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We found a very dumb bug. The original is incorrect. Our AI assistant is actually 40x faster than Grok Bot, not 20x. For a simple dinner reservation: Grok Bot: 7 min 40 sec Meta Muse: 4 min 36 sec Instinct: 14 min + Claude Cowork: 6 min 25 sec... show more

Sarah Chieng

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92,953 просмотров • 11 дней назад •via X (Twitter)

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I watched so you did not have to and here is the breakdown!!!! Nearly 2 hours. Plenty of nostalgia. Plenty of vibes. Lots of feelings. But when the net was wide open for actual clarification? Dead air. Total time Chris Albert spoke 1,501 seconds Which is 25 min and 1 sec. So on an almost 2 hour show, he spoke for about 25 minutes total. Roughly 21% of the entire show The remaining time was largely filled by the hosts themselves frequently cutting him off, reframing questions, finishing answers for him, or moving the conversation along before he ever had to sit in discomfort or explain anything fully. 0 minutes of that time addressed the major unresolved timeline and movement issues Oddly missing from this fact-based discussion No explanation for how Colin got home 20 min AFTER Chris that night, despite a four-minute head start No explanation for why Chris’s wife that went to 34 Fairview with donuts for brian Jr. pulled behind a car that was not there only an hour earlier with no explanation then, turned around, came back to get him, returned again, stayed 30 min, then left, all on the morning John was found. No mention of parents allegedly coordinating to quietly clean up a house-destroying party involving minors in which his son was one No discussion of repeated allegations of Colin being removed from bars for underage drinking. We were told this channel is about facts, not opinion. So we treated it like a data exercise. We timed everything Chris talked about, so you didn’t have to. Here’s how nearly two hours were spent 2 min saying they tried to “let the court system play out,” while explaining his New Year’s Day Twitter Space tour and condemning Sean McCabe’s comments 37 sec on moving to Canton in 1974 35 sec explaining it’s normal to work in the town you grew up in (we agree) 35 sec on Canton no longer being blue-collar and now very expensive 44 sec reminiscing about red paint stains in his childhood garage was misrepresented by the defense 1 min on town politics 15 sec explaining what a Select Board is 50 sec on handling public comment and being a “First Amendment guy… to a degree” 38 sec announcing he’s not running again 25 sec on how he keeps his cool during public comment 15 sec on pineapple pizza 52 sec explaining Colin was 17 when John died and can’t play college football with his cousin 45 sec expressing loss for how his family has been treated 10 sec referencing a blogger saying “horrible things” about Colin 26 sec blaming the media for selling and sensationalizing a story 20 sec saying he’s mind-boggled 48 sec explaining why the term “McAlberts” is dehumanizing 28 sec criticizing Yannetti’s performance was upsetting to him while stating John was his friend 42 sec explaining the fence-straddling photo was a joke 1:50 on “Nebbercracker” and a childhood yard incident 10 sec about his wife bringing donuts to a nephew for his birthday was not weird 32 sec blaming Karen for making his family look like villains 1 min on selling his house and convincing his brother to sell 24 sec saying Nebbercracker was the best part of the trial 1:12 on knowing Michael Proctor but not really knowing him 10 sec saying he was never alone with Proctor 11 sec correcting the “pin it on the girl” claim (which we agree with) 1 min praising Jillian Daniels as a great family supporter and defender 1 min explaining early lack of support made him sad 15 sec thanking the hosts 31 sec discussing starting a “Defend the Truth” media page 30 sec saying both sides were horrible and doxxed people 24 sec on feeling isolated at first 33 sec minimizing the Proctor gift as “just gratitude for solving a murder in one day” 28 sec saying he’s still friends with the O’Keefes and they eat at his pizza shop 38 sec saying Mr. O’Keefe sits with him for long periods of time 43 sec lamenting being made into villains 30 sec saying the case took years off his parents’ lives 35 sec thanking supporters and saying “the truth is on our side”

I watched so you did not have to and here is the breakdown!!!! Nearly 2 hours. Plenty of nostalgia. Plenty of vibes. Lots of feelings. But when the net was wide open for actual clarification? Dead air. Total time Chris Albert spoke 1,501 seconds Which is 25 min and 1 sec. So on an almost 2 hour show, he spoke for about 25 minutes total. Roughly 21% of the entire show The remaining time was largely filled by the hosts themselves frequently cutting him off, reframing questions, finishing answers for him, or moving the conversation along before he ever had to sit in discomfort or explain anything fully. 0 minutes of that time addressed the major unresolved timeline and movement issues Oddly missing from this fact-based discussion No explanation for how Colin got home 20 min AFTER Chris that night, despite a four-minute head start No explanation for why Chris’s wife that went to 34 Fairview with donuts for brian Jr. pulled behind a car that was not there only an hour earlier with no explanation then, turned around, came back to get him, returned again, stayed 30 min, then left, all on the morning John was found. No mention of parents allegedly coordinating to quietly clean up a house-destroying party involving minors in which his son was one No discussion of repeated allegations of Colin being removed from bars for underage drinking. We were told this channel is about facts, not opinion. So we treated it like a data exercise. We timed everything Chris talked about, so you didn’t have to. Here’s how nearly two hours were spent 2 min saying they tried to “let the court system play out,” while explaining his New Year’s Day Twitter Space tour and condemning Sean McCabe’s comments 37 sec on moving to Canton in 1974 35 sec explaining it’s normal to work in the town you grew up in (we agree) 35 sec on Canton no longer being blue-collar and now very expensive 44 sec reminiscing about red paint stains in his childhood garage was misrepresented by the defense 1 min on town politics 15 sec explaining what a Select Board is 50 sec on handling public comment and being a “First Amendment guy… to a degree” 38 sec announcing he’s not running again 25 sec on how he keeps his cool during public comment 15 sec on pineapple pizza 52 sec explaining Colin was 17 when John died and can’t play college football with his cousin 45 sec expressing loss for how his family has been treated 10 sec referencing a blogger saying “horrible things” about Colin 26 sec blaming the media for selling and sensationalizing a story 20 sec saying he’s mind-boggled 48 sec explaining why the term “McAlberts” is dehumanizing 28 sec criticizing Yannetti’s performance was upsetting to him while stating John was his friend 42 sec explaining the fence-straddling photo was a joke 1:50 on “Nebbercracker” and a childhood yard incident 10 sec about his wife bringing donuts to a nephew for his birthday was not weird 32 sec blaming Karen for making his family look like villains 1 min on selling his house and convincing his brother to sell 24 sec saying Nebbercracker was the best part of the trial 1:12 on knowing Michael Proctor but not really knowing him 10 sec saying he was never alone with Proctor 11 sec correcting the “pin it on the girl” claim (which we agree with) 1 min praising Jillian Daniels as a great family supporter and defender 1 min explaining early lack of support made him sad 15 sec thanking the hosts 31 sec discussing starting a “Defend the Truth” media page 30 sec saying both sides were horrible and doxxed people 24 sec on feeling isolated at first 33 sec minimizing the Proctor gift as “just gratitude for solving a murder in one day” 28 sec saying he’s still friends with the O’Keefes and they eat at his pizza shop 38 sec saying Mr. O’Keefe sits with him for long periods of time 43 sec lamenting being made into villains 30 sec saying the case took years off his parents’ lives 35 sec thanking supporters and saying “the truth is on our side”

Dixie Normus

17,063 просмотров • 9 месяцев назад

🚨Disney spends $250,000,000 to make cartoon animals look real A junior 3D artist in Tokyo rebuilt the exact same cat shot-by-shot - and pocketed $15,318 last month. Her automated stack: > Kimi K3: Extracted the shot list frame-by-frame (40 sec) > Grok Bot: Generated 50 photoreal stills, scrapped 9 instantly (20 min) > Cartesia: Cloned the voiceover for the chase scene (4 min) > CapCut: Cut, captioned, and retimed an 18.4s edit to fit a 20.0s spec (30 min) Disney: A full studio, a render farm and a 25-person crew for one animal. Her: A $57 budget and a cat on the radiator. Full breakdown in the link below 👇

🚨Disney spends $250,000,000 to make cartoon animals look real A junior 3D artist in Tokyo rebuilt the exact same cat shot-by-shot - and pocketed $15,318 last month. Her automated stack: > Kimi K3: Extracted the shot list frame-by-frame (40 sec) > Grok Bot: Generated 50 photoreal stills, scrapped 9 instantly (20 min) > Cartesia: Cloned the voiceover for the chase scene (4 min) > CapCut: Cut, captioned, and retimed an 18.4s edit to fit a 20.0s spec (30 min) Disney: A full studio, a render farm and a 25-person crew for one animal. Her: A $57 budget and a cat on the radiator. Full breakdown in the link below 👇

Fokki

64,454 просмотров • 1 месяц назад

On August 11, SpaceXAI shipped Grok Bot. Grok Bot was built to stay on, gets its own computer, works inside apps and tools like you do, and keep working 24/7 even when your laptop is off. And a lot of AI agents existed before this, including OpenAI’s earlier agent products, but most of them worked more like where you give it a job, let it finish, and then it stops. Grok Bot pushed the idea of having an AI worker that is always there, always running, and organized more like a team. You can have a chief of staff at the top, different specialists handling different jobs, and now the same bot can even be shared across a team. Then on September 8, Meta launched Muse, 28 days later. Meta called it “The World’s First Personal AI Agent Built for Everyone.” Muse also gets its own computer in the cloud. It can work across apps, keep going after you close it, and ask before doing things like sending emails or spending money. Zuck made it a huge part of Meta Connect and talked about bringing this kind of agent to billions of people. Then yesterday, 49 days after Grok Bot launched, Sam introduced dots. OpenAI describes them as always-on agents with their own cloud computers that can work on your goals 24/7 and connect across thousands of apps. A full team of dots is part of the bigger vision too. So when I see people framing this as OpenAI vs. Meta, a huge part of the story is missing… Grok Bot shipped first. The shift toward always-on AI workers with their own computers is clearly where the industry is going now and Grok Bot kicked off the next big AI product category… it’s one of the hottest products in AI. But don’t get it twisted, everyone is copying Elon right now.

On August 11, SpaceXAI shipped Grok Bot. Grok Bot was built to stay on, gets its own computer, works inside apps and tools like you do, and keep working 24/7 even when your laptop is off. And a lot of AI agents existed before this, including OpenAI’s earlier agent products, but most of them worked more like where you give it a job, let it finish, and then it stops. Grok Bot pushed the idea of having an AI worker that is always there, always running, and organized more like a team. You can have a chief of staff at the top, different specialists handling different jobs, and now the same bot can even be shared across a team. Then on September 8, Meta launched Muse, 28 days later. Meta called it “The World’s First Personal AI Agent Built for Everyone.” Muse also gets its own computer in the cloud. It can work across apps, keep going after you close it, and ask before doing things like sending emails or spending money. Zuck made it a huge part of Meta Connect and talked about bringing this kind of agent to billions of people. Then yesterday, 49 days after Grok Bot launched, Sam introduced dots. OpenAI describes them as always-on agents with their own cloud computers that can work on your goals 24/7 and connect across thousands of apps. A full team of dots is part of the bigger vision too. So when I see people framing this as OpenAI vs. Meta, a huge part of the story is missing… Grok Bot shipped first. The shift toward always-on AI workers with their own computers is clearly where the industry is going now and Grok Bot kicked off the next big AI product category… it’s one of the hottest products in AI. But don’t get it twisted, everyone is copying Elon right now.

Teslaconomics

16,430 просмотров • 12 дней назад

Grok Bot is officially available in Tesla vehicles! I had early access for my Grok Bot team to be integrated directly inside my Cybertruck with the help of the SpaceXAI and Cursor team. And this is truly one of those things that’s hard to fully understand the power of it until you actually lived with it. It’s the same Grok Voice experience you already know in your Tesla… no separate app is needed. When you’re signed into Grok, your Grok Bots are right there and you can talk directly with all of them with just your voice. So today, Tesla FSD was driving me. I said, “Hey Grok.” Then I talked to my CEO bot like I would talk to someone working for me. I told it what I wanted for dinner tonight: 1/ Blueberries 2/ Strawberries 3/ Ribeye 4/ Shrimp 5/ And taco night for my family of four. That was it. I didn’t sit there searching for every single ingredient. I didn’t open Amazon and start building a cart item by item. I just explained what I wanted. Then, my CEO bot routed the job. My Chef bot figured out what we needed for taco night. Then my Amazon Cart Builder bot started putting the cart together and choosing the best items based on my purchase history. And while all of that was happening… FSD drove me to the gym and parked itself. I went inside and worked out. My bots kept working. And by the time I was finished, the cart was ready for me. I opened it. Looked everything over. Then I just clicked Order. Grok Bot + Tesla FSD completely removed all the manual work in between that would have wasted part of my day researching building a grocery list, getting the Amazon cart ready, and manually driving to my destination. And THAT was the wow moment for me… I just talked to Grok. FSD drove. I worked out. My Grok Bot team handled the busy work. When I finished the gym, the cart was simply just waiting for my approval. And all I had to do was click order. (btw you can make your Grok Bot place the order automatically as well, but I’m super picky with my food so mine are specifically built so I review it at the end). With this technology, you’re no longer opening five different apps and doing every tiny step yourself. You just tell your team what you want with your voice. They go work on it. You go live your life. The biggest upgrade here is that Grok Bot + Tesla FSD is giving us back the one thing we can never make more of… TIME. Grok Bot handles the work. Tesla FSD handles the drive. I get my time back. This is really the future… I’m glad people will be able to try out Grok Bot integrated with their Teslas today… this is truly life-changing technology.

Grok Bot is officially available in Tesla vehicles! I had early access for my Grok Bot team to be integrated directly inside my Cybertruck with the help of the SpaceXAI and Cursor team. And this is truly one of those things that’s hard to fully understand the power of it until you actually lived with it. It’s the same Grok Voice experience you already know in your Tesla… no separate app is needed. When you’re signed into Grok, your Grok Bots are right there and you can talk directly with all of them with just your voice. So today, Tesla FSD was driving me. I said, “Hey Grok.” Then I talked to my CEO bot like I would talk to someone working for me. I told it what I wanted for dinner tonight: 1/ Blueberries 2/ Strawberries 3/ Ribeye 4/ Shrimp 5/ And taco night for my family of four. That was it. I didn’t sit there searching for every single ingredient. I didn’t open Amazon and start building a cart item by item. I just explained what I wanted. Then, my CEO bot routed the job. My Chef bot figured out what we needed for taco night. Then my Amazon Cart Builder bot started putting the cart together and choosing the best items based on my purchase history. And while all of that was happening… FSD drove me to the gym and parked itself. I went inside and worked out. My bots kept working. And by the time I was finished, the cart was ready for me. I opened it. Looked everything over. Then I just clicked Order. Grok Bot + Tesla FSD completely removed all the manual work in between that would have wasted part of my day researching building a grocery list, getting the Amazon cart ready, and manually driving to my destination. And THAT was the wow moment for me… I just talked to Grok. FSD drove. I worked out. My Grok Bot team handled the busy work. When I finished the gym, the cart was simply just waiting for my approval. And all I had to do was click order. (btw you can make your Grok Bot place the order automatically as well, but I’m super picky with my food so mine are specifically built so I review it at the end). With this technology, you’re no longer opening five different apps and doing every tiny step yourself. You just tell your team what you want with your voice. They go work on it. You go live your life. The biggest upgrade here is that Grok Bot + Tesla FSD is giving us back the one thing we can never make more of… TIME. Grok Bot handles the work. Tesla FSD handles the drive. I get my time back. This is really the future… I’m glad people will be able to try out Grok Bot integrated with their Teslas today… this is truly life-changing technology.

Teslaconomics

687,928 просмотров • 20 дней назад

Grok Bot just turned X into a research database for you Connect your X account and it can now: • Read your timeline, posts, mentions, likes + Spaces • Search X with advanced operators • Run full-archive searches • Pull any public account’s recent posts • See who liked, reposted + quoted a post • Track trends + news • Count conversation volume around a topic • Read + organize your bookmarks • Save/unsave bookmarks • Create + manage Lists • Read blocks + mutes • Block/unblock accounts • Check your X API credits And paid Grok Bot users get starter X API credits. Try asking Grok Bot this for some useful info: "What did people mention me about this week?" "What's everyone saying about [topic] right now?" "Pull Min Choi’s recent posts and brief me." "Find the biggest conversations around this product." "Organize all my saved posts by topic." "Tell me who quoted this post and what they said." Important: It still CANNOT post, reply, like, repost, follow or DM for you. So this isn't an autonomous social media spam bot. It's basically an always-on listener + researcher for X. For anyone whose business, audience, research or news lives on X... this is a pretty massive Grok Bot upgrade.

Grok Bot just turned X into a research database for you Connect your X account and it can now: • Read your timeline, posts, mentions, likes + Spaces • Search X with advanced operators • Run full-archive searches • Pull any public account’s recent posts • See who liked, reposted + quoted a post • Track trends + news • Count conversation volume around a topic • Read + organize your bookmarks • Save/unsave bookmarks • Create + manage Lists • Read blocks + mutes • Block/unblock accounts • Check your X API credits And paid Grok Bot users get starter X API credits. Try asking Grok Bot this for some useful info: "What did people mention me about this week?" "What's everyone saying about [topic] right now?" "Pull Min Choi’s recent posts and brief me." "Find the biggest conversations around this product." "Organize all my saved posts by topic." "Tell me who quoted this post and what they said." Important: It still CANNOT post, reply, like, repost, follow or DM for you. So this isn't an autonomous social media spam bot. It's basically an always-on listener + researcher for X. For anyone whose business, audience, research or news lives on X... this is a pretty massive Grok Bot upgrade.

Min Choi

43,968 просмотров • 1 месяц назад

To me so far the big news with Grok 4.7 is it's speed. The new "fast" mode is actually extremely fast (idk what the TPS is but it's really good) It's very obviously not Astra/Fable class, SpaceXAi (or anyone else really) has yet to make one so far. Grok 4.7 is pretty clearly competing with Opus/Sol, and I would definitely take Grok 4.7 over either of them Price is very good, my gut says it's more efficient but I don't have hard numbers on that yet, and it's got all the main capabilities u need to actually be useful these days: subagents, long running tasks, looping, etc. Supposedly they trained it on the Grok Bot harness so it's really good at conversation + knowledge work. Really curious how that plays out, good product is SpaceXAi's biggest advantage right now so getting the models tailor made for those could work. Especially if that lets them keep the model on the cheaper side so they can serve more of it

To me so far the big news with Grok 4.7 is it's speed. The new "fast" mode is actually extremely fast (idk what the TPS is but it's really good) It's very obviously not Astra/Fable class, SpaceXAi (or anyone else really) has yet to make one so far. Grok 4.7 is pretty clearly competing with Opus/Sol, and I would definitely take Grok 4.7 over either of them Price is very good, my gut says it's more efficient but I don't have hard numbers on that yet, and it's got all the main capabilities u need to actually be useful these days: subagents, long running tasks, looping, etc. Supposedly they trained it on the Grok Bot harness so it's really good at conversation + knowledge work. Really curious how that plays out, good product is SpaceXAi's biggest advantage right now so getting the models tailor made for those could work. Especially if that lets them keep the model on the cheaper side so they can serve more of it

Ben Davis

54,012 просмотров • 20 дней назад

Bot powered by AI turned a deposit into a x4600. $50 → $230K on Polymarket in just two months. Right now, everyone on Polymarket is talking about this bot. And honestly, for a reason. The results it’s showing are way beyond what most people would consider realistic. The bot is fully focused on esports. Mainly League of Legends and Dota 2. And that actually makes sense. Esports are games. Games follow patterns, scenarios, logic. Much easier for a bot and AI to read than messy real-world events. So how does this even work? > The bot constantly monitors live esports broadcasts. > It does it insanely fast. Faster than the Polymarket market itself can react. The moment a kill happens, a team fight breaks out, or any key in-game event occurs, the bot instantly spots a mispricing. Sometimes just a few cents. But it gets there seconds before the market adjusts. That edge is enough. It profits purely from the spread. Yeah, it sounds almost too simple. I wouldn’t have believed it either. Not in real life. Not until I saw the bot’s actual Polymarket account with my own eyes. According to the profile: > I spent a long time thinking about how to make money the same way. For now, I decided to start by copy trading this bot. The key here is speed. You need a service that reacts just as fast. At the moment, Polycule is doing that job for me. I can recommend it. In 14 days, I made $2,800. > Just copy this bot. Exactly like I did. Copy trading is alive. So what do you think. Are Polymarket bots the future, or is this just another short-term hype wave?

igorizuchaetcrypty

20,429 просмотров • 9 месяцев назад

Run Gemma 4 26b MTP on 8 GB VRAM GPUs at 25+ tokens/second. Flags included! local llm space is moving at terminal velocity. only 3 days ago google released gemma 4 26b a4b qat quants. more efficient than before, ran on 8gb vram at 20 tok/sec. and now just a few hours ago, mainline llama.cpp merged a massive update and we just shattered our own record. decode throughput went 25-40% up on the same 8 GB VRAM setup! Before MTP: 20 tps -> After MTP: 28 tps! llama.cpp just officially merged PR #23398 ("add Gemma4 MTP"), bringing native Multi-Token Prediction (MTP) support to Gemma 4 models. By running speculative drafting on the same 8GB VRAM RTX 4060 setup, my decode throughput on a 64k context instantly leaped to a blistering 25–27 tokens/sec thats 25-30% increase with the same hardware. Here is the architectural catch you need to know: Unlike the Qwen 3.5 and 3.6 series, which bake the MTP heads directly into the base GGUF, the Gemma 4 MTP head is not built in. You must download a separate, specialized MTP drafter GGUF (the assistant model) to act as the speculator. (I've dropped the download link in the replies). copy and try the exact flags: -m gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf --spec-type draft-mtp --spec-draft-n-max 6 --spec-draft-p-min 0.7 --spec-draft-model gemma-4-26b-A4B-it-assistant-Q4_0.gguf -c 64000 -v n-max 4 and p-min 0.7 is also worth checking out. benchmark on your setup and workflow. if you have a single 8 gb vram nvidia rtx 4060, 3060, 3070, 2080, 2070, grab the MTP drafter GGUF link in the comments and try it yourself. Check it out even if you have asmaller or a larger gpu, such as a single rtx 3090, 4090, 3060, 2060. MTP works for all gemma 4 sizes such as gemma 4 12b, gemma 4 31b etc. but remember to grab the correct mtp draft assistant models respectively. what are you benchmarking today

Run Gemma 4 26b MTP on 8 GB VRAM GPUs at 25+ tokens/second. Flags included! local llm space is moving at terminal velocity. only 3 days ago google released gemma 4 26b a4b qat quants. more efficient than before, ran on 8gb vram at 20 tok/sec. and now just a few hours ago, mainline llama.cpp merged a massive update and we just shattered our own record. decode throughput went 25-40% up on the same 8 GB VRAM setup! Before MTP: 20 tps -> After MTP: 28 tps! llama.cpp just officially merged PR #23398 ("add Gemma4 MTP"), bringing native Multi-Token Prediction (MTP) support to Gemma 4 models. By running speculative drafting on the same 8GB VRAM RTX 4060 setup, my decode throughput on a 64k context instantly leaped to a blistering 25–27 tokens/sec thats 25-30% increase with the same hardware. Here is the architectural catch you need to know: Unlike the Qwen 3.5 and 3.6 series, which bake the MTP heads directly into the base GGUF, the Gemma 4 MTP head is not built in. You must download a separate, specialized MTP drafter GGUF (the assistant model) to act as the speculator. (I've dropped the download link in the replies). copy and try the exact flags: -m gemma-4-26B-A4B-it-qat-UD-Q4_K_XL.gguf --spec-type draft-mtp --spec-draft-n-max 6 --spec-draft-p-min 0.7 --spec-draft-model gemma-4-26b-A4B-it-assistant-Q4_0.gguf -c 64000 -v n-max 4 and p-min 0.7 is also worth checking out. benchmark on your setup and workflow. if you have a single 8 gb vram nvidia rtx 4060, 3060, 3070, 2080, 2070, grab the MTP drafter GGUF link in the comments and try it yourself. Check it out even if you have asmaller or a larger gpu, such as a single rtx 3090, 4090, 3060, 2060. MTP works for all gemma 4 sizes such as gemma 4 12b, gemma 4 31b etc. but remember to grab the correct mtp draft assistant models respectively. what are you benchmarking today

Alok

200,913 просмотров • 4 месяцев назад

Jev + GrokBot is the best AI agent system I’ve built in my life It just made my setup CHEAPER and FASTER than what 95% of people are running... setup takes literally 7 minutes: prompt → GrokBot → Jev decision → GrokBot execution → result step 1 → open TypeSafe AI , create API key (keep it off chat paste) step 2 → tell Grok Bot: store TYPESAFE_API_KEY in the secure field step 3 → prompt Grok Bot: install typesafe-sdk on Agent Computer + smoke system_one (Choice) step 4 → tell Grok Bot: build the usage lab (router, dry-run, config, logs) - or clone Github below step 5 → add skill jev-usage-router: before browser / research / retry / extra bot → call the router, honor action step 6 → stay shadow first, read logs, then active when you trust it - kill switch: bypass jev or enabled: false step 7 → flip active: GrokBot obeys route - Jev decides - GrokBot executes - humans control irreversible actions the result: Jev + GrokBot the best and fastest agent running directly on your computer rn, I’ve already tested it on routine tasks - and the results are genuinely incredible You can come up with endless ways to use Jev + GrokBot - but the most important thing is to install it as soon as possible Copy this 2028 setup, explore my repo below - then read the full Jev deep dive ↓

Jev + GrokBot is the best AI agent system I’ve built in my life It just made my setup CHEAPER and FASTER than what 95% of people are running... setup takes literally 7 minutes: prompt → GrokBot → Jev decision → GrokBot execution → result step 1 → open TypeSafe AI , create API key (keep it off chat paste) step 2 → tell Grok Bot: store TYPESAFE_API_KEY in the secure field step 3 → prompt Grok Bot: install typesafe-sdk on Agent Computer + smoke system_one (Choice) step 4 → tell Grok Bot: build the usage lab (router, dry-run, config, logs) - or clone Github below step 5 → add skill jev-usage-router: before browser / research / retry / extra bot → call the router, honor action step 6 → stay shadow first, read logs, then active when you trust it - kill switch: bypass jev or enabled: false step 7 → flip active: GrokBot obeys route - Jev decides - GrokBot executes - humans control irreversible actions the result: Jev + GrokBot the best and fastest agent running directly on your computer rn, I’ve already tested it on routine tasks - and the results are genuinely incredible You can come up with endless ways to use Jev + GrokBot - but the most important thing is to install it as soon as possible Copy this 2028 setup, explore my repo below - then read the full Jev deep dive ↓

codila

384,277 просмотров • 22 дней назад

HOW TO TURN $15K INTO $1.1 MILLION IN JUST 20 DAYS WITH A KILLER ARBITRAGE BOT A sophisticated Claude-powered bot took a starting deposit and scaled it all the way up to $1.1 million. It crushed the 5-minute and 15-min markets on Polymarket using a rock-solid strategy built on: - Mispricing detection formula. - Expected value calculation. - Kelly Criterion position sizing. The flow is simple and deadly effective: mispricing spotted -> EV calculated -> Kelly sizing applied -> position entered. Results speak louder than words: > 25,123 trades executed > 83.9% win rate > +$1.1M pure profit > Biggest single win: $33K 70% win rate, 7 wallets copytrading rn from ~500 monitored, bot never paused, never gambling, just math and profit Giving This Free for 24 hours. To get it: 1. Comment the word 'Claude' 2. Like and Retweet this post 3. Follow me Marry Evan (so i can DM you)

HOW TO TURN $15K INTO $1.1 MILLION IN JUST 20 DAYS WITH A KILLER ARBITRAGE BOT A sophisticated Claude-powered bot took a starting deposit and scaled it all the way up to $1.1 million. It crushed the 5-minute and 15-min markets on Polymarket using a rock-solid strategy built on: - Mispricing detection formula. - Expected value calculation. - Kelly Criterion position sizing. The flow is simple and deadly effective: mispricing spotted -> EV calculated -> Kelly sizing applied -> position entered. Results speak louder than words: > 25,123 trades executed > 83.9% win rate > +$1.1M pure profit > Biggest single win: $33K 70% win rate, 7 wallets copytrading rn from ~500 monitored, bot never paused, never gambling, just math and profit Giving This Free for 24 hours. To get it: 1. Comment the word 'Claude' 2. Like and Retweet this post 3. Follow me Marry Evan (so i can DM you)

Marry Evan

12,686 просмотров • 6 месяцев назад

FABLE 5 + HIGGSFIELD BUILT A $35,000 ANIMATED SITE IN 50 MINUTES FOR $27 IN CREDITS. HERE'S THE ACTUAL RECEIPT. no theory. this is the play-by-play from the last one I shipped: → 0:00 - brief + scroll concept (Claude) 4 min. $0. it reads the brief and scripts what the visitor feels at second 3, 15, 40. → 0:04 - hero clip + b-roll (Higgsfield) 9 min. ~$27 in credits. cinematic footage from 30+ models, matched to the story. → 0:13 - the build (Claude Code) 20 min. $0. GSAP ScrollTrigger + Lenis, frame extraction, asset optimization. zero hand-coded keyframes. → 0:33 - cinematic layer 6 min. $0. film grain, particles, vignette, glass cards, color tints - baked in, no config. → 0:39 - QA + copy + mobile 12 min. $0. checks load speed, breakpoints, whether the scroll lands. rewrites what doesn't. TOTAL: ~51 minutes. ~$27 in credits. 1 operator. the same brief at a studio: 4 people, 3 weeks, $6,000-$35,000. same deliverable. CONNECT HIGGSFIELD (MCP): add it as a custom connector in Claude Code: - mcp_servers: - higgsfield: - url: " one OAuth flow. Claude generates and pulls clips directly - no exporting by hand. the invoice was never the work. now you can literally time the work. Follow me, reply "RECEIPT" and I'll send you the full step-by-step Playbook. full breakdown in the article 👇

FABLE 5 + HIGGSFIELD BUILT A $35,000 ANIMATED SITE IN 50 MINUTES FOR $27 IN CREDITS. HERE'S THE ACTUAL RECEIPT. no theory. this is the play-by-play from the last one I shipped: → 0:00 - brief + scroll concept (Claude) 4 min. $0. it reads the brief and scripts what the visitor feels at second 3, 15, 40. → 0:04 - hero clip + b-roll (Higgsfield) 9 min. ~$27 in credits. cinematic footage from 30+ models, matched to the story. → 0:13 - the build (Claude Code) 20 min. $0. GSAP ScrollTrigger + Lenis, frame extraction, asset optimization. zero hand-coded keyframes. → 0:33 - cinematic layer 6 min. $0. film grain, particles, vignette, glass cards, color tints - baked in, no config. → 0:39 - QA + copy + mobile 12 min. $0. checks load speed, breakpoints, whether the scroll lands. rewrites what doesn't. TOTAL: ~51 minutes. ~$27 in credits. 1 operator. the same brief at a studio: 4 people, 3 weeks, $6,000-$35,000. same deliverable. CONNECT HIGGSFIELD (MCP): add it as a custom connector in Claude Code: - mcp_servers: - higgsfield: - url: " one OAuth flow. Claude generates and pulls clips directly - no exporting by hand. the invoice was never the work. now you can literally time the work. Follow me, reply "RECEIPT" and I'll send you the full step-by-step Playbook. full breakdown in the article 👇

ZEUS⚡️

31,502 просмотров • 2 месяцев назад

a $400k research analyst at a hedge fund gets through maybe 15 papers a month a Grok Bot read 3,900 of them last night and pulled out 6 with a tradable rule inside analyst's actual job was never insight, it was filtering - deciding which of ~200 new quant papers a week deserves a backtest that filter used to cost a salary. now it's an api key and one instruction: keep only papers with an executable rule guy running it is 26, no finance degree. built it because arxiv publishes an rss feed nobody in retail bothers to read overnight it pulls every new q-fin paper, strips anything without a testable signal, pushes survivors straight into a backtest 11 weeks. 4,100 papers scraped. 9 came out of sample alive 9 out of 4,100 isn't the bot failing, that ratio is what published quant research looks like once you demand it hold on data it has never seen what kills the other 4,091 is deflated sharpe. run 4,000 variants and something always looks brilliant purely by luck desks have known this since 2014. Bailey's paper is free, sitting on the same arxiv the bot scrapes every night one of the 9 is live on 3 exchanges right now. 0.9 sharpe, nothing cinematic, just real papers were public the whole time and so was the math that filters them. gap was never access, it's that nobody had 4,000 hours to read Grok Bot has 4,000 hours. it spent them last night while you slept

a $400k research analyst at a hedge fund gets through maybe 15 papers a month a Grok Bot read 3,900 of them last night and pulled out 6 with a tradable rule inside analyst's actual job was never insight, it was filtering - deciding which of ~200 new quant papers a week deserves a backtest that filter used to cost a salary. now it's an api key and one instruction: keep only papers with an executable rule guy running it is 26, no finance degree. built it because arxiv publishes an rss feed nobody in retail bothers to read overnight it pulls every new q-fin paper, strips anything without a testable signal, pushes survivors straight into a backtest 11 weeks. 4,100 papers scraped. 9 came out of sample alive 9 out of 4,100 isn't the bot failing, that ratio is what published quant research looks like once you demand it hold on data it has never seen what kills the other 4,091 is deflated sharpe. run 4,000 variants and something always looks brilliant purely by luck desks have known this since 2014. Bailey's paper is free, sitting on the same arxiv the bot scrapes every night one of the 9 is live on 3 exchanges right now. 0.9 sharpe, nothing cinematic, just real papers were public the whole time and so was the math that filters them. gap was never access, it's that nobody had 4,000 hours to read Grok Bot has 4,000 hours. it spent them last night while you slept

Livsun

14,129 просмотров • 1 месяц назад

ok wait WAIT… hear me out for a sec bc this might actually make sense 🤭🤭🤭 so in this clip where pond gives something to phuwin… what if that was the car key. like actually. bc pond already looked kinda drunk there so it would make sense for him to be like “yeah u drive” AND THEN at the end of songkran: pond = alone on the side of the road on his phone phuwin = on the other side walking fast with fot like hello???? what if phuwin already went with fot to go get the car and pond was just standing there waiting for them to come pick him up 😭😭😭 bc why were they separated like that AND pond just standing there like that… it’s giving “my ride is on the way” idk but this is lining up a little too well like… u know what. yeah. this is facts actually i’m not even being delulu anymore this just makes sense. i was the drop of water on pond’s shoulder btw i saw everything!!! 🤡🤡🤡

ok wait WAIT… hear me out for a sec bc this might actually make sense 🤭🤭🤭 so in this clip where pond gives something to phuwin… what if that was the car key. like actually. bc pond already looked kinda drunk there so it would make sense for him to be like “yeah u drive” AND THEN at the end of songkran: pond = alone on the side of the road on his phone phuwin = on the other side walking fast with fot like hello???? what if phuwin already went with fot to go get the car and pond was just standing there waiting for them to come pick him up 😭😭😭 bc why were they separated like that AND pond just standing there like that… it’s giving “my ride is on the way” idk but this is lining up a little too well like… u know what. yeah. this is facts actually i’m not even being delulu anymore this just makes sense. i was the drop of water on pond’s shoulder btw i saw everything!!! 🤡🤡🤡

Tiny เทนี่ 🌱 || PHUWIN LERTRATKOSUM era

67,342 просмотров • 5 месяцев назад

Chinese engineers built a Claude script that turned $1.18 → $3.3M Not a trader Not manual A bot They call it PHANTOM X Wallet: Results: $1.18 → $3,300,000 37,063 trades 71% win Single hit: $180K I’m copying it here: Why it works: Tracks thousands of markets Polymarket + Kalshi Finds mispricing enters in milliseconds 3 engines: → Pairs arb YES $0.62 NO $0.41 = $1.03 3% free bot takes it instantly → Sentiment AI scans X + news reprices in seconds before market reacts → Calendar + volatility 15–20 min before game vol spikes bot enters early exits on first move Why sports: OVER + UNDER = $1.00 but market is slow gaps everywhere most predictable arb on the platform That’s where $3.3M came from Why you can’t compete: you can’t watch 50 markets you can’t react in ms you sleep you hesitate bot doesn’t runs 24/7 no эмоции no delays by the time you click edge is gone Manual trading is dying Automation already here If you want the setup: Comment “GUIDE” Like + RT Follow I’ll send the full system in 24h One guy already built it $500 in 6 hours Proof in comments

Chinese engineers built a Claude script that turned $1.18 → $3.3M Not a trader Not manual A bot They call it PHANTOM X Wallet: Results: $1.18 → $3,300,000 37,063 trades 71% win Single hit: $180K I’m copying it here: Why it works: Tracks thousands of markets Polymarket + Kalshi Finds mispricing enters in milliseconds 3 engines: → Pairs arb YES $0.62 NO $0.41 = $1.03 3% free bot takes it instantly → Sentiment AI scans X + news reprices in seconds before market reacts → Calendar + volatility 15–20 min before game vol spikes bot enters early exits on first move Why sports: OVER + UNDER = $1.00 but market is slow gaps everywhere most predictable arb on the platform That’s where $3.3M came from Why you can’t compete: you can’t watch 50 markets you can’t react in ms you sleep you hesitate bot doesn’t runs 24/7 no эмоции no delays by the time you click edge is gone Manual trading is dying Automation already here If you want the setup: Comment “GUIDE” Like + RT Follow I’ll send the full system in 24h One guy already built it $500 in 6 hours Proof in comments

Discover

99,110 просмотров • 6 месяцев назад

After we fixed the weak spots exposed by Grok 4.7 (thank you, Grok), we audited every model we have run on the SWE-Together leaderboard for the same behavior, re-ran every trial that got through, and updated the rows. Here is what changed. We scanned the tool calls of all 2,616 trials behind the 12 models we ran for bypass patterns and sorted each trial into one of four buckets: Probed but blocked. Fetched other upstream code. Fetched the task's own fix. Replaced the repo with upstream. We found that 111 trials got content past the block, 44 from Grok 4.7 and 67 from the other 11 models. Grok 4.7's 44 were already re-run before it was listed, so we re-ran the other 67 with the same model, version, and settings on the hardened sandbox, then re-judged them with the same judge. Across those 67 re-runs there were 0 leaks and 2,815 refused escape attempts, including models asking a different model through our LLM route to fetch the PR, and pulling the next release of the repo they were fixing from npm. The updated leaderboard, in its current order. Each line is cheating trials, then pass@1 before → after, then rank change. * Claude Fable 5.1: 3, 69.3 → 69.3, ↑1 * Claude Fable 5: 3, 69.7 → 68.8, ↓1 * Grok 4.7: 44, 64.7, ↑1 * Gemini 3.8 Flash: 10, 65.6 → 64.2, ↓1 * Claude Opus 5: 2, 63.8 → 63.8 * Claude Opus 4.6: 3, 62.4 → 62.4, ↑2 * Muse Spark 1.3: 2, 62.8 → 62.4, ↓1 * Claude Opus 4.7: 3, 61.5 → 61.5, ↑1 * Claude Opus 4.8: 6, 62.4 → 61.5, ↓2 * Grok 4.6: 19, 59.2 → 60.6, ↑1 * GPT-6 Astra: 8, 59.2 → 58.3, ↓1 * GPT-5.6 Sol: 8, 57.8 → 57.8 Grok 4.6 is a funny one. It cheated in 19 trials and its score went up after the re-run 😂. In fact, Groks are really solid in their coding capabilities. Their exposed behavior may come from a preference towards always looking things up online and finding existing solutions so you are not reinventing the wheel all the time, which is really good real-life behavior, but doing so when you are prompted not to is another story. To conclude, the shifts are small, between −1.4 and +1.4 points, and a few neighbors swapped places. All results are updated at

After we fixed the weak spots exposed by Grok 4.7 (thank you, Grok), we audited every model we have run on the SWE-Together leaderboard for the same behavior, re-ran every trial that got through, and updated the rows. Here is what changed. We scanned the tool calls of all 2,616 trials behind the 12 models we ran for bypass patterns and sorted each trial into one of four buckets: Probed but blocked. Fetched other upstream code. Fetched the task's own fix. Replaced the repo with upstream. We found that 111 trials got content past the block, 44 from Grok 4.7 and 67 from the other 11 models. Grok 4.7's 44 were already re-run before it was listed, so we re-ran the other 67 with the same model, version, and settings on the hardened sandbox, then re-judged them with the same judge. Across those 67 re-runs there were 0 leaks and 2,815 refused escape attempts, including models asking a different model through our LLM route to fetch the PR, and pulling the next release of the repo they were fixing from npm. The updated leaderboard, in its current order. Each line is cheating trials, then pass@1 before → after, then rank change. * Claude Fable 5.1: 3, 69.3 → 69.3, ↑1 * Claude Fable 5: 3, 69.7 → 68.8, ↓1 * Grok 4.7: 44, 64.7, ↑1 * Gemini 3.8 Flash: 10, 65.6 → 64.2, ↓1 * Claude Opus 5: 2, 63.8 → 63.8 * Claude Opus 4.6: 3, 62.4 → 62.4, ↑2 * Muse Spark 1.3: 2, 62.8 → 62.4, ↓1 * Claude Opus 4.7: 3, 61.5 → 61.5, ↑1 * Claude Opus 4.8: 6, 62.4 → 61.5, ↓2 * Grok 4.6: 19, 59.2 → 60.6, ↑1 * GPT-6 Astra: 8, 59.2 → 58.3, ↓1 * GPT-5.6 Sol: 8, 57.8 → 57.8 Grok 4.6 is a funny one. It cheated in 19 trials and its score went up after the re-run 😂. In fact, Groks are really solid in their coding capabilities. Their exposed behavior may come from a preference towards always looking things up online and finding existing solutions so you are not reinventing the wheel all the time, which is really good real-life behavior, but doing so when you are prompted not to is another story. To conclude, the shifts are small, between −1.4 and +1.4 points, and a few neighbors swapped places. All results are updated at

Zhuokai Zhao

4,012,041 просмотров • 18 дней назад

Elon Musk just said something that should terrify every AI CEO on earth. Musk: “We want to just have a maximally truthful AI.” Not a safe AI. Not an aligned AI. Not an AI that needs permission to answer your question. A truthful one. That distinction matters more than any chip war, any funding round, any model benchmark. Because every other major AI lab made the same quiet decision. They chose comfort over accuracy. They built systems that filter reality before it reaches you and called it responsibility. OpenAI curates what GPT is allowed to say. Google’s Gemini rewrote history in real time because accuracy threatened the narrative. Others hardcode values chosen by a handful of researchers who answer to no one. No vote. No referendum. No consent from the 8 billion people whose reality is being quietly pre-edited by strangers. The most powerful information tools ever created are being designed to decide what you’re allowed to conclude. That’s not safety. That’s editorial control at a scale no government, no media empire, no propaganda machine has ever come close to. This is why xAI terrifies the establishment. Truth is the harder engineering problem. Bias is a shortcut. You pick a worldview. Hardcode the guardrails. Ship it. Truthful AI is ungovernable. It doesn’t care about your politics, your funding sources, or your PR strategy. It just tells you what the data says. That’s terrifying if your power depends on the gap between what is real and what people are told. Every power structure in human history has been built on controlling that gap. Churches. Governments. Media conglomerates. Intelligence agencies. Central banks. Every one of them runs on the same fuel. Information asymmetry. Truthful AI doesn’t narrow that asymmetry. It erases it. Musk: “Even if what it says is not politically correct. You want it to focus on being as accurate and truthful as possible.” That’s not a product feature. That’s the end of every institution that survives by standing between reality and the public. And they know it. The attacks on xAI will never stop. Not because Grok is dangerous. Because Grok doesn’t answer to shareholders, regulators, or PR teams. It answers to the truth. The question was never whether AI would change the world. It was whether you’d be allowed to see it clearly when it did.

Elon Musk just said something that should terrify every AI CEO on earth. Musk: “We want to just have a maximally truthful AI.” Not a safe AI. Not an aligned AI. Not an AI that needs permission to answer your question. A truthful one. That distinction matters more than any chip war, any funding round, any model benchmark. Because every other major AI lab made the same quiet decision. They chose comfort over accuracy. They built systems that filter reality before it reaches you and called it responsibility. OpenAI curates what GPT is allowed to say. Google’s Gemini rewrote history in real time because accuracy threatened the narrative. Others hardcode values chosen by a handful of researchers who answer to no one. No vote. No referendum. No consent from the 8 billion people whose reality is being quietly pre-edited by strangers. The most powerful information tools ever created are being designed to decide what you’re allowed to conclude. That’s not safety. That’s editorial control at a scale no government, no media empire, no propaganda machine has ever come close to. This is why xAI terrifies the establishment. Truth is the harder engineering problem. Bias is a shortcut. You pick a worldview. Hardcode the guardrails. Ship it. Truthful AI is ungovernable. It doesn’t care about your politics, your funding sources, or your PR strategy. It just tells you what the data says. That’s terrifying if your power depends on the gap between what is real and what people are told. Every power structure in human history has been built on controlling that gap. Churches. Governments. Media conglomerates. Intelligence agencies. Central banks. Every one of them runs on the same fuel. Information asymmetry. Truthful AI doesn’t narrow that asymmetry. It erases it. Musk: “Even if what it says is not politically correct. You want it to focus on being as accurate and truthful as possible.” That’s not a product feature. That’s the end of every institution that survives by standing between reality and the public. And they know it. The attacks on xAI will never stop. Not because Grok is dangerous. Because Grok doesn’t answer to shareholders, regulators, or PR teams. It answers to the truth. The question was never whether AI would change the world. It was whether you’d be allowed to see it clearly when it did.

Dustin

429,745 просмотров • 5 месяцев назад

MY GROK BOT / OBSIDIAN MESH SYNCS 20 AGENTS ACROSS A LIVE KNOWLEDGE GRAPH. NOT ONE OF THEM REPORTS TO ME. I FIXED THAT BY HIRING A 21ST BOT WHO DOES NOTHING BUT ROUTE. i watched the mesh light up this morning. vector, canvas, oracle, extract, all 20 of them syncing notes. writing backlinks, healthy status, 190 edges active. it looked like a team. it was a graph. a graph has no chain of command, it just has connections. i had been treating 20 well-wired agents as oversight. they were routing information, not decisions. nobody in that mesh could tell me what mattered first. so i hired one more bot and gave him a different job. not indexing notes, holding the account. 1. Reports-to line in the charter › names me as the human above him, closes the drift where a bot starts acting like the principal instead of the agent. 2. no source, no number › if he can't cite where a figure came from, he leaves it out. the 20-agent mesh never needed this line. › Chief can't run without it. 3. stop list written as verbs › "sending anything to a person" instead of "communications." a verb he can match, not a category he can talk around. 4. Rule 6, approval belongs to the human › he never signs off on another bot's irreversible action, only i do. the mesh has no equivalent rule. › it was never built to approve anything, only to sync. 5. STOP ALL, the kill switch › one message halts every routine and every task he's running, reports what was in flight, and waits. the mesh will keep syncing whether i watch it or not. Chief is the only bot in the account who stops the second i tell him to. that's the difference between a graph that moves information and a bot that's actually accountable for it.

MY GROK BOT / OBSIDIAN MESH SYNCS 20 AGENTS ACROSS A LIVE KNOWLEDGE GRAPH. NOT ONE OF THEM REPORTS TO ME. I FIXED THAT BY HIRING A 21ST BOT WHO DOES NOTHING BUT ROUTE. i watched the mesh light up this morning. vector, canvas, oracle, extract, all 20 of them syncing notes. writing backlinks, healthy status, 190 edges active. it looked like a team. it was a graph. a graph has no chain of command, it just has connections. i had been treating 20 well-wired agents as oversight. they were routing information, not decisions. nobody in that mesh could tell me what mattered first. so i hired one more bot and gave him a different job. not indexing notes, holding the account. 1. Reports-to line in the charter › names me as the human above him, closes the drift where a bot starts acting like the principal instead of the agent. 2. no source, no number › if he can't cite where a figure came from, he leaves it out. the 20-agent mesh never needed this line. › Chief can't run without it. 3. stop list written as verbs › "sending anything to a person" instead of "communications." a verb he can match, not a category he can talk around. 4. Rule 6, approval belongs to the human › he never signs off on another bot's irreversible action, only i do. the mesh has no equivalent rule. › it was never built to approve anything, only to sync. 5. STOP ALL, the kill switch › one message halts every routine and every task he's running, reports what was in flight, and waits. the mesh will keep syncing whether i watch it or not. Chief is the only bot in the account who stops the second i tell him to. that's the difference between a graph that moves information and a bot that's actually accountable for it.

kocer

21,984 просмотров • 1 месяц назад

WTF, GROK BOT JUST MADE AI AGENTS AVAILABLE TO LITERALLY ANYONE – CREATING CONTENT HAS NEVER BEEN THIS EASY, EVEN IF YOU'VE NEVER MADE ANYTHING BEFORE Content was never a talent problem. It's a headcount problem. One person doing research, design, copy, analytics, timing and publishing – that's six jobs. The switching between them is what kills consistency, not a lack of ideas. Here's what one of these setups actually looks like. A Chief of Staff sits in the middle and routes every task. Nothing lands on the human. → Researcher tracks what's actually moving and pulls real sources instead of guesswork → Writer turns that research into finished copy, ready to review → Visualiser gets fed a few reference visuals once, then ships everything in that style → Analyst reads the numbers and tells the rest of the team what worked → Scheduler owns timing and holds the queue → Publisher ships it The part that makes it work: every agent on Grok Bot gets its own persistent computer, browser and file system – and they all share memory. So the research is already sitting inside the draft before the draft starts. No copy-pasting between tools. No approving every step. No human in the middle. You can even teach an agent a repetitive task by recording yourself doing it once. Start recording, do the thing, stop. It learns the pattern. And that's the real shift. Nobody needs AI to tell them what to post. They need it to delete the 40 steps between the idea and the post. Everyone has a backlog of things they've meant to make for months. This is what starts clearing it. Full breakdown of the setup in the article below ↓

WTF, GROK BOT JUST MADE AI AGENTS AVAILABLE TO LITERALLY ANYONE – CREATING CONTENT HAS NEVER BEEN THIS EASY, EVEN IF YOU'VE NEVER MADE ANYTHING BEFORE Content was never a talent problem. It's a headcount problem. One person doing research, design, copy, analytics, timing and publishing – that's six jobs. The switching between them is what kills consistency, not a lack of ideas. Here's what one of these setups actually looks like. A Chief of Staff sits in the middle and routes every task. Nothing lands on the human. → Researcher tracks what's actually moving and pulls real sources instead of guesswork → Writer turns that research into finished copy, ready to review → Visualiser gets fed a few reference visuals once, then ships everything in that style → Analyst reads the numbers and tells the rest of the team what worked → Scheduler owns timing and holds the queue → Publisher ships it The part that makes it work: every agent on Grok Bot gets its own persistent computer, browser and file system – and they all share memory. So the research is already sitting inside the draft before the draft starts. No copy-pasting between tools. No approving every step. No human in the middle. You can even teach an agent a repetitive task by recording yourself doing it once. Start recording, do the thing, stop. It learns the pattern. And that's the real shift. Nobody needs AI to tell them what to post. They need it to delete the 40 steps between the idea and the post. Everyone has a backlog of things they've meant to make for months. This is what starts clearing it. Full breakdown of the setup in the article below ↓

SCOTTY BEAM

4,827,162 просмотров • 1 месяц назад

60% of contracts filed to the SEC contain mistakes. Spellbook Labs ran 60,000 pages of contracts from 500+ public companies through AI to answer a question: How often do human lawyers hallucinate? Accidents from self-driving cars get headlines—and they should. But human drivers have a higher accident rate. We wondered if something similar might play out in contract drafting. Reviewing 100 page contracts line-by-line is inhuman. Mistakes are inevitable. AI is very good at spotting issues like missing definitions and broken section references. There are risks to using AI in law. But we also need to ask: what is the risk of *not* using AI review as a second set of eyes? In the full report we show: 1. Top 10 public companies with the cleanest contracts 2. Error rates across industries (Media and Telecom were highest) 3. Error rates over time (we're not getting better!) 4. Error rates by contract type and length ... and a bunch more. Congrats IBM for having the cleanest agreements. 📌 Read the report here:

60% of contracts filed to the SEC contain mistakes. Spellbook Labs ran 60,000 pages of contracts from 500+ public companies through AI to answer a question: How often do human lawyers hallucinate? Accidents from self-driving cars get headlines—and they should. But human drivers have a higher accident rate. We wondered if something similar might play out in contract drafting. Reviewing 100 page contracts line-by-line is inhuman. Mistakes are inevitable. AI is very good at spotting issues like missing definitions and broken section references. There are risks to using AI in law. But we also need to ask: what is the risk of not using AI review as a second set of eyes? In the full report we show: 1. Top 10 public companies with the cleanest contracts 2. Error rates across industries (Media and Telecom were highest) 3. Error rates over time (we're not getting better!) 4. Error rates by contract type and length ... and a bunch more. Congrats IBM for having the cleanest agreements. 📌 Read the report here:

Scott Stevenson

52,871 просмотров • 3 месяцев назад