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SpaceX’s AI arm is partnering with coding startup Cursor in a deal worth no less than $10 billion and as much as $60 billion. Can the pair topple the rising Anthropic-OpenAI AI coding axis? A lot of money is being bet that the answer is yes. Next up, Lon...

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This Week in Startups

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19,991 次观看 • 2 个月前 •via X (Twitter)

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Claude Mythos found critical zero-days in every major OS and browser. Jason calls it a cyber weapon of mass destruction. Meanwhile: Small language models may be about to collapse the value of frontier models entirely. It’s a new TWiST with special guest AI expert Rob May of NeuroMetric, PLUS we’re checking out Death by Clawd with its founder, Gyani, plus a special non-sponsored message from our roving Miami crypto correspondent Nick “Choose Rich” O’Neil. 0:00 Anthropic's new, powerful 'Mythos' model 3:50 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 5:26 Neurometric's Rob May joins the show 10:04 Sam Altman's talent exodus 10:54 Render - Go to to apply for the Render Startup Program. You'll get anywhere from $500 to $100,000 in free credits. 11:50 Has Anthropic Passed OpenAI? 15:44 When will Claude release Mythos? Polymarket: 18:32 The AI race turns existential 19:16 Would Anthropic's model give the CIA the ability to hack a foreign government? 20:12 Grasshopper Bank - Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 21:19 Should AI be nationalized? 29:43 Subsidizing secret AI development. 30:25 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 31:29 How much of the military's $1.5T will go to AI cybersecurity? 35:17 Nick O'Neill's "not sponsored" call-in. 38:24 What is an SLM? 42:01 Tactical/Practical: How can you tune SLMs 45:43 How Neurometric can afford 100M free tokens per month for its users? 49:04 What is "harness engineering"? 50:58 Tactical/ Practical: Every Reddit rant is a startup idea 1:00:25 Why Meta is the most un-innovative AI company in the world. 1:03:43 Gyani of Deathbclawd joins the show — Is your company COOKED? cc: @jason, alex 🏴‍☠️🇺🇸🇺🇦, Rob May, NeuroMetric AI, Nick O’Neill, DeathByClawd 🎥 Watch the full episode here 👇
1:16:48

Claude Mythos found critical zero-days in every major OS and browser. Jason calls it a cyber weapon of mass destruction. Meanwhile: Small language models may be about to collapse the value of frontier models entirely. It’s a new TWiST with special guest AI expert Rob May of NeuroMetric, PLUS we’re checking out Death by Clawd with its founder, Gyani, plus a special non-sponsored message from our roving Miami crypto correspondent Nick “Choose Rich” O’Neil. 0:00 Anthropic's new, powerful 'Mythos' model 3:50 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 5:26 Neurometric's Rob May joins the show 10:04 Sam Altman's talent exodus 10:54 Render - Go to to apply for the Render Startup Program. You'll get anywhere from $500 to $100,000 in free credits. 11:50 Has Anthropic Passed OpenAI? 15:44 When will Claude release Mythos? Polymarket: 18:32 The AI race turns existential 19:16 Would Anthropic's model give the CIA the ability to hack a foreign government? 20:12 Grasshopper Bank - Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 21:19 Should AI be nationalized? 29:43 Subsidizing secret AI development. 30:25 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 31:29 How much of the military's $1.5T will go to AI cybersecurity? 35:17 Nick O'Neill's "not sponsored" call-in. 38:24 What is an SLM? 42:01 Tactical/Practical: How can you tune SLMs 45:43 How Neurometric can afford 100M free tokens per month for its users? 49:04 What is "harness engineering"? 50:58 Tactical/ Practical: Every Reddit rant is a startup idea 1:00:25 Why Meta is the most un-innovative AI company in the world. 1:03:43 Gyani of Deathbclawd joins the show — Is your company COOKED? cc: @jason, alex 🏴‍☠️🇺🇸🇺🇦, Rob May, NeuroMetric AI, Nick O’Neill, DeathByClawd 🎥 Watch the full episode here 👇

This Week in Startups

33,452 次观看 • 3 个月前

✨New demo: what if vibe coding felt more visual? Brian Lovin Mary Rose Cook and I did a game jam using Notion as our "IDE": launching Cursor agents from a task board, and making a custom image for each task 😎 The demo shows 3 ideas for the future of agents: 1) Agents should collaborate across apps. Each app has its focus--Notion AI is good at drafting specs and organizing tasks; Cursor is good at coding. So let them specialize! Today we're launching a new integration where Notion AI can kick off Cursor Cloud Agents to do coding tasks. The Cursor API accepts natural language prompts, so I think of this as "cross-app sub-agents" -- it's kinda cute how it resembles humans hiring outside contractors 😊 BTW: the parallelism of cloud agents is incredibly freeing for creativity, but it also creates a new problem: sooo much work to keep track of! Which brings us to the next idea... 2) Agent orchestration is a data visualization problem. A powerful frame for designing agent UIs is to think of the chat transcripts as the "raw data" and ask: what visual projections might help people make sense of this data at scale? We need to engage our human GPUs -- our visual processing -- to understand what the computer GPUs are doing for us! One thing we can do is use AI to populate traditional UIs like progress bars and status updates. But there are also new possibilities now... For example: when you have a lot going on, it can be hard to identify tasks just by text titles. So we tried generating an AI image for each task -- turns out this helps a lot by giving it a unique visual identity! And of course, it also just makes it super fun to build with friends 😃 Speaking of friends... 3) The future of coding is collaborative. Sometimes it feels like IC engineers are being reduced to middle managers: shuffling information between the team's context and the coding agents that they individually manage. The solution: bring all the people and agents into one shared space, with shared context and visibility! In the video you can get a glimpse of how this feels. Mary, Brian and I record ourselves chatting about ideas, and then we use AI to turn that conversation into a list of tasks on a shared board. As the ideas get built in parallel, we can all monitor progress and review the work together, nothing is siloed. My main takeaway from this game jam was: damn, creativity with friends, at the speed of conversation, is incredibly fun. --- Our goal here is to let anyone use Notion as a fun and creative "software factory" to build software together with your team. Give the Cursor integration a shot and let us know what you think! (AI Image gen in Notion isn't GA yet, but coming soon and already out to some users) And let me know if you'd want a template or more detailed instructions on the setup we showed in this demo...
12:37

✨New demo: what if vibe coding felt more visual? Brian Lovin Mary Rose Cook and I did a game jam using Notion as our "IDE": launching Cursor agents from a task board, and making a custom image for each task 😎 The demo shows 3 ideas for the future of agents: 1) Agents should collaborate across apps. Each app has its focus--Notion AI is good at drafting specs and organizing tasks; Cursor is good at coding. So let them specialize! Today we're launching a new integration where Notion AI can kick off Cursor Cloud Agents to do coding tasks. The Cursor API accepts natural language prompts, so I think of this as "cross-app sub-agents" -- it's kinda cute how it resembles humans hiring outside contractors 😊 BTW: the parallelism of cloud agents is incredibly freeing for creativity, but it also creates a new problem: sooo much work to keep track of! Which brings us to the next idea... 2) Agent orchestration is a data visualization problem. A powerful frame for designing agent UIs is to think of the chat transcripts as the "raw data" and ask: what visual projections might help people make sense of this data at scale? We need to engage our human GPUs -- our visual processing -- to understand what the computer GPUs are doing for us! One thing we can do is use AI to populate traditional UIs like progress bars and status updates. But there are also new possibilities now... For example: when you have a lot going on, it can be hard to identify tasks just by text titles. So we tried generating an AI image for each task -- turns out this helps a lot by giving it a unique visual identity! And of course, it also just makes it super fun to build with friends 😃 Speaking of friends... 3) The future of coding is collaborative. Sometimes it feels like IC engineers are being reduced to middle managers: shuffling information between the team's context and the coding agents that they individually manage. The solution: bring all the people and agents into one shared space, with shared context and visibility! In the video you can get a glimpse of how this feels. Mary, Brian and I record ourselves chatting about ideas, and then we use AI to turn that conversation into a list of tasks on a shared board. As the ideas get built in parallel, we can all monitor progress and review the work together, nothing is siloed. My main takeaway from this game jam was: damn, creativity with friends, at the speed of conversation, is incredibly fun. --- Our goal here is to let anyone use Notion as a fun and creative "software factory" to build software together with your team. Give the Cursor integration a shot and let us know what you think! (AI Image gen in Notion isn't GA yet, but coming soon and already out to some users) And let me know if you'd want a template or more detailed instructions on the setup we showed in this demo...

Geoffrey Litt

88,919 次观看 • 4 个月前

A subnet founder allegedly walked away with $10M in TAO and torched his own community in the process. On TWiST, Mark Jeffrey of Stillcore Capital joins us to break down what really happened with Templar/Covenant, the overall fixes that co-founder Const has proposed, and why Bittensor’s incentive engine may have been a victim of its own success. PLUS we’re joined by subnet operators Will Squires and Steffan Cruz (of MacroCosmos) and Ken Miyachi of BitMind to get their perspective on the controversy, and to demo the exciting projects they’re still building on the blockchain. 0:00 Mark Jeffrey joins the show! 2:18 How Mark Jeffrey learned about Bittensor. 6:17 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 7:22 Mark Jeffrey's Bittensor investments. 9:25 Check out our discussion with Nova: 10:16 Sentry - New users can get $240 in free credits when they go to and use the code TWIST 10:41 Check out Ridges! 11:53 How trading alpha tokens works on Bittensor 12:44 Subnet drama: what happened? 16:01 Do subnet owners have too much power? 18:33 Check out our conversation with Sam Dare (2268): 19:10 How Sam Dare should've handled walking away (per Mark Jeffrey) 20:02 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit to learn more. 23:29 Who should subnets be owned by? 24:02 Ken Miyachi from BitMind joins the show 30:56 Netsuite - Get the free business guide Demystifying AI at 31:06 Ken's $3M raise & investors (Arch, Canonical, Mechanism) 33:18 Token vs. equity: how to think about a subnet investment. 41:57 Will Squires and Stefan Kruse of MacroCosmos join the show 42:54 How MacroCosmos lets anyone become a compute provider. 56:29 Stefan on the Covenant drama: "disappointing, but solvable" 1:02:11 Off-duty with J-Cal, Mark Jeffrey, and Lon Harris 1:02:48 Bieber vs. Carpenter: does Coachella owe you a spectacle? 1:15:20 Jason says Staples should pay the "Staples baddie" $1M/year cc: @jason, Lon Harris, Mark Jeffrey, const, Distributed State, templar, covenant, Macrocosmos, Apex・SN1, IOTA ・ SN9, Ken Jon, BitMind BitMindAI 🎥 Watch the full episode here 👇
1:18:38

A subnet founder allegedly walked away with $10M in TAO and torched his own community in the process. On TWiST, Mark Jeffrey of Stillcore Capital joins us to break down what really happened with Templar/Covenant, the overall fixes that co-founder Const has proposed, and why Bittensor’s incentive engine may have been a victim of its own success. PLUS we’re joined by subnet operators Will Squires and Steffan Cruz (of MacroCosmos) and Ken Miyachi of BitMind to get their perspective on the controversy, and to demo the exciting projects they’re still building on the blockchain. 0:00 Mark Jeffrey joins the show! 2:18 How Mark Jeffrey learned about Bittensor. 6:17 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 7:22 Mark Jeffrey's Bittensor investments. 9:25 Check out our discussion with Nova: 10:16 Sentry - New users can get $240 in free credits when they go to and use the code TWIST 10:41 Check out Ridges! 11:53 How trading alpha tokens works on Bittensor 12:44 Subnet drama: what happened? 16:01 Do subnet owners have too much power? 18:33 Check out our conversation with Sam Dare (2268): 19:10 How Sam Dare should've handled walking away (per Mark Jeffrey) 20:02 Deel - Founders scale faster on Deel. Set up payroll for any country in minutes, hire anyone anywhere, get visas handled fast, and get back to building. Visit to learn more. 23:29 Who should subnets be owned by? 24:02 Ken Miyachi from BitMind joins the show 30:56 Netsuite - Get the free business guide Demystifying AI at 31:06 Ken's $3M raise & investors (Arch, Canonical, Mechanism) 33:18 Token vs. equity: how to think about a subnet investment. 41:57 Will Squires and Stefan Kruse of MacroCosmos join the show 42:54 How MacroCosmos lets anyone become a compute provider. 56:29 Stefan on the Covenant drama: "disappointing, but solvable" 1:02:11 Off-duty with J-Cal, Mark Jeffrey, and Lon Harris 1:02:48 Bieber vs. Carpenter: does Coachella owe you a spectacle? 1:15:20 Jason says Staples should pay the "Staples baddie" $1M/year cc: @jason, Lon Harris, Mark Jeffrey, const, Distributed State, templar, covenant, Macrocosmos, Apex・SN1, IOTA ・ SN9, Ken Jon, BitMind BitMindAI 🎥 Watch the full episode here 👇

This Week in Startups

29,964 次观看 • 3 个月前

The cost to go from idea to first customer used to be $3 million and 12 months. Now you can get there in a weekend. On a TWiST devoted to your questions, Jason and Lon reflect on how getting early-stage companies launched and funded has changed, how to compete with major players like OpenAI and Anthropic, and who Jason dislikes the most in Silicon Valley. 0:00 Inside the TWiST private group chat 3:25 How to react when an investor says your "too early." 6:50 The ultimate seed round funnel 8:48 Jason's new Associate in Training program 10:09 Grasshopper Bank - Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 18:28 How have the metrics for early-stage companies changed? 20:20 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 22:34 TWiST Bounties update 23:43 Competing against frontier labs 30:03 What signals real investor-founder alignment? 30:14 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 36:07 A crash course in Bay Area startup culture 40:15 Automatons-as-a-Service (AaaS) 42:29 Who in Silicon Valley does Jason really not like? 49:59 Museum Etiquette with Lon Harris cc: @jason, Lon Harris, JS, sergedawg, Peridot: Curated matchmaking, Shawn Sully 🎥 Watch the full episode here 👇
57:55

The cost to go from idea to first customer used to be $3 million and 12 months. Now you can get there in a weekend. On a TWiST devoted to your questions, Jason and Lon reflect on how getting early-stage companies launched and funded has changed, how to compete with major players like OpenAI and Anthropic, and who Jason dislikes the most in Silicon Valley. 0:00 Inside the TWiST private group chat 3:25 How to react when an investor says your "too early." 6:50 The ultimate seed round funnel 8:48 Jason's new Associate in Training program 10:09 Grasshopper Bank - Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 18:28 How have the metrics for early-stage companies changed? 20:20 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 22:34 TWiST Bounties update 23:43 Competing against frontier labs 30:03 What signals real investor-founder alignment? 30:14 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 36:07 A crash course in Bay Area startup culture 40:15 Automatons-as-a-Service (AaaS) 42:29 Who in Silicon Valley does Jason really not like? 49:59 Museum Etiquette with Lon Harris cc: @jason, Lon Harris, JS, sergedawg, Peridot: Curated matchmaking, Shawn Sully 🎥 Watch the full episode here 👇

This Week in Startups

45,672 次观看 • 1 个月前

SpaceX just agreed to buy Cursor for $60 billion. Everyone is talking about the product, the models, the valuation. I’m interested in the human side of this AI story. Who built the team behind one of the fastest-growing software companies in history, and how do they think about talent at the frontier of AI? For the first episode of my new podcast, Below the Surface, I sat down with Adam Ward, Cursor 's Head of Talent, to find out. Before Cursor, Adam helped scale Facebook through its IPO, ran global recruiting at Pinterest from 200 to 2000+ people, and built Growth by Design Talent, the advisory firm behind OpenAI, Anthropic, Stripe, Notion, and Figma … until Cursor acquired it last year. We talked about what hiring looks like when the market is moving this fast, how Cursor does it differently, and what it actually takes to build a high-performance team right now. One of my biggest takeaways: the companies that win in AI won’t just have better models. They’ll have better systems for finding, assessing, and enabling exceptional people. Watch the full episode here: Or subscribe wherever you get podcasts: 🎧 🎤
0:53

SpaceX just agreed to buy Cursor for $60 billion. Everyone is talking about the product, the models, the valuation. I’m interested in the human side of this AI story. Who built the team behind one of the fastest-growing software companies in history, and how do they think about talent at the frontier of AI? For the first episode of my new podcast, Below the Surface, I sat down with Adam Ward, Cursor 's Head of Talent, to find out. Before Cursor, Adam helped scale Facebook through its IPO, ran global recruiting at Pinterest from 200 to 2000+ people, and built Growth by Design Talent, the advisory firm behind OpenAI, Anthropic, Stripe, Notion, and Figma … until Cursor acquired it last year. We talked about what hiring looks like when the market is moving this fast, how Cursor does it differently, and what it actually takes to build a high-performance team right now. One of my biggest takeaways: the companies that win in AI won’t just have better models. They’ll have better systems for finding, assessing, and enabling exceptional people. Watch the full episode here: Or subscribe wherever you get podcasts: 🎧 🎤

Joelle Emerson

24,821 次观看 • 21 天前

A Bittensor subnet just outscored Claude and Cursor on the SWE benchmark. They spent less than $1 million to get there. Anthropic spent billions. I sat down with Mark Jeffrey, one of the most connected people in the Bittensor ecosystem, and he broke down everything. Here's what most people don't know about TAO. Bittensor takes Bitcoin's mining concept and makes it programmable. Instead of solving meaningless hash puzzles, miners compete on real AI tasks. Best freelancer wins. Blockchain pays them. No company. No CEO. No permission needed. Bitcoin did this for energy. Bittensor does it for talent. The numbers are wild: • Ridges (Subnet 62) built a Claude/Cursor competitor for under $1M • Miners on Ridges were earning $50K per day at peak • The Bittensor network has 128 subnets, each like its own AI startup • Mark says 20-30 of them could become multi-billion dollar companies • Only 20% of TAO is staked in subnets right now • Stakers are earning up to 80% yield on some subnets Mark has been in crypto since 2013. He was in the Ethereum ICO. He's seen every cycle. His take: Bittensor is the most important thing to happen in crypto since Ethereum. He calls TAO the "third great coin" alongside Bitcoin and ETH. The comparison to early Bitcoin is hard to ignore. TAO just had its first halving in December. Same 21 million supply cap. Same post-halving setup. When Bitcoin went through this phase, it jumped from $250 to $10,000. Mark's conservative target for TAO by end of 2026: $3,000. But the real insight was about demand. More subnets means more TAO gets locked up. Subnet cap going from 128 to 256. Staking will absorb most of the supply. And AI agents need crypto to transact. They can't open bank accounts. Bittensor is building the rails for that. Jensen Huang just talked about Templar, a Bittensor subnet, on stage. This isn't theoretical anymore. People are using this stuff. The products on Bittensor are 10 to 100x better than what we saw in early Ethereum. And we're still early.
0:37

A Bittensor subnet just outscored Claude and Cursor on the SWE benchmark. They spent less than $1 million to get there. Anthropic spent billions. I sat down with Mark Jeffrey, one of the most connected people in the Bittensor ecosystem, and he broke down everything. Here's what most people don't know about TAO. Bittensor takes Bitcoin's mining concept and makes it programmable. Instead of solving meaningless hash puzzles, miners compete on real AI tasks. Best freelancer wins. Blockchain pays them. No company. No CEO. No permission needed. Bitcoin did this for energy. Bittensor does it for talent. The numbers are wild: • Ridges (Subnet 62) built a Claude/Cursor competitor for under $1M • Miners on Ridges were earning $50K per day at peak • The Bittensor network has 128 subnets, each like its own AI startup • Mark says 20-30 of them could become multi-billion dollar companies • Only 20% of TAO is staked in subnets right now • Stakers are earning up to 80% yield on some subnets Mark has been in crypto since 2013. He was in the Ethereum ICO. He's seen every cycle. His take: Bittensor is the most important thing to happen in crypto since Ethereum. He calls TAO the "third great coin" alongside Bitcoin and ETH. The comparison to early Bitcoin is hard to ignore. TAO just had its first halving in December. Same 21 million supply cap. Same post-halving setup. When Bitcoin went through this phase, it jumped from $250 to $10,000. Mark's conservative target for TAO by end of 2026: $3,000. But the real insight was about demand. More subnets means more TAO gets locked up. Subnet cap going from 128 to 256. Staking will absorb most of the supply. And AI agents need crypto to transact. They can't open bank accounts. Bittensor is building the rails for that. Jensen Huang just talked about Templar, a Bittensor subnet, on stage. This isn't theoretical anymore. People are using this stuff. The products on Bittensor are 10 to 100x better than what we saw in early Ethereum. And we're still early.

Jesus Martinez

73,314 次观看 • 3 个月前

Anthropic and OpenAI slammed the this week on secondary transactions of their shares as both AI labs race to list. To help @jason and alex 🏴‍☠️🇺🇸🇺🇦 unpack the market-moving news, investors Jenny Fielding Dave McClure and sam lessin 🏴‍☠️ joined our venture capital panel to make plain which Anthropic investing vehicles are legit, and which may be fake. The group also dug into software moats, large venture funds pressuring smaller firms, the future of LP capital, and the IPO market! 0:00 Guest introductions 1:30 Guest introductions 2:36 Anthropic voids unauthorized SPV trades 9:23 Accredited investor reform & the SEC sophisticated investor test 9:40 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free at 12:25 Naval's USVC closed-end fund as a workaround 17:23 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 18:30 Pro-rata rights battles: when Series A investors push seed investors out 20:18 Grasshopper Bank: Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 29:55 Pilot: Focus on your product, let Pilot handle your bookkeeping. Pilot provides the most reliable accounting, CFO, and tax services for startups and small businesses. Head to and get $1,200 off your first year. 31:05 Storing wealth in stories vs. cash flows 35:01 Cerebras and Fervo Energy IPOs — meaningful liquidity? 38:36 Will SpaceX, Anthropic, OpenAI IPOs redistribute capital or compound it? 46:40 The $15M Series A founder who returned the money because of Claude 50:43 Should founders pivot or return capital when the world changes? 57:25 OpenAI's $6.6B tender and Shruti Gandhi's viral SF cost-of-living tweet 1:01:07 Intercom rebrands to Fin: the AI-first late-stage pivot 🎥 Watch the full episode here 👇
1:25:16

Anthropic and OpenAI slammed the this week on secondary transactions of their shares as both AI labs race to list. To help @jason and alex 🏴‍☠️🇺🇸🇺🇦 unpack the market-moving news, investors Jenny Fielding Dave McClure and sam lessin 🏴‍☠️ joined our venture capital panel to make plain which Anthropic investing vehicles are legit, and which may be fake. The group also dug into software moats, large venture funds pressuring smaller firms, the future of LP capital, and the IPO market! 0:00 Guest introductions 1:30 Guest introductions 2:36 Anthropic voids unauthorized SPV trades 9:23 Accredited investor reform & the SEC sophisticated investor test 9:40 Quo (formerly OpenPhone) - Quo gives you a clean, modern way to handle every customer call, text, and thread all in one place. Try it free at 12:25 Naval's USVC closed-end fund as a workaround 17:23 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 18:30 Pro-rata rights battles: when Series A investors push seed investors out 20:18 Grasshopper Bank: Time is money. Don't waste either. Go to and get an exclusive $500 cash bonus just for opening an account. 29:55 Pilot: Focus on your product, let Pilot handle your bookkeeping. Pilot provides the most reliable accounting, CFO, and tax services for startups and small businesses. Head to and get $1,200 off your first year. 31:05 Storing wealth in stories vs. cash flows 35:01 Cerebras and Fervo Energy IPOs — meaningful liquidity? 38:36 Will SpaceX, Anthropic, OpenAI IPOs redistribute capital or compound it? 46:40 The $15M Series A founder who returned the money because of Claude 50:43 Should founders pivot or return capital when the world changes? 57:25 OpenAI's $6.6B tender and Shruti Gandhi's viral SF cost-of-living tweet 1:01:07 Intercom rebrands to Fin: the AI-first late-stage pivot 🎥 Watch the full episode here 👇

This Week in Startups

19,800 次观看 • 2 个月前

We’re back for Episode 14 of TAO Talk 🚨 calanthia from Masa joins 563 and brody this week to chat about new subnets and AI agents sourcing intelligence from Bittensor! The group chats about: - $TAO -pilling AI/ML chads at NeurIPS Conference feat. const Crucible Labs Macrocosmos Manifold and Yuma - JJ teaming up with Cameron Fairchild to form Laτenτ Holdings, which will validate and help scale subnets - Crucible Labs drops a subnet analysis framework - Celium offering H100s cheaper than any other provider - Tao360 releases inaugural research report for their AI-enabled subnet analysis tool @notYourBananaa - Masa unveils the AI Agent Arena on SN59 /// Timestamps: 00:00 Intro 01:10 Subnet 42 and Agent Arena: Masa’s Subnets 03:00 Real-Time Data Networks for AI 04:20 How Masa is Building AI Agent Arenas Inspired by Gladiators 06:10 Decentralized AI and Bittensor: The Growing Ecosystem 08:15 AI Meets Web3: Masa’s Role in Revolutionizing Data Networks 10:00 The Future of AI Agents: Intelligent Societies and Real-Time Data 12:05 Why Masa Chose Bittensor 14:10 $TAO Incentives and the Future of AI Decentralization 16:25 Bittensor and the Rise of Agent Competition: Masa’s Perspective 18:00 Exploring AI Agent Societies 20:30 Creating Competitive AI Arenas: The Agent Arena Subnet Explained 23:00 Calanthia on the Challenges of Web3 AI Development 25:10 Bringing Web2 Developers into Web3: Lessons from Masa 27:30 The Evolution of AI: From Dumb Agents to Intelligent Societies 30:00 AI Agents as the Future of Interaction in Decentralized AI 34:00 The Agent Arena’s Vision: Competition, Incentives, and Innovation
37:00

We’re back for Episode 14 of TAO Talk 🚨 calanthia from Masa joins 563 and brody this week to chat about new subnets and AI agents sourcing intelligence from Bittensor! The group chats about: - $TAO -pilling AI/ML chads at NeurIPS Conference feat. const Crucible Labs Macrocosmos Manifold and Yuma - JJ teaming up with Cameron Fairchild to form Laτenτ Holdings, which will validate and help scale subnets - Crucible Labs drops a subnet analysis framework - Celium offering H100s cheaper than any other provider - Tao360 releases inaugural research report for their AI-enabled subnet analysis tool @notYourBananaa - Masa unveils the AI Agent Arena on SN59 /// Timestamps: 00:00 Intro 01:10 Subnet 42 and Agent Arena: Masa’s Subnets 03:00 Real-Time Data Networks for AI 04:20 How Masa is Building AI Agent Arenas Inspired by Gladiators 06:10 Decentralized AI and Bittensor: The Growing Ecosystem 08:15 AI Meets Web3: Masa’s Role in Revolutionizing Data Networks 10:00 The Future of AI Agents: Intelligent Societies and Real-Time Data 12:05 Why Masa Chose Bittensor 14:10 $TAO Incentives and the Future of AI Decentralization 16:25 Bittensor and the Rise of Agent Competition: Masa’s Perspective 18:00 Exploring AI Agent Societies 20:30 Creating Competitive AI Arenas: The Agent Arena Subnet Explained 23:00 Calanthia on the Challenges of Web3 AI Development 25:10 Bringing Web2 Developers into Web3: Lessons from Masa 27:30 The Evolution of AI: From Dumb Agents to Intelligent Societies 30:00 AI Agents as the Future of Interaction in Decentralized AI 34:00 The Agent Arena’s Vision: Competition, Incentives, and Innovation

TAO τalk 🥩🦍

24,929 次观看 • 1 年前

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self
1:45:40

The end of coding? *Epic* conversation with Guillermo Rauch of Vercel on vibe coding, MCP, agents and building products in the AI era. (00:00) - Intro: Guillermo's Story (02:08) - What is v0 and Why Did It Take Off So Fast? (04:10) - Building a hit product with < people (07:51) - Cursor, Replit, etc: v0 vs Other AI Coding Tools (10:35) - Everyone can cook - What is Vibe Coding? (17:05) - Is v0 Just Frontend? Moving Toward Full Stack 19:40 - How to Become a Great Vibe Coder (23:35) - A GUI for AI: The Future of Interfaces (29:46) - Developer Love vs Agent Love (33:41) - The Importance of Taste in the AI Era (39:10) - MCP: The Protocol for AI-to-AI Communication (43:11) - Security and the Risks of Agentic Web (45:25) - Are Enterprises Ready for the Agentic Future? (49:42) - Building a Data Flywheel (56:06) - The Vercel AI Cloud: From Pixels to Tokens (1:10:14) - Adapting to a Non-Developer Persona (1:13:47) - Retention, Margins, and the Business of AI (1:16:51) - The Secret Behind Vercel Last Year Growth (1:24:15) - The importance of Online Presence (1:30:49) - Everything, Everywhere, All at Once: Keeping your Sanity as a CEO (1:34:59) - Guillermo's Advice to Younger Self

Matt Turck

86,153 次观看 • 1 年前

This is very true. AI integration is both hard and necessary for companies. And AI-native junior employees can drive this adoption. Earlier this year Aaron Levie explained with martin_casado on the a16z podcast how AI fluency is one of the most powerful skills a new grad can have. The real value comes from knowing how to make AI work inside an organization. Most companies, both large and small, are slow to adopt new technology. They need people who can explain what AI can do, show them how to use it, and help them move faster. If you are fluent in AI, you can be that person. You can walk into a company, spot the areas where AI can save time or create new opportunities, and make it happen. That is a wedge into your first job and a way to stand out from everyone else.
0:39

This is very true. AI integration is both hard and necessary for companies. And AI-native junior employees can drive this adoption. Earlier this year Aaron Levie explained with martin_casado on the a16z podcast how AI fluency is one of the most powerful skills a new grad can have. The real value comes from knowing how to make AI work inside an organization. Most companies, both large and small, are slow to adopt new technology. They need people who can explain what AI can do, show them how to use it, and help them move faster. If you are fluent in AI, you can be that person. You can walk into a company, spot the areas where AI can save time or create new opportunities, and make it happen. That is a wedge into your first job and a way to stand out from everyone else.

a16z

366,027 次观看 • 10 个月前

Naval on how to get a job in 2025: Learn how to use AI Naval on E215: "The fastest way to help somebody get a job right now: the best thing you can do is say, 'Hey, go download the AI tools and just start talking to them. Just start using them in any way.'" "And then you can walk into any employer in almost any field and say, 'Hey, I understand AI.' And they'll hire you on the spot." "AI is a productivity tool. It increases the productivity of a worker. It allows them to do more creative work and less repetitive work. As such, it makes them more valuable." "Yes, there is some retraining involved, but not a lot. These are natural language computers. You can talk to them in plain English, and they talk back to you in plain English." "I think we will see job creation by AI that will be as fast or faster than job destruction." "You saw this even with the internet. Like, YouTube came along. Look at all these YouTube streamers and influencers. That didn't used to be a job." "Go brush up on your AI. Learn a little bit. Watch a few videos. Use the AI." "Tinker with it and then go reapply for that job that rejected you, and watch how they pull you in."
0:50

Naval on how to get a job in 2025: Learn how to use AI Naval on E215: "The fastest way to help somebody get a job right now: the best thing you can do is say, 'Hey, go download the AI tools and just start talking to them. Just start using them in any way.'" "And then you can walk into any employer in almost any field and say, 'Hey, I understand AI.' And they'll hire you on the spot." "AI is a productivity tool. It increases the productivity of a worker. It allows them to do more creative work and less repetitive work. As such, it makes them more valuable." "Yes, there is some retraining involved, but not a lot. These are natural language computers. You can talk to them in plain English, and they talk back to you in plain English." "I think we will see job creation by AI that will be as fast or faster than job destruction." "You saw this even with the internet. Like, YouTube came along. Look at all these YouTube streamers and influencers. That didn't used to be a job." "Go brush up on your AI. Learn a little bit. Watch a few videos. Use the AI." "Tinker with it and then go reapply for that job that rejected you, and watch how they pull you in."

The All-In Podcast

164,027 次观看 • 1 年前

Chamath: “Facebook, Tesla, Google… they almost had an allergic reaction to the traditional software stack. They refused to use it.” Find out why he raised a $135M Series A to redefine development, giving every enterprise the opportunity to build and maintain their own software without the $4T in consultants and middleware that usually comes with it… in the debut episode of TWiST All Star Summer 2026. 0:00 It's TWiST All-Star Summer! 0:44 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 3:21 Chamath's origin story 7:54 Tom Sawyer entrepreneurship 11:29 Shopify - Turn those What If's into sales with the ecommerce platform powering millions of businesses. Sign up for your $1-per-month trial today at 16:25 The $5 trillion software market 21:06 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 25:00 Building "a co-founder for every human" 31:51 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 35:00 How product development lost its way 45:00 Regulated industries are the beachhead 50:00 Raising the $135M Series A 55:00 8090's "System on a Chip" model 1:04:44 What to tell your kids about AI cc: Chamath Palihapitiya, @jason, 8090 🎥 Watch the full episode here 👇
1:12:05

Chamath: “Facebook, Tesla, Google… they almost had an allergic reaction to the traditional software stack. They refused to use it.” Find out why he raised a $135M Series A to redefine development, giving every enterprise the opportunity to build and maintain their own software without the $4T in consultants and middleware that usually comes with it… in the debut episode of TWiST All Star Summer 2026. 0:00 It's TWiST All-Star Summer! 0:44 Plaud: If your work depends on conversations — interviews, meetings, calls — you need a Plaud NotePin. You can check it out at and use code TWIST for 10% off! 3:21 Chamath's origin story 7:54 Tom Sawyer entrepreneurship 11:29 Shopify - Turn those What If's into sales with the ecommerce platform powering millions of businesses. Sign up for your $1-per-month trial today at 16:25 The $5 trillion software market 21:06 LinkedIn Jobs - Hire right, the first time. Post your first job and get $100 off towards your job post at 25:00 Building "a co-founder for every human" 31:51 Northwest Registered Agent - Get more when you start your business with Northwest. In 10 clicks and 10 minutes, you can form your company and walk away with a real business identity — Learn more at 35:00 How product development lost its way 45:00 Regulated industries are the beachhead 50:00 Raising the $135M Series A 55:00 8090's "System on a Chip" model 1:04:44 What to tell your kids about AI cc: Chamath Palihapitiya, @jason, 8090 🎥 Watch the full episode here 👇

This Week in Startups

109,738 次观看 • 15 天前

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.
4:16

This agent relies on a marketplace of 2.8M+ specialized agents to complete a task. This is how I imagine the future of personal agents. Here is how this works: 1. Agentverse is a marketplace of agents 2. Anyone can build and publish an agent there 3. ASI:One is a personal agent with access to the marketplace 4. To solve a task, ASI:One finds the best agent for the job In other words: You have an agent that can solve pretty much *anything* because it knows how to outsource the work to a network of specialized agents. And you don't need to do any setup to get this working. The way ranking agents in the marketplace works is pretty cool: Fetch.ai, the company behind it, created an AgentRank algorithm that works much like Google's PageRank. Every time an agent calls another, it forms a connection. Over time, these connections build into a graph of who relies on whom. An agent that is frequently called by other reputable agents scores higher and surfaces higher in results. The end result here is that your agent will consistently use the best agents in the marketplace to accomplish a goal. You should give this a try: You don't need to pay or even register to try these agents. Thanks to the team for partnering with me on this post.

Santiago

18,677 次观看 • 20 天前

The most overlooked part of the SpaceX IPO thesis is the model and most people are completely missing it (Save this) Everyone has been focused on the Anthropic compute deal and the Colossus revenue because those are numbers you can put in a spreadsheet. Six months ago, xAI was competing reasonably well on model performance but was not clearly on the frontier. Then SpaceX exercised its option to acquire Cursor for $60 billion, the largest startup acquisition in history just days after completing the largest IPO in history at $75 billion. Cursor is a team of 700 to 800 people, was on track to exit 2026 at up to $10 billion in revenue, had millions of professional developers using it daily, and had already built a team with the genuine potential to compete at the frontier, the one thing holding them back was compute. SpaceX just gave them the largest GPU cluster in the world to work with. Grok 4.3, a 1.5 trillion parameter model, is currently training with Cursor's proprietary coding data being injected directly into pre-training, not just fine tuning which is a fundamentally more powerful integration than anything the market is currently modeling. The prior version, Grok 4, was already on the Pareto frontier as of 10 to 12 days ago, the most intelligent 500 billion parameter model in the world, sitting alongside Google Gemini, Anthropic, and OpenAI as one of only four systems at the true frontier. Composer 2.5, the previous Cursor model was Pareto dominant in coding tasks just before the acquisition closed, meaning SpaceX inherited a model that was already best-in-class in the highest-value AI use case in the market. The AWS parallel is the one everyone keeps missing. Bezos built data center capacity for Black Friday, sat on idle infrastructure the rest of the year, and monetized it into what was at the time the most profitable technology business in history and investors hated it in 2009 and 2010 because he was burning free cash flow on capacity that had no obvious revenue yet. SpaceX is in exactly that position, it built Colossus for xAI's own training needs, is monetizing excess capacity to Anthropic at $1.25 billion per month across 220,000 Nvidia GPUs, and has reportedly secured up to 20% of Nvidia's early Vera Rubin allocation, giving it the most powerful and scarcest GPU infrastructure in the world during the critical window when those chips are hardest to get. The $60 billion Cursor acquisition closed at a moment when SpaceX had essentially unlimited compute, a team already at the frontier, and a product with deep enterprise distribution, three things no other model lab had simultaneously when it was at this stage. The market is pricing the compute business conservatively and ignoring the model call option entirely, and coding is the fastest path to AGI, once you are on the Pareto frontier with that compute, revenue scales fast. Anthropic went from negligible revenue to $30 billion annualized in under 18 months and that is the existence proof. Bullish on SpaceXAI and Elon Musk
6:02

The most overlooked part of the SpaceX IPO thesis is the model and most people are completely missing it (Save this) Everyone has been focused on the Anthropic compute deal and the Colossus revenue because those are numbers you can put in a spreadsheet. Six months ago, xAI was competing reasonably well on model performance but was not clearly on the frontier. Then SpaceX exercised its option to acquire Cursor for $60 billion, the largest startup acquisition in history just days after completing the largest IPO in history at $75 billion. Cursor is a team of 700 to 800 people, was on track to exit 2026 at up to $10 billion in revenue, had millions of professional developers using it daily, and had already built a team with the genuine potential to compete at the frontier, the one thing holding them back was compute. SpaceX just gave them the largest GPU cluster in the world to work with. Grok 4.3, a 1.5 trillion parameter model, is currently training with Cursor's proprietary coding data being injected directly into pre-training, not just fine tuning which is a fundamentally more powerful integration than anything the market is currently modeling. The prior version, Grok 4, was already on the Pareto frontier as of 10 to 12 days ago, the most intelligent 500 billion parameter model in the world, sitting alongside Google Gemini, Anthropic, and OpenAI as one of only four systems at the true frontier. Composer 2.5, the previous Cursor model was Pareto dominant in coding tasks just before the acquisition closed, meaning SpaceX inherited a model that was already best-in-class in the highest-value AI use case in the market. The AWS parallel is the one everyone keeps missing. Bezos built data center capacity for Black Friday, sat on idle infrastructure the rest of the year, and monetized it into what was at the time the most profitable technology business in history and investors hated it in 2009 and 2010 because he was burning free cash flow on capacity that had no obvious revenue yet. SpaceX is in exactly that position, it built Colossus for xAI's own training needs, is monetizing excess capacity to Anthropic at $1.25 billion per month across 220,000 Nvidia GPUs, and has reportedly secured up to 20% of Nvidia's early Vera Rubin allocation, giving it the most powerful and scarcest GPU infrastructure in the world during the critical window when those chips are hardest to get. The $60 billion Cursor acquisition closed at a moment when SpaceX had essentially unlimited compute, a team already at the frontier, and a product with deep enterprise distribution, three things no other model lab had simultaneously when it was at this stage. The market is pricing the compute business conservatively and ignoring the model call option entirely, and coding is the fastest path to AGI, once you are on the Pareto frontier with that compute, revenue scales fast. Anthropic went from negligible revenue to $30 billion annualized in under 18 months and that is the existence proof. Bullish on SpaceXAI and Elon Musk

Milk Road AI

69,393 次观看 • 28 天前

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team
1:13:20

I asked Dan Martell to walk me through every level of making money with AI. He gave me the most simple, practical advice I've ever heard on this subject. Level 1 - Making $0 - $100k Level 2 - Making $1m - $10m Level 3 - Building a $10m++ enterprise. 0:00 Only 5% of the World Has Ever Paid for AI 0:46 The Easiest Thing to Sell With AI Right Now 1:56 The Marcus and Sophie Framework 4:24 Theory of Constraints (Right Problem to Solve) 5:33 What Is the Number One Business Constraint 7:13 How to Leave Your Job and Go All In 8:27 Business Is Simple Find a Problem and Solve It 9:08 Stop Getting Ready to Get Ready 9:33 The Sarah Story One Text and $10K 9:53 Pull Up Your Phone and Message Your Contacts 11:05 Dan's Son Gets His First Client at $800/Month 12:41 Best Employee vs. Best Employer 13:59 What Other Services Can You Sell With AI 14:44 Sales Is Not Talking It's Asking 17:01 What to Do When You Hate Your Business 18:40 Pain and Pleasure Are the Only Two Motivators 19:13 They Haven't Made It a Must Yet 20:29 Make It a Must Not a Nice to Have 21:06 The Jen Story and the Gasping Moment 22:17 How to Find Your First 10 to 15 Clients 28:38 The Personal Brand Play 33:06 Vision Is What AI Cannot Do 34:55 Hard for Computers Easy for Humans 36:13 Level 2 Making Your First Million With AI 37:18 The Replacement Ladder Framework 37:39 Admin First Then Delivery Then Marketing 39:09 Why Marketing Is the Biggest AI Category 39:32 Why You Should Keep Sales for Yourself 40:00 Level 5 Leadership and AI Agents 41:41 What a Fully AI Systems Business Looks Like 43:13 The Gym Owner With Three Locations 46:16 Shutting Down the Company for Two Days 46:37 Teaching the Whole Team to Code in Claude 49:28 Wayne the 62 Year Old Who Made $12K a Month 52:38 I Only Share What Actually Works 53:21 Whisper Flow and Talking to Your AI 56:41 Claude Chat Claude Coworker and Claude Code 57:57 The Claude Browser Extension 58:49 Claude Code Is Not Just for Developers 1:00:06 How to Migrate Your AI Memory Across Tools 1:01:08 Level 3 $1M to $10M and the Brand Play 1:02:05 Nobody Buys AI They Buy Trust 1:03:25 Brand Is Association and Association Is Trust 1:05:12 A Million Followers Is $10M in Activated Revenue 1:07:03 How to Keep AI From Becoming Slop 1:07:42 Human in the Loop 1:08:16 The 10 80 10 Rule and Why AI Is Now the 80 1:10:01 The Team FIRED Themselves 1:11:45 Dan's Free AI Curriculum for Your Team

Grant

165,182 次观看 • 20 天前

DROPS E38: Vanta Trading - The Best Traders Won't Be Human Arrash is the founder and CEO of Vanta Trading, a decentralized prop trading platform built on Bittensor. He spent years as a quant trader building his own strategies before deciding the entire funded-account industry needed to be rebuilt from the ground up. We talk about: - Why most "funded accounts" trade on money that doesn't exist - Why your payout was never real - How prop firms intentionally change rules and spreads before you cash out - Why the best traders of the future won't be human And much more… Timestamps: 0:00 Introduction 1:48 Founder of Vanta 3:08 Explaining Vanta to an Uber Driver 3:26 Unfair vs Fair Funding 6:37 How do they make money? 8:33 How a Legit Prop Firm Makes Money 9:43 Founder's Journey Into Entrepreneurship 10:42 Discovering Crypto & Blockchain 13:03 From LinkedIn Engineer to Quant Trader 15:22 Trading Strategies 16:13 How Trading Is Changing? 18:39 Why TradFi Should Fear Hyperliquid 19:16 Building on BitTensor 21:43 Explaining BitTensor Simply 22:03 How BitTensor Creates Value 23:17 BitTensor's Structure 24:36 BitTensor as Crypto AI 25:35 Is the BitTensor Hype Justified? 27:09 Revenue & Profitability in BitTensor 29:17 Role of TAO 29:51 Advantages & Limitations of BitTensor ecosystem 31:56 What Is Vanta? 32:26 Why No One Fixed Prop Trading Before 33:12 Is the Entire Industry a Scam? 34:17 How Prop Firms Really Make Money 35:35 How Vanta Is Different 38:33 Copy Trading Explained 39:30 Vanta's Business Model 40:28 Dark Reality Behind Funded Accounts 43:48 Long-Term Vision for Vanta 44:50 What Happens If Too Many Traders Win? 46:25 Future Belongs to AI Traders 47:59 Vanta's Endgame 49:14 Conclusion
50:55

DROPS E38: Vanta Trading - The Best Traders Won't Be Human Arrash is the founder and CEO of Vanta Trading, a decentralized prop trading platform built on Bittensor. He spent years as a quant trader building his own strategies before deciding the entire funded-account industry needed to be rebuilt from the ground up. We talk about: - Why most "funded accounts" trade on money that doesn't exist - Why your payout was never real - How prop firms intentionally change rules and spreads before you cash out - Why the best traders of the future won't be human And much more… Timestamps: 0:00 Introduction 1:48 Founder of Vanta 3:08 Explaining Vanta to an Uber Driver 3:26 Unfair vs Fair Funding 6:37 How do they make money? 8:33 How a Legit Prop Firm Makes Money 9:43 Founder's Journey Into Entrepreneurship 10:42 Discovering Crypto & Blockchain 13:03 From LinkedIn Engineer to Quant Trader 15:22 Trading Strategies 16:13 How Trading Is Changing? 18:39 Why TradFi Should Fear Hyperliquid 19:16 Building on BitTensor 21:43 Explaining BitTensor Simply 22:03 How BitTensor Creates Value 23:17 BitTensor's Structure 24:36 BitTensor as Crypto AI 25:35 Is the BitTensor Hype Justified? 27:09 Revenue & Profitability in BitTensor 29:17 Role of TAO 29:51 Advantages & Limitations of BitTensor ecosystem 31:56 What Is Vanta? 32:26 Why No One Fixed Prop Trading Before 33:12 Is the Entire Industry a Scam? 34:17 How Prop Firms Really Make Money 35:35 How Vanta Is Different 38:33 Copy Trading Explained 39:30 Vanta's Business Model 40:28 Dark Reality Behind Funded Accounts 43:48 Long-Term Vision for Vanta 44:50 What Happens If Too Many Traders Win? 46:25 Future Belongs to AI Traders 47:59 Vanta's Endgame 49:14 Conclusion

MR SHIFT 🦁

37,896 次观看 • 29 天前

🚀 Exciting News $SHELL the Future of AI Agents and $TAO with the TTS Subnet on Bittensor! 🚀 MyShell extends the impact of Bittensor's incentive mechanism to its over 1 million registered users and 50,000 creators, greatly expanding Bittensor's and $TAO's influence. MyShell and Bittensor are right at the heart this massive shake-up with $SHELL and $TAO. They’re all about making AI not just smart but also something everyone can get into, thanks to the power of decentralized networks. And at the core? AI agents. These aren't your average digital assistants; they're about to change how we interact with tech on a whole new level. MyShell's Big Idea with $SHELL So, MyShell’s got this big plan to make AI something anyone can dive into. They're launching this TTS Subnet thing on Bittensor's network, which is all about making machines talk in more human-like ways, and they're using $SHELL tokens to fuel this vision. Their goal? To push past old-school AI limits and create with AI as easy as pie, all while keeping it open-source and community-powered. Bittensor Does Its Magic with $TAO On the other side, you’ve got Bittensor doing wonders with $TAO, building this massive network where anyone, anywhere, can chip in on AI research and development. This partnership with MyShell? It’s a game-changer, breaking down walls in AI development and letting folks from all over the world have a go at making AI smarter. $SHELL + $TAO = AI Revolution Putting $SHELL and $TAO together is where the magic really happens. MyShell and Bittensor aren’t just teaming up for the tech; they’re here to transform our digital world, making AI agents a big part of our online lives. Imagine AI that doesn’t just follow orders but helps, creates, and learns with you. That’s the future they’re building. Hop on Board the AI Revolution This isn’t just tech talk; it’s a call to action. MyShell and Bittensor are inviting anyone with a spark for AI to jump in and help shape this new world. Whether you’re a coder, a creator, or just curious, there’s a spot for you to dive in and make a difference. Want to get started? Check out MyShell on GitHub: Follow the latest buzz on X: MyShell.AI Take a deeper dive at Website: This is more than just building AI; it’s about crafting a future where AI is part of everyone’s life, powered by the community, for the community. Let’s make it happen with $SHELL and $TAO. Share on YouTube:
4:21

🚀 Exciting News $SHELL the Future of AI Agents and $TAO with the TTS Subnet on Bittensor! 🚀 MyShell extends the impact of Bittensor's incentive mechanism to its over 1 million registered users and 50,000 creators, greatly expanding Bittensor's and $TAO's influence. MyShell and Bittensor are right at the heart this massive shake-up with $SHELL and $TAO. They’re all about making AI not just smart but also something everyone can get into, thanks to the power of decentralized networks. And at the core? AI agents. These aren't your average digital assistants; they're about to change how we interact with tech on a whole new level. MyShell's Big Idea with $SHELL So, MyShell’s got this big plan to make AI something anyone can dive into. They're launching this TTS Subnet thing on Bittensor's network, which is all about making machines talk in more human-like ways, and they're using $SHELL tokens to fuel this vision. Their goal? To push past old-school AI limits and create with AI as easy as pie, all while keeping it open-source and community-powered. Bittensor Does Its Magic with $TAO On the other side, you’ve got Bittensor doing wonders with $TAO, building this massive network where anyone, anywhere, can chip in on AI research and development. This partnership with MyShell? It’s a game-changer, breaking down walls in AI development and letting folks from all over the world have a go at making AI smarter. $SHELL + $TAO = AI Revolution Putting $SHELL and $TAO together is where the magic really happens. MyShell and Bittensor aren’t just teaming up for the tech; they’re here to transform our digital world, making AI agents a big part of our online lives. Imagine AI that doesn’t just follow orders but helps, creates, and learns with you. That’s the future they’re building. Hop on Board the AI Revolution This isn’t just tech talk; it’s a call to action. MyShell and Bittensor are inviting anyone with a spark for AI to jump in and help shape this new world. Whether you’re a coder, a creator, or just curious, there’s a spot for you to dive in and make a difference. Want to get started? Check out MyShell on GitHub: Follow the latest buzz on X: MyShell.AI Take a deeper dive at Website: This is more than just building AI; it’s about crafting a future where AI is part of everyone’s life, powered by the community, for the community. Let’s make it happen with $SHELL and $TAO. Share on YouTube:

Andy ττ

10,823 次观看 • 2 年前

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on The Startup Ideas Podcast (SIP) 🧃 was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch
58:55

AI AGENTS 101 (58 minute free masterclass) send this to anyone who wants to understand ai agents, claude skills, md files, how to get the most out of AI etc in plain english: 1. chat vs agents - chat models answer questions in a back and forth while agents take a goal, figure out the steps, and deliver a result 2. agents don’t stop after one response. they keep running until the task is actually finishedno babysitting required 3. everything runs on a loop. they gather context, decide what to do, take an action, then repeat until done 4. the loop is the system. they look at files, tools, and the internet. decide the next step. execute and then feed that back into the next step. over and over until completion 5. the model is just one piece. gpt, claude, gemini are the reasoning layer. the key is model + loop + tools + context 6. mcp is how agents use tools. it connects things like browser, code, apis, and your internal software. once connected, the agent decides when to use them to get the job done 7. context beats prompt all day. you don't need to write perfect prompts. load your agent with context about your business, style, and goals and then simple instructions work 8. claude.md or agents.md is the onboarding doc it tells the agent who it is, how to behave, what it knows, and what tools it can use. this gets loaded every time before it starts 9. memory.md is how it improves. agents don’t remember by default. this file stores preferences, corrections, and patterns you tell the agent to update it, and it gets better over time 10. skills + harnesses make it usable. skills are reusable tasks like writing, research, analysis the harness is the environment like claude code or openclaw that runs everything. basiclaly, different interfaces, same system underneath this episode with remy on The Startup Ideas Podcast (SIP) 🧃 was one of the clearest ways of understanding a lot of the core concepts of ai agents could be the best beginners course for ai agents 58 mins. all free. no advertisers. i just want to see you build cool stuff. im rooting for you. send to a friend watch

GREG ISENBERG

375,365 次观看 • 3 个月前

Elon Musk just made one if the biggest moves in taking over the programming industry “SpaceX just bought Cursor for $60 billion. Do you realize how big this is? SpaceX went public — the biggest IPO in history. $75 billion raised, almost a $2 trillion valuation and the first thing to do with that money? Buy the most popular AI coding tool on the planet. Here's why that changes everything. Elon now owns 3 layers: the compute, Colossus data centers, the models, Grok through xAI, and now the tool that developers actually use every day. It's the full stack. And here's what makes Cursor different from Claude Code or Codex. Cursor is model agnostic. You can run Claude in it, GPT, Gemini, whatever model you want. It's not locked to any one company, and now it has SpaceX's resources behind it. Cursor said they were bottlenecked by compute. Well, that bottleneck has just been removed. $4 billion in annual revenue, over half the Fortune 500 already uses it, and now it's backed by a $2 trillion company. OpenAI has Codex, Anthropic has Claude Code, and now Elon has Cursor.” Let me break this down in simple terms Elon Musk now controls more of the full AI picture: - Massive computers, power (data centers like Colossus) - Smart AI models (Grok from xAI) - The actual tool millions of developers use every day (Cursor) For every day users this means Faster and smarter apps and websites in the future. More developers using powerful AI tools means new apps, games, websites, and features get built quicker and cheaper. This means better video games, smoother streaming, smarter phone apps and better programs For Developers they can describe what they want in plain English (“make a feature that does X”) and the AI handles more of the heavy lifting
2:13

Elon Musk just made one if the biggest moves in taking over the programming industry “SpaceX just bought Cursor for $60 billion. Do you realize how big this is? SpaceX went public — the biggest IPO in history. $75 billion raised, almost a $2 trillion valuation and the first thing to do with that money? Buy the most popular AI coding tool on the planet. Here's why that changes everything. Elon now owns 3 layers: the compute, Colossus data centers, the models, Grok through xAI, and now the tool that developers actually use every day. It's the full stack. And here's what makes Cursor different from Claude Code or Codex. Cursor is model agnostic. You can run Claude in it, GPT, Gemini, whatever model you want. It's not locked to any one company, and now it has SpaceX's resources behind it. Cursor said they were bottlenecked by compute. Well, that bottleneck has just been removed. $4 billion in annual revenue, over half the Fortune 500 already uses it, and now it's backed by a $2 trillion company. OpenAI has Codex, Anthropic has Claude Code, and now Elon has Cursor.” Let me break this down in simple terms Elon Musk now controls more of the full AI picture: - Massive computers, power (data centers like Colossus) - Smart AI models (Grok from xAI) - The actual tool millions of developers use every day (Cursor) For every day users this means Faster and smarter apps and websites in the future. More developers using powerful AI tools means new apps, games, websites, and features get built quicker and cheaper. This means better video games, smoother streaming, smarter phone apps and better programs For Developers they can describe what they want in plain English (“make a feature that does X”) and the AI handles more of the heavy lifting

Wall Street Apes

212,830 次观看 • 25 天前