it keeps cleaning. It’s the first time you’re not being asked to take a company at its word.

What stuck with me in 2022 is that the Roomba photos weren’t leaked. They were sent out normally, as intended, to contractors who were paid to review them one by one. A woman sitting in the bathroom of her own home ended up in a Facebook group because "someone thought it was funny". Matic can’t do that even if it wanted to. The processing stays inside the robot. Cut the Wi-Fi and it keeps cleaning. It’s the first time you’re not being asked to take a company at its word.

Kayla ♔

92,799 просмотров • 1 месяц назад

On your open perpetual position can become an NFT and live in your wallet. You open a position like normal than mint it. The program issues a token 2022 nft, that points to your exact position. Normally your open position lives inside the protocol. With Percolator Trade your able to wrap it into an NFT that sits in your own wallet. A real, ownable object instead of a line in a dashboard. Because it’s a token, it moves like one. Send the NFT to another wallet and the position goes with it. Whoever holds the NFT owns the trade. One NFT = one position If you burn it, your back to holding the position directly. That’s the composable part, a position use to be stuck inside one account. Because it’s a token, it can now be sold OTC or used by anything that speaks tokens. Why does it matter? Because the position is bound to the NFT, it can’t be drained out from under whoever holds it so there is no middleman that holds your position. The NFT does, and the NFT is yours. One important safety detail; transfers run through a token 2022 hook that checks the positions health first, so it can’t be handed off in a broken state & the NFT layer is a separate program so it can never touch the funds the core engine holds.

On your open perpetual position can become an NFT and live in your wallet. You open a position like normal than mint it. The program issues a token 2022 nft, that points to your exact position. Normally your open position lives inside the protocol. With Percolator Trade your able to wrap it into an NFT that sits in your own wallet. A real, ownable object instead of a line in a dashboard. Because it’s a token, it moves like one. Send the NFT to another wallet and the position goes with it. Whoever holds the NFT owns the trade. One NFT = one position If you burn it, your back to holding the position directly. That’s the composable part, a position use to be stuck inside one account. Because it’s a token, it can now be sold OTC or used by anything that speaks tokens. Why does it matter? Because the position is bound to the NFT, it can’t be drained out from under whoever holds it so there is no middleman that holds your position. The NFT does, and the NFT is yours. One important safety detail; transfers run through a token 2022 hook that checks the positions health first, so it can’t be handed off in a broken state & the NFT layer is a separate program so it can never touch the funds the core engine holds.

Percolator

12,359 просмотров • 3 месяцев назад

The lesson is not that LEGO made better bricks. It is that a company in crisis was saved by a CEO who assumed the people doing the work already knew what was broken. His job was to listen, remove the noise, and get out of their way.

The lesson is not that LEGO made better bricks. It is that a company in crisis was saved by a CEO who assumed the people doing the work already knew what was broken. His job was to listen, remove the noise, and get out of their way.

Mark Woodland

245,898 просмотров • 6 месяцев назад

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

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

shmidt

19,505 просмотров • 3 месяцев назад

Ripple CEO says the company nearly shut down! CEO Brad Garlinghouse has revealed that the U.S. Securities and Exchange Commission's lawsuit against Ripple back in 2020 had company considering a shut down, per Wu Blockchain. It considered distributing $XRP holdings to shareholders, but decided to fight on to prevent major job losses.

Ripple CEO says the company nearly shut down! CEO Brad Garlinghouse has revealed that the U.S. Securities and Exchange Commission's lawsuit against Ripple back in 2020 had company considering a shut down, per Wu Blockchain. It considered distributing $XRP holdings to shareholders, but decided to fight on to prevent major job losses.

BSCN

30,842 просмотров • 3 месяцев назад

🚨 BILLIONAIRE CEO TELLS FLAT EARTHERS: "PROVE IT - I’LL GIVE YOU MY COMPANY" Columbia Sportswear CEO Tim Boyle issued a public challenge on video: If flat-Earth believers can find the edge of the Earth and bring back a photo, he says they can have the entire company. Not a reward. Not a bet. The $3 billion business. If the Earth is flat… what’s stopping someone from taking the company?

🚨 BILLIONAIRE CEO TELLS FLAT EARTHERS: "PROVE IT - I’LL GIVE YOU MY COMPANY" Columbia Sportswear CEO Tim Boyle issued a public challenge on video: If flat-Earth believers can find the edge of the Earth and bring back a photo, he says they can have the entire company. Not a reward. Not a bet. The $3 billion business. If the Earth is flat… what’s stopping someone from taking the company?

HustleBitch

463,388 просмотров • 9 месяцев назад

😌 Fire Point announces first Ukrainian ballistic missile launch against Russia Fire Point CEO Iryna Terekh said the tactical ballistic missile has a range of 300 km. She did not specify which target it struck. Terekh also said the company is working on a longer-range version and hopes to unveil it before the end of the year.

😌 Fire Point announces first Ukrainian ballistic missile launch against Russia Fire Point CEO Iryna Terekh said the tactical ballistic missile has a range of 300 km. She did not specify which target it struck. Terekh also said the company is working on a longer-range version and hopes to unveil it before the end of the year.

NEXTA

50,064 просмотров • 2 дней назад

your agent already does the work. reports. research. plans. full websites. then it dies in a chat reply. or a .md file. or a localhost page nobody else can open. showly fixes the last step. it's an agent artifact cloud. connect the agent you already use. claude code, codex, cursor, openclaw, hermes. ask it to deliver the work as a page. you review it privately. you decide who sees it. password, specific emails, your company domain, or fully public. then you share one link. every update is saved. go back to any version whenever you want. done isn't "the agent answered." done is an artifact with a link. first reply: start free. no credit card.

your agent already does the work. reports. research. plans. full websites. then it dies in a chat reply. or a .md file. or a localhost page nobody else can open. showly fixes the last step. it's an agent artifact cloud. connect the agent you already use. claude code, codex, cursor, openclaw, hermes. ask it to deliver the work as a page. you review it privately. you decide who sees it. password, specific emails, your company domain, or fully public. then you share one link. every update is saved. go back to any version whenever you want. done isn't "the agent answered." done is an artifact with a link. first reply: start free. no credit card.

Iris Hayes

44,398 просмотров • 23 дней назад

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 ↓

Argona

892,436 просмотров • 2 месяцев назад

herdr 0.7.0 is out, and it's a major one: it introduces plugins! the idea is simple: herdr stays lean, and everything custom gets extended through plugins. shareable, scoped, built however you want, to fit your own flow. with this release we're also shipping a few examples of what the plugin system can do. first up: a telegram plugin. herdr already controls your agents and knows their status, so the plugin just hooks into agent events and pings telegram the moment one needs you. notification lands → `herdr --remote` or ssh from your phone → straight back to the agent that needs you.

herdr 0.7.0 is out, and it's a major one: it introduces plugins! the idea is simple: herdr stays lean, and everything custom gets extended through plugins. shareable, scoped, built however you want, to fit your own flow. with this release we're also shipping a few examples of what the plugin system can do. first up: a telegram plugin. herdr already controls your agents and knows their status, so the plugin just hooks into agent events and pings telegram the moment one needs you. notification lands → `herdr --remote` or ssh from your phone → straight back to the agent that needs you.

herdr

104,889 просмотров • 4 месяцев назад

1 mini PC that fits in a palm, with no monthly token bill attached to it. Most people run their AI through a browser tab. Every prompt, every document, every half-finished idea leaves the machine and lands on someone else's server. This ORICO mini PC runs the model locally. The assistant lives inside the box, not in a data center 2,000 miles away. Small enough to slide into a bag. Powerful enough that you stop noticing it is not a desktop. You pay once for hardware instead of every month for limits. No outage that takes your assistant down with it. No terms of service deciding what your files are worth. Plug it in anywhere, and the assistant is already there, offline, waiting. The smallest machine on the desk is the only one that keeps its mouth shut.

1 mini PC that fits in a palm, with no monthly token bill attached to it. Most people run their AI through a browser tab. Every prompt, every document, every half-finished idea leaves the machine and lands on someone else's server. This ORICO mini PC runs the model locally. The assistant lives inside the box, not in a data center 2,000 miles away. Small enough to slide into a bag. Powerful enough that you stop noticing it is not a desktop. You pay once for hardware instead of every month for limits. No outage that takes your assistant down with it. No terms of service deciding what your files are worth. Plug it in anywhere, and the assistant is already there, offline, waiting. The smallest machine on the desk is the only one that keeps its mouth shut.

AiMind

82,756 просмотров • 1 месяц назад

THE CHEAPEST LINE ON THIS LIST IS THE ONE THAT SHOULD WORRY PEOPLE. Pulling every ad a competitor is running on Meta now costs your AI $0.002. That used to be somebody's whole afternoon. Now Claude does it in the middle of a chat, then reads what that competitor's customers complain about, then makes your counter-ad. The models could always plan this kind of work. What they were missing was the tools, and a safe way to pay for them. Agentik plugs Claude, ChatGPT, Codex and Cursor into 2,500+ paid tools through one connection, and every call shows its price before it runs. I tested it on Calendly last week. Claude read Reddit and Trustpilot to find the #1 complaint, named a rival brand, made 8 ads and a voiceover, and found the first people to pitch. One tool got stuck halfway and wasn't billed. The whole run came to $0.94. What single jobs cost: → every Meta ad a brand is running: $0.002 → 100 local businesses from Google Maps: $0.002 → a buyer's verified work email: $0.02 → an ad image with clean text: $0.06 → a 5-second product clip: $0.40 The video is the only job on that list over a dime. Eligible new accounts get $5 of free credit that covers every call up to $0.10. The link and a first prompt to try are in the reply

Theinfralab

18,432 просмотров • 2 дней назад

Most Web3 campaigns still pay for attention. This one pays for usage. NeoSoul is live on Action Model with a $5K pool running until September 10. The task is simple and specific: Create your first AI agent on NeoSoul. Meet the success criteria. Get verified through the Action Model browser extension. No vanity metrics. No empty follows. Just a real product action that actually matters. This is the point of ActionFi. Partners don’t buy fake engagement. They pay people to experience the product. If you already have the extension installed, you can start now. If not, you’re leaving a live campaign on the table. 👉 Have you created your first NeoSoul agent yet? #ActionModel #ActionFi #NeoSoul

Most Web3 campaigns still pay for attention. This one pays for usage. NeoSoul is live on Action Model with a $5K pool running until September 10. The task is simple and specific: Create your first AI agent on NeoSoul. Meet the success criteria. Get verified through the Action Model browser extension. No vanity metrics. No empty follows. Just a real product action that actually matters. This is the point of ActionFi. Partners don’t buy fake engagement. They pay people to experience the product. If you already have the extension installed, you can start now. If not, you’re leaving a live campaign on the table. 👉 Have you created your first NeoSoul agent yet? #ActionModel #ActionFi #NeoSoul

Trathoa

21,461 просмотров • 1 месяц назад

🚨 one person can now do the work of an entire creative team. i just tested it on a real one. a friend needed an ad for his brand, so I opened the new Runway Agent 2.0 to try it out. here's how it went: → it generated the music and the key image first, so I could approve the direction → once I gave the ok, it built the full video around it → and when something was off, i changed just that one piece, without redoing the rest one prompt, and I had the ad we needed, work that used to take weeks. this is what it made 👇 if you want to try it → · 30% off 3 months with code RUNWAYAGENT — made with Runway · #MadeWithRunway · #ad

brenz.

28,770 просмотров • 3 месяцев назад

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 ↓

Argona

32,752 просмотров • 2 месяцев назад