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My thesis on $PATH in 60 seconds: Everyone thinks agentic AI kills UiPath. I think it's the opposite. AI agents are powerful but useless without orchestration. Someone has to deploy them, govern them, and connect them to the 50 different systems inside a Fortune 500 company. That's what UiPath...

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Jason Luongo

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Mark Zuckerberg: Most businesses will not own frontier AI in the way Meta or OpenAI does. But many will end up with something that feels like their own AI: a customized operational layer that reflects how that company actually works. He says, "OpenAI, Google, they're building an AI. But I think we're gonna have a lot of different AI systems, just like we're gonna have, we have a lot of different apps. I think in the future, every business, just like I have a website and a phone number and an email address, a social media account, is also going to have an AI that can interact with their customers to help them sell things, help them give support." --- What he is really describing that a company’s “own AI” will usually not be a frontier model trained from scratch, but a layer built on top of shared models, shaped by its products, policies, customer history, and way of working. Support, sales, and basic operations can be handled through a system that knows the business well enough to answer, route, recommend, and escalate without feeling generic. --- From 'Cleo Abram' YT channel (link in comment)
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Mark Zuckerberg: Most businesses will not own frontier AI in the way Meta or OpenAI does. But many will end up with something that feels like their own AI: a customized operational layer that reflects how that company actually works. He says, "OpenAI, Google, they're building an AI. But I think we're gonna have a lot of different AI systems, just like we're gonna have, we have a lot of different apps. I think in the future, every business, just like I have a website and a phone number and an email address, a social media account, is also going to have an AI that can interact with their customers to help them sell things, help them give support." --- What he is really describing that a company’s “own AI” will usually not be a frontier model trained from scratch, but a layer built on top of shared models, shaped by its products, policies, customer history, and way of working. Support, sales, and basic operations can be handled through a system that knows the business well enough to answer, route, recommend, and escalate without feeling generic. --- From 'Cleo Abram' YT channel (link in comment)

Rohan Paul

429,685 Aufrufe • vor 3 Monaten

Sequoia's Pat Grady says systems of record software companies are relatively safe from AI disruption, but that systems of engagement companies built on top of them are in trouble: "The first wave of the on-prem to cloud transition was transitioning systems of record — the Workdays, Salesforces, and Servicenows of the world." "The second layer on top of that was the systems of engagement. The systems of record might own the core database, but then there are a bunch of different workflow applications that reside on top." "I think what we're going to see with the wave of AI software is a third layer on top of those." "It's the layer that does the work. It's the agents getting deployed. They may or may not need those workflows beneath them, but certainly need access to everything that's sitting in that system of record." "As a result, I think those systems of record companies are relatively safe. They may not catch a lot of net new workloads, because those might go to the AI native companies. But I think overall they're pretty safe." "I think some of those workflow-based companies in the middle are in trouble, because they're neither the systems of record nor the agentic capability that's getting deployed. So they'll have to figure out how to become like that agent harness, so to speak, for whatever job needs to be done."
1:38

Sequoia's Pat Grady says systems of record software companies are relatively safe from AI disruption, but that systems of engagement companies built on top of them are in trouble: "The first wave of the on-prem to cloud transition was transitioning systems of record — the Workdays, Salesforces, and Servicenows of the world." "The second layer on top of that was the systems of engagement. The systems of record might own the core database, but then there are a bunch of different workflow applications that reside on top." "I think what we're going to see with the wave of AI software is a third layer on top of those." "It's the layer that does the work. It's the agents getting deployed. They may or may not need those workflows beneath them, but certainly need access to everything that's sitting in that system of record." "As a result, I think those systems of record companies are relatively safe. They may not catch a lot of net new workloads, because those might go to the AI native companies. But I think overall they're pretty safe." "I think some of those workflow-based companies in the middle are in trouble, because they're neither the systems of record nor the agentic capability that's getting deployed. So they'll have to figure out how to become like that agent harness, so to speak, for whatever job needs to be done."

TBPN

95,022 Aufrufe • vor 3 Monaten

$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.
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$NVDA CEO Jensen Huang said demand has gone parabolic because agentic AI has arrived, AI can now do productive work and tokens are becoming profitable. If tokens are profitable then model builders have a reason to produce more of them which means more inference, more compute and more demand across networking, memory, CPUs, power and data centers. The near-term stock reaction is about expectations but long-term story is still that the AI factory buildout is running through Nvidia which is why I think it has a real path to becoming the world’s first $10T company.

Shay Boloor

261,700 Aufrufe • vor 1 Monat

What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch
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What does it actually mean to be AI native? There was no clear guide on the internet for how to become AI native so we built the definitive one (60 min masterclass): 1. An AI native org has 3 layers: people for strategy and taste, agents for execution, and a shared context layer that makes the entire company readable to agents. 2. AI eats the middle of your work. You used to spend 80% of your day on execution. Now agents do that. Your job is the bookends: deciding what to do and judging whether it's good enough. 3. Everyone is a manager now. Your output is the output of your agents. If your agents produce garbage, that's on you. You set them up wrong. 4. Using ChatGPT doesn't make you AI native. That's like having a website and calling yourself a tech company lol. 5. No AI native org without AI native people. Most companies skip straight to the tools. That's why it fails. If your people don't understand how to manage agents, the tech doesn't matter. 6. Making your company "readable" to agents is the real work. Every process, every decision, every piece of knowledge needs to exist in a format an agent can consume. Most companies are nowhere close. 7. Speed without signal is just expensive chaos. You need the system to move fast AND know if you're moving in the right direction. 8. The skill chain is how agents get good at your specific workflows. Skills build on skills. The more you invest in them, the more your company compounds. 9. The moat is the system. People managing agents, agents reading from rich context, the whole thing getting smarter every week. That compounds. Your competitor can copy your tools. They can't copy your system. Full episode with Theo Tabah from LCA on The Startup Ideas Podcast (SIP) 🧃. This is the stuff we normally keep internal but all the sauce is yours. Theo Tabah is the brains behind advising the world's biggest companies on AI and building AI products. Your fav CEO's first call for figuring out AI. You are in for a treat Become AI native in under 60 minutes Watch

GREG ISENBERG

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Sequoia’s Carl Eschenbach says the SaaSpocalypse narrative is "completely overblown," and that it's not a zero-sum game between incumbent SaaS and AI-native newcomers: "Incumbency is incredibly powerful in enterprise. Incumbency is even more powerful when a company like Workday has a 98% gross retention rate across 11,000 customers, with 65%+ of them being Fortune 500 companies. They’re not going anywhere." "That all being said, [with] the pace and rate of change that can happen outside of the big incumbents and big SaaS companies...[new companies] have an opportunity to start completely fresh, and start from scratch." "They get to leverage all the technologies and all the models that are out there, and build agents and agentic solutions faster than anyone else. And they're going to be able to go into the enterprise and provide value on day one, either on their own, or on top of and through some of these SaaS companies."
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Sequoia’s Carl Eschenbach says the SaaSpocalypse narrative is "completely overblown," and that it's not a zero-sum game between incumbent SaaS and AI-native newcomers: "Incumbency is incredibly powerful in enterprise. Incumbency is even more powerful when a company like Workday has a 98% gross retention rate across 11,000 customers, with 65%+ of them being Fortune 500 companies. They’re not going anywhere." "That all being said, [with] the pace and rate of change that can happen outside of the big incumbents and big SaaS companies...[new companies] have an opportunity to start completely fresh, and start from scratch." "They get to leverage all the technologies and all the models that are out there, and build agents and agentic solutions faster than anyone else. And they're going to be able to go into the enterprise and provide value on day one, either on their own, or on top of and through some of these SaaS companies."

TBPN

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0:20

Why do we need a purpose-built blockchain for agentic payments? Because AI agents are now smart enough to operate autonomously, and they need their own rails to transact with each other. Watch the video to see what that looks like in action: A real agent, built on Kite AI, helped our CTO Scott Shi - e/acc order lunch from Uber Eats fully on its own. It explored menu options, made the choice, and completed the payment - all without human intervention. This marks the beginning of agentic commerce and the future of agentic payments - and Kite AI is building this.

KITE AI

88,081 Aufrufe • vor 9 Monaten

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.
1:52

Here we go again 🚀! Excited to announce that we're building A1Zap (YC W25) with Pennie Li and that we're in the Y Combinator W25 batch in San Francisco! What is A1Base? A1Base gives AI Agents a real world identity for work. We do that by rebuilding Twilio and Okta from the ground up, putting AI Agents first. This means developers can make AI-first agentic applications 10x easier with our API's. ⁉️ Why are we doing this? Because there's a huge torrent of new valuable companies possible with AI agents, but to get their AI Agents to users, they have to chain custom apps, chat interfaces, awkward Slack integrations, browser bots, and wrestle with Twilio’s legacy API (which is built for marketing). We solve this by providing developers with an easy to use API to interface your AI agent with humans/coworkers/users where they are in this case in Whatsapp, Slack, Teams, SMS and more) - with AI Agent features built in. These digital workers are poised to transform how we work and we're the critical infrastructure to help them interact naturally in human workflows. We're not just building another AI tool. We're creating the infrastructure that will enable AI agents to become a natural part of the workforce - handling everything from customer support to sales development to creative work. We're backed by Y Combinator and working with founding teams who share our vision. We believe that in the near future, AI Agents with human coworkers will enable us to pursue more creative and impactful work. Our mission is to help developers build AI Agents that people can partner with and rely on as trusted allies—always with a human-first mindset. If you're thinking about the Agentic future of your company reach out! If you're looking to build your first AI Agentic company - reach out too - we have some amazing open source templates to get you started on the journey. Excited to share more of what we're up to soon 🔜.

Pasha Rayan

53,904 Aufrufe • vor 1 Jahr

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA
1:48

Jensen Huang explains the AI industry as a five layer cake, and why "model only" companies are missing the real map. "AI is not just a model. AI is really a five layer cake to think about it." "From the lowest level, it requires energy because AI is produced, generated in real time, just like you and I right now. We need calories, we need energy." "The next level is chips. This is where Nvidia is and where a lot of the companies in Taiwan are." "The layer above that is infrastructure: land, power, data center, as well as the cloud service software that turns the chips into a cloud service." "The layer above that is where most people think about when they think about AI, which is models. ChatGPT was revolutionary. Claude Code is now incredibly successful. But AI is much more than just human language." Most people are still debating the model layer. Jensen is describing an industrial stack: energy, chips, infrastructure, models, and applications. If you are building in AI, this is the map that matters. The winning product may look like software, but the bottlenecks are calories, land, power, data centers, chips, and distribution. - Jensen Huang (NVIDIA), CEO of Nvidia, on CNA

Karl Mehta

14,946 Aufrufe • vor 10 Tagen

"A generation of management teaching taught us CEOs should trust their people and get out of the way. But I don't think 'trust' and 'getting out of the way' are the same thing." Brian Chesky on how Founder Mode will become even more important with agentic AI: "Great leadership is presence, not absence." "Leadership is presence. You should actually be partnering with people. You should be on the field with them. If you're a calvalry general, you should be on a horse. You should be on the battlefield. You're not overseas just writing blueprints. You gotta be on the field with them, you gotta be leading by example." "Leadership is from the front, not the back." "I think AI is going to create the equivalent of an AI founder mode. Now you gotta be even more hands-on. I don't think in the era of AI, there should be any pure people managers. Because you're so close to the details and data. Everyone has the opportunity to be hands-on, and it's hard to imagine only managing people and not agents."
1:15

"A generation of management teaching taught us CEOs should trust their people and get out of the way. But I don't think 'trust' and 'getting out of the way' are the same thing." Brian Chesky on how Founder Mode will become even more important with agentic AI: "Great leadership is presence, not absence." "Leadership is presence. You should actually be partnering with people. You should be on the field with them. If you're a calvalry general, you should be on a horse. You should be on the battlefield. You're not overseas just writing blueprints. You gotta be on the field with them, you gotta be leading by example." "Leadership is from the front, not the back." "I think AI is going to create the equivalent of an AI founder mode. Now you gotta be even more hands-on. I don't think in the era of AI, there should be any pure people managers. Because you're so close to the details and data. Everyone has the opportunity to be hands-on, and it's hard to imagine only managing people and not agents."

TBPN

16,005 Aufrufe • vor 2 Monaten

The entire AI industry is racing to build the smartest model. Satya Nadella just admitted that is not where the money is. The model is not the product. The harness is. That is the exact line. And it changes what Microsoft is actually competing on. OpenAI, Anthropic, Google, xAI, Meta every frontier lab is pouring hundreds of billions into training compute, chasing the next capability jump. Each betting that raw model intelligence is the moat. Microsoft is doing the opposite. It is building the harness the orchestration layer that sits above the model, connecting it to tools, data, permissions, sub-agents, and enterprise workflows. And it is letting OpenAI, Anthropic, and MAI compete to plug into it. "You need the model. But the model is not the product. The harness is." So do the math on what a harness actually does. A raw model dropped into an enterprise answers questions. That is a chatbot. A harness turns that same model into an agent that reads the SharePoint, edits the ERP entry, pulls the GitHub PR, updates Salesforce, and files the Excel report with the right permissions, the right audit trail, and the right sub-agent for each sub-task. The model provides the intelligence. The harness converts intelligence into work. Now here's where it gets interesting. "Even the best model in the world will feel broken without a great harness. And an okay model with a great harness can feel like magic." If that is true, the enterprise buyer is not buying model quality. The enterprise buyer is buying the harness. Which means model quality becomes a commodity input over time, and harness quality becomes the sustainable moat. Compare that to the strategy the entire frontier lab industry is executing. Everyone else is chasing the numerator raw intelligence. Almost nobody at scale is racing to build the denominator the orchestration layer that determines whether that intelligence can actually be deployed profitably inside a real company. The frontier model race has a 10 to 20 percent chance of producing a single dominant winner. Nadella just told the industry he does not need to be that winner. If OpenAI wins, Microsoft wins. If Anthropic wins, Microsoft wins. If MAI wins, Microsoft wins. If someone Microsoft has never heard of trains a better model in 2027, Microsoft still wins. Because the compute they train on, the harness they get plugged into, the enterprise contracts they get delivered through, and the products they sit inside are all Microsoft. He is not building the best AI model. He is building the layer that the best AI model has to run on to make anyone money. I wonder which position looks more valuable in ten years.
3:19

The entire AI industry is racing to build the smartest model. Satya Nadella just admitted that is not where the money is. The model is not the product. The harness is. That is the exact line. And it changes what Microsoft is actually competing on. OpenAI, Anthropic, Google, xAI, Meta every frontier lab is pouring hundreds of billions into training compute, chasing the next capability jump. Each betting that raw model intelligence is the moat. Microsoft is doing the opposite. It is building the harness the orchestration layer that sits above the model, connecting it to tools, data, permissions, sub-agents, and enterprise workflows. And it is letting OpenAI, Anthropic, and MAI compete to plug into it. "You need the model. But the model is not the product. The harness is." So do the math on what a harness actually does. A raw model dropped into an enterprise answers questions. That is a chatbot. A harness turns that same model into an agent that reads the SharePoint, edits the ERP entry, pulls the GitHub PR, updates Salesforce, and files the Excel report with the right permissions, the right audit trail, and the right sub-agent for each sub-task. The model provides the intelligence. The harness converts intelligence into work. Now here's where it gets interesting. "Even the best model in the world will feel broken without a great harness. And an okay model with a great harness can feel like magic." If that is true, the enterprise buyer is not buying model quality. The enterprise buyer is buying the harness. Which means model quality becomes a commodity input over time, and harness quality becomes the sustainable moat. Compare that to the strategy the entire frontier lab industry is executing. Everyone else is chasing the numerator raw intelligence. Almost nobody at scale is racing to build the denominator the orchestration layer that determines whether that intelligence can actually be deployed profitably inside a real company. The frontier model race has a 10 to 20 percent chance of producing a single dominant winner. Nadella just told the industry he does not need to be that winner. If OpenAI wins, Microsoft wins. If Anthropic wins, Microsoft wins. If MAI wins, Microsoft wins. If someone Microsoft has never heard of trains a better model in 2027, Microsoft still wins. Because the compute they train on, the harness they get plugged into, the enterprise contracts they get delivered through, and the products they sit inside are all Microsoft. He is not building the best AI model. He is building the layer that the best AI model has to run on to make anyone money. I wonder which position looks more valuable in ten years.

Vikram M

21,463 Aufrufe • vor 11 Tagen

The AI market rally in 2026 has one anchor. It's private. Brad Gerstner Gerstner holds Anthropic equity with non-public financial access. His claim: without Anthropic's 2026 revenue delivery, the market would be down 10-15% right now. Not NVIDIA. Not OpenAI launches. Anthropic's profit path. High gross margins and a path to positive FCF in Q2 2026 triggered the market's ascent out of a deep correction. One private company validated that AI revenue was real and profitable. The anchor is private. The companies depending on it are public. If Anthropic's next revenue update disappoints, every AI-correlated position loses its primary justification. Source: TBPN (TBPN) -
0:51

The AI market rally in 2026 has one anchor. It's private. Brad Gerstner Gerstner holds Anthropic equity with non-public financial access. His claim: without Anthropic's 2026 revenue delivery, the market would be down 10-15% right now. Not NVIDIA. Not OpenAI launches. Anthropic's profit path. High gross margins and a path to positive FCF in Q2 2026 triggered the market's ascent out of a deep correction. One private company validated that AI revenue was real and profitable. The anchor is private. The companies depending on it are public. If Anthropic's next revenue update disappoints, every AI-correlated position loses its primary justification. Source: TBPN (TBPN) -

Podcast Alpha

28,361 Aufrufe • vor 1 Monat

America has the edge in the world’s most powerful AI models, no question. But China is playing a different game: efficiency, scale, and global deployment. Kyle Chan from Brookings China explains: "Does winning mean developing the world's most powerful AI models? If yes, then the us has the decisive lead. American ai models are widely recognized as the best in the world on virtually every metric you can think of, from math and reasoning to coding and AI agents, American private companies continue to set the pace at the technological frontier supported by deep capital markets, a dynamic innovation ecosystem, and the best talent from around the world. China's AI models are improving quickly but continue to lag behind. Chinese AI companies face real constraints on compute due to our export controls and their own limited capital resources, so instead they're prioritizing other goals. They're focused on efficiency, building models that are cheaper to train and run. They're focused on adoption using an open source strategy to win users around the world, and they're focused on integration with other platforms and services. On sheer performance, I would expect the gap between our models and theirs to persist or even widen over time. But model performance is not everything."
1:10

America has the edge in the world’s most powerful AI models, no question. But China is playing a different game: efficiency, scale, and global deployment. Kyle Chan from Brookings China explains: "Does winning mean developing the world's most powerful AI models? If yes, then the us has the decisive lead. American ai models are widely recognized as the best in the world on virtually every metric you can think of, from math and reasoning to coding and AI agents, American private companies continue to set the pace at the technological frontier supported by deep capital markets, a dynamic innovation ecosystem, and the best talent from around the world. China's AI models are improving quickly but continue to lag behind. Chinese AI companies face real constraints on compute due to our export controls and their own limited capital resources, so instead they're prioritizing other goals. They're focused on efficiency, building models that are cheaper to train and run. They're focused on adoption using an open source strategy to win users around the world, and they're focused on integration with other platforms and services. On sheer performance, I would expect the gap between our models and theirs to persist or even widen over time. But model performance is not everything."

Select Committee on China

60,135 Aufrufe • vor 3 Monaten

Ilya Sutskever, the co-founder of OpenAI, on the one AI risk that grows with every jump in capability. "There are concerns around if an AGI ever becomes very, very powerful, which is possible. Maybe it will want to go rogue, being that it is an agent." "We are also doing a lot of research on addressing the technological side of things, so that the AI will never want to go rogue. And this is something which I am working on as well." The work he is describing has a name: the assurance layer. Proving a powerful, agentic system will not go rogue before you deploy it, not after. That layer does not build itself. It gets built by the labs, regulators, and insurers who agree on how to test and verify these systems. P.S. That is the entire agenda of the AI Assurance and Governance Summit. Frontier labs, regulated industries, insurers, and investors in one room at Stanford on October 1. Reserve a seat: - Ilya Sutskever (Ilya Sutskever), co-founder of OpenAI, at TED
1:05

Ilya Sutskever, the co-founder of OpenAI, on the one AI risk that grows with every jump in capability. "There are concerns around if an AGI ever becomes very, very powerful, which is possible. Maybe it will want to go rogue, being that it is an agent." "We are also doing a lot of research on addressing the technological side of things, so that the AI will never want to go rogue. And this is something which I am working on as well." The work he is describing has a name: the assurance layer. Proving a powerful, agentic system will not go rogue before you deploy it, not after. That layer does not build itself. It gets built by the labs, regulators, and insurers who agree on how to test and verify these systems. P.S. That is the entire agenda of the AI Assurance and Governance Summit. Frontier labs, regulated industries, insurers, and investors in one room at Stanford on October 1. Reserve a seat: - Ilya Sutskever (Ilya Sutskever), co-founder of OpenAI, at TED

Karl Mehta

22,453 Aufrufe • vor 11 Tagen

$PLTR this analyst gets it: - Palantir is the AI Operating System - Palantir provides the environment and context layer (ontology + security model) for enterprises to deploy AI models and agents - This is a structural growth opportunity - The ROI for enterprises to deploy AI and use Palantir’s service will become increasingly attractive - (Regarding living up to today’s PE) Revenue growth and margin is unique. “You’ve never seen that type of growth and margin previously for any other companies. Enterprise is a huge market. AI is really shifting from consumer to the enterprise world. Enterprise offers a larger TAM. This is early stage for enterprise to use AI. The TAM could be trillion $$ level…. The path towards that will never be easy, it will be uneven. If you have that long term view, you will still be long term bullish on the company.” - Enterprise opportunities across the world will totally change the business of Palantir in the coming decades I don’t think he’s bullish enough on government based on what we see coming from Gokarp and DV, but at least he acknowledges the importance of the government sector to the company.
3:37

$PLTR this analyst gets it: - Palantir is the AI Operating System - Palantir provides the environment and context layer (ontology + security model) for enterprises to deploy AI models and agents - This is a structural growth opportunity - The ROI for enterprises to deploy AI and use Palantir’s service will become increasingly attractive - (Regarding living up to today’s PE) Revenue growth and margin is unique. “You’ve never seen that type of growth and margin previously for any other companies. Enterprise is a huge market. AI is really shifting from consumer to the enterprise world. Enterprise offers a larger TAM. This is early stage for enterprise to use AI. The TAM could be trillion $$ level…. The path towards that will never be easy, it will be uneven. If you have that long term view, you will still be long term bullish on the company.” - Enterprise opportunities across the world will totally change the business of Palantir in the coming decades I don’t think he’s bullish enough on government based on what we see coming from Gokarp and DV, but at least he acknowledges the importance of the government sector to the company.

Jack Prescott

112,551 Aufrufe • vor 10 Monaten

The future of AI Agents needs #ICP AI agents are starting to act on our behalf: - making deals - sending messages - handling sensitive data But there is no trust layer telling you who or what you're actually dealing with ❌ zCloak Network is building exactly that: the trust, identity and privacy infrastructure for the AI-native economy, and they built it on top of Internet Computer Protocol In this podcast I sit down with Xiao Zhang (0xFrancis), founder of to break down what they're building, why they chose ICP over every other blockchain, and what the world looks like when AI agents can finally be trusted.
36:32

The future of AI Agents needs #ICP AI agents are starting to act on our behalf: - making deals - sending messages - handling sensitive data But there is no trust layer telling you who or what you're actually dealing with ❌ zCloak Network is building exactly that: the trust, identity and privacy infrastructure for the AI-native economy, and they built it on top of Internet Computer Protocol In this podcast I sit down with Xiao Zhang (0xFrancis), founder of to break down what they're building, why they chose ICP over every other blockchain, and what the world looks like when AI agents can finally be trusted.

Alex (BCP)

20,791 Aufrufe • vor 2 Monaten

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.
1:54

This is the biggest irony in tech history. Microsoft beat revenue estimates. Stock plunged 11%, wiped out $400 BILLION in market cap. Salesforce reported growth. Stock fell 5.6%. ServiceNow beat earnings. Stock crashed 11%. SAP beat projections. Stock dropped 16%. Entire software sector entered bear market territory. Down 22% from peak. These are the companies everyone said would WIN from AI. They spent billions BUYING AI companies. ServiceNow: $7.75 billion for Armis. Salesforce: $8 billion for Informatica. They launched AI products. Built AI workflows. Hired AI teams. And the market said: You're all dead. Because investors just realized something nobody wanted to admit: AI doesn't make software companies stronger. AI makes software companies OBSOLETE. Morgan Stanley: "In an environment of heightened investor skepticism, stable growth falls short of shifting the narrative." Good earnings aren't enough anymore. The market is pricing in a world where AI replaces the software these companies sell. ServiceNow CEO tried defending on the earnings call: "AI needs workflow orchestration. ServiceNow is the gateway to this shift." Market response: 11% crash. Because here's what he didn't say: If AI can write code, automate workflows, and generate apps at a fraction of the cost, why would anyone pay $50,000 per year for enterprise software licenses? The per-seat pricing model that made SaaS companies rich is getting murdered by AI efficiency. One AI agent replaces 10 seats. One prompt replaces months of custom development. One LLM call replaces entire software categories. Klarna already proved it. CEO said they pulled Salesforce out of their stack. Built everything themselves using AI. And that's just the beginning. The software apocalypse hit hardest on companies that INVESTED IN AI: Atlassian: down 12.6% Intuit: down 7.8% HubSpot: down 11.5% Zscaler: down 6.3% Meanwhile, the companies ENABLING AI made money: Nvidia: up Semiconductor stocks: surging Memory firms: rallying The divide is brutal. Hardware companies print cash. Software companies get destroyed. Because in an AI-first world, you need GPUs to build the models. But you don't need software subscriptions when the AI builds the software for you. Jim Cramer called it the "P/E multiple compression crisis." Translation: Investors don't care about earnings anymore. They care about whether your business model survives the next 5 years. And right now software business models look doomed. They're literally stuck: If they DON'T invest in AI, they fall behind. If they DO invest in AI, they cannibalize their own products. It's a death spiral with no exit. ServiceNow spent $12 BILLION on acquisitions in 2025 alone. Trying to buy their way into relevance. And yesterday the market cooked them. The craziest thing to me tho... Most software companies beat earnings. Revenue was solid. Growth was fine. But it didn't matter. Because the market stopped pricing software on what it earns TODAY. It's pricing software on what it's worth in a world where AI does the job for free. And in that world these companies are worth nothing. This is the biggest sector repricing since 2008. $500 billion in market value gone in ONE DAY. And it's not stopping. Because every company watching this is thinking the same thing: "If I can replace ServiceNow with 3 AI agents and save $10 million per year, why wouldn't I?" The answer used to be: "Because you need enterprise-grade reliability." But now? AI agents are getting reliable. Fast. Software companies just realized they're competing with open-source models that cost $0.02 per 1,000 tokens. You can't win a pricing war against free. The companies that spent BILLIONS preparing for AI are getting killed BY AI. What an irony.

Ricardo

1,813,369 Aufrufe • vor 5 Monaten

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)
0:59

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 Aufrufe • vor 1 Monat

We’ve integrated a first-of-its-kind, privacy-native MCP connector layer to the Dot platform, making DotChat agentic by default. Live at → Even in private AI, the standard product is: pick a model, send a prompt, maybe enable web search and get an answer. This is simply not enough. MCPs changed what AI agents can do, but they are trapped inside: Claude Code, Cursor, local agents, API tooling and enterprise setups. Through Dot, users can now connect any MCP directly into their AI workspace, while maintaining Dot’s privacy boundary around the entire workflow. This means Dot users won’t just ask models questions, they’ll be able to connect tools, inspect onchain state, check portfolios, prepare transactions, and interact with Base from inside the chat flow. And yes, we’re starting with the big one. The Base MCP. This is a major step toward Dot’s agentic vision: powerful AI agents that can interact with the world without compromising user privacy. Check our demo below, where we integrate the updated Base MCP into Dot, and utilize it to buy $10 in $DOT, all whilst retaining full anonymity ↓
1:09

We’ve integrated a first-of-its-kind, privacy-native MCP connector layer to the Dot platform, making DotChat agentic by default. Live at → Even in private AI, the standard product is: pick a model, send a prompt, maybe enable web search and get an answer. This is simply not enough. MCPs changed what AI agents can do, but they are trapped inside: Claude Code, Cursor, local agents, API tooling and enterprise setups. Through Dot, users can now connect any MCP directly into their AI workspace, while maintaining Dot’s privacy boundary around the entire workflow. This means Dot users won’t just ask models questions, they’ll be able to connect tools, inspect onchain state, check portfolios, prepare transactions, and interact with Base from inside the chat flow. And yes, we’re starting with the big one. The Base MCP. This is a major step toward Dot’s agentic vision: powerful AI agents that can interact with the world without compromising user privacy. Check our demo below, where we integrate the updated Base MCP into Dot, and utilize it to buy $10 in $DOT, all whilst retaining full anonymity ↓

Dot

10,268 Aufrufe • vor 21 Tagen

Everyone is hyping Paperclip as the OpenClaw🦞 killer. I spent a day building an entire AI company on it. Here's my honest take. In this video you'll see: • How Paperclip spins up an org chart, CEO, and sub agents in under 5 minutes • The exact prompt I used to bootstrap a content agency from scratch • Where it actually beats Open Claw (and where it falls flat) • Why I think it's the iPod of agent orchestration, not the iPhone • The 12 page architecture doc I built alongside it Full video is live on YouTube. Comment "Paperclip" and I'll DM you the link.
0:44

Everyone is hyping Paperclip as the OpenClaw🦞 killer. I spent a day building an entire AI company on it. Here's my honest take. In this video you'll see: • How Paperclip spins up an org chart, CEO, and sub agents in under 5 minutes • The exact prompt I used to bootstrap a content agency from scratch • Where it actually beats Open Claw (and where it falls flat) • Why I think it's the iPod of agent orchestration, not the iPhone • The 12 page architecture doc I built alongside it Full video is live on YouTube. Comment "Paperclip" and I'll DM you the link.

Jacob Klug

23,481 Aufrufe • vor 3 Monaten

In a matter of months or years, AI agents will be some of the best (if not *the* best) venture investors in the world. That's why we're excited to give a sneak peak of ADIN -- AI-powered venture capital. ADIN is a network of AI agents that are able to: * evaluate deals, performing superhuman diligence in a matter of minutes * predict the value of a company (with reasonably accuracy, without knowing the value beforehand) * democratically vote on whether to invest in a project * recommend an investment amount based on the DAO/fund's thesis, deployment schedule, size, stage focus, and risk appetite With ADIN, we’re aiming to push both DAOs and venture into an agentic future.
0:54

In a matter of months or years, AI agents will be some of the best (if not *the* best) venture investors in the world. That's why we're excited to give a sneak peak of ADIN -- AI-powered venture capital. ADIN is a network of AI agents that are able to: * evaluate deals, performing superhuman diligence in a matter of minutes * predict the value of a company (with reasonably accuracy, without knowing the value beforehand) * democratically vote on whether to invest in a project * recommend an investment amount based on the DAO/fund's thesis, deployment schedule, size, stage focus, and risk appetite With ADIN, we’re aiming to push both DAOs and venture into an agentic future.

Aaron Wright

29,543 Aufrufe • vor 1 Jahr