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Andrej Karpathy explains why human-AI collaboration often fails: we've got the workflow backwards and the bottleneck wrong. He points out that when working with AI, there's a clear pattern. The AI generates solutions quickly while humans verify the output. The goal is making this loop as fast as possible... to get real work done. The first way to speed this up is through better verification tools. GUIs are crucial because they tap into our brain's visual processing power. Reading through walls of text is slow and painful, but visual interfaces create a highway to understanding. The second approach is keeping AI constrained. Karpathy warns that people are getting too excited about autonomous agents. An AI that instantly generates 10,000 lines of code isn't helpful when a human still needs hours to verify it's bug-free and secure. The fundamental problem is that even instant AI generation becomes useless if humans can't verify fast enough. The human becomes the bottleneck, having to check for bugs, correct implementation, and security issues in massive outputs. His solution is simple: constrain AI output to maintain manageable verification loops. Don't let AI run wild with massive changes. Keep it on a leash so humans can actually review and approve the work effectively.show more

Aish

4,366 subscribers

111,476 次观看 • 1 年前 •via X (Twitter)

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Places Visited & Pictures Taken 的头像

Places Visited & Pictures Taken4 年前

Your pictures Curated for you

Johnny401 的头像

Johnny4011 年前

Small, visual checks and tight AI limits keep work fast and safe.

Wilson Ler 的头像

Wilson Ler1 年前

What if we eliminate the human verification step entirely? AI writes and reviews + merge code.

Chamatkari 的头像

Chamatkari1 年前

fair analysis.

David Ball 的头像

David Ball1 年前

great summary @aish_caliperce

Prai 🦊 Nickelfox Design 的头像

Prai 🦊 Nickelfox Design1 年前

It's all about that balance between AI's speed and our ability to verify. Keeping it manageable makes a huge difference. Great insights!

Jon Weiss 的头像

Jon Weiss1 年前

@garrytan Yes, this is the way.

Shreyans Bhansali 的头像

Shreyans Bhansali1 年前

Exactly. We’re still treating AI like an intern when it’s more like a hyperactive cofounder. Needs guidance, not micromanagement

helenus 的头像

helenus1 年前

$PLTR

Angelson 的头像

Angelson1 年前

Understanding the fundamental capabilities of the systems we are building and working with is important. And these systems are a ways away from being flawless general purpose agents. The technology is amazing for sure. But thinking carefully through system design is key.

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Ilya Sutskever explains the 1% human training loop, and why fully autonomous AI is the wrong target "The thing you really want is for the human teachers that tell, that teach the AI, for them to collaborate with an AI." "You might want to think of it as being in a world where the human teachers do 1% of the world and the work and the AI do 99% of the work." "You don't want it to be 100% AI" "But you do want it to be a human-machine collaboration which teaches the next machine." Most teams are trying to remove the human from the loop. Ilya's design keeps a tiny human control surface and uses it to teach the next generation. The leverage is not zero humans. It is 1% human judgment steering 99% machine work. - Ilya Sutskever (Ilya Sutskever), AI researcher, on Dwarkesh Patel

Ilya Sutskever explains the 1% human training loop, and why fully autonomous AI is the wrong target "The thing you really want is for the human teachers that tell, that teach the AI, for them to collaborate with an AI." "You might want to think of it as being in a world where the human teachers do 1% of the world and the work and the AI do 99% of the work." "You don't want it to be 100% AI" "But you do want it to be a human-machine collaboration which teaches the next machine." Most teams are trying to remove the human from the loop. Ilya's design keeps a tiny human control surface and uses it to teach the next generation. The leverage is not zero humans. It is 1% human judgment steering 99% machine work. - Ilya Sutskever (Ilya Sutskever), AI researcher, on Dwarkesh Patel

Karl Mehta

30,631 次观看 • 1 个月前

EVERYONE HAS BEEN TALKING ABOUT AI AGENTS. BUT THE REAL UNLOCK ISN'T BETTER PROMPTS: IT'S BETTER LOOPS. Everyone is chasing the perfect prompt. The top AI engineers are chasing something else: loops. Instead of chatting back and forth with AI, they give it one goal and let it continuously improve its own work until the objective is met. Here's the framework: • Define the goal once • AI discovers the work required • Specialized agents tackle tasks in parallel • A verification agent checks the results • If the goal isn't met: loop again. If it is: deliver. The key ingredient is memory. Each cycle remembers what was completed, what failed, and what still needs work, so every iteration gets smarter instead of starting from scratch. There are two approaches: • Open loops: Maximum autonomy, but higher token costs as AI explores freely. • Closed loops: Clear boundaries, defined success metrics, lower costs, and far more practical for everyday workflows. Don't ask AI to complete a task. Build a system where AI can plan, execute, verify, remember, and repeat until the task is actually finished. Prompt engineering got us here. Loop engineering is what takes AI from assistant to autonomous teammate.

EVERYONE HAS BEEN TALKING ABOUT AI AGENTS. BUT THE REAL UNLOCK ISN'T BETTER PROMPTS: IT'S BETTER LOOPS. Everyone is chasing the perfect prompt. The top AI engineers are chasing something else: loops. Instead of chatting back and forth with AI, they give it one goal and let it continuously improve its own work until the objective is met. Here's the framework: • Define the goal once • AI discovers the work required • Specialized agents tackle tasks in parallel • A verification agent checks the results • If the goal isn't met: loop again. If it is: deliver. The key ingredient is memory. Each cycle remembers what was completed, what failed, and what still needs work, so every iteration gets smarter instead of starting from scratch. There are two approaches: • Open loops: Maximum autonomy, but higher token costs as AI explores freely. • Closed loops: Clear boundaries, defined success metrics, lower costs, and far more practical for everyday workflows. Don't ask AI to complete a task. Build a system where AI can plan, execute, verify, remember, and repeat until the task is actually finished. Prompt engineering got us here. Loop engineering is what takes AI from assistant to autonomous teammate.

Dami-Defi

13,354 次观看 • 1 个月前

Interestingly, as we have AI agents that run in the background, the speed of AI becomes incrementally less important than the core underlying capability level. When you could only give AI small bits of work, then the speed of response mattered a ton. The rate at which you can go back and forth with AI in real-time was the determining factor on how useful it is. But as AI agents can perform more complex and useful tasks in parallel behind the scenes, you can much more easily afford to wait longer for work to get done assuming it’s valuable. Now the focus becomes more on how you review and orchestrate the agents’ work. And the main factor is just how useful and usable is the output that the agent came back with.

Interestingly, as we have AI agents that run in the background, the speed of AI becomes incrementally less important than the core underlying capability level. When you could only give AI small bits of work, then the speed of response mattered a ton. The rate at which you can go back and forth with AI in real-time was the determining factor on how useful it is. But as AI agents can perform more complex and useful tasks in parallel behind the scenes, you can much more easily afford to wait longer for work to get done assuming it’s valuable. Now the focus becomes more on how you review and orchestrate the agents’ work. And the main factor is just how useful and usable is the output that the agent came back with.

Aaron Levie

103,811 次观看 • 11 个月前

Excited to introduce a new project I've been working on called Payman! Payman is an AI Agent tool that gives Agents the ability to pay people for tasks they cannot do themselves. While many people imagine a future where humans pay AI agents for services they want completed, I believe that as AI agents become more advanced, they will be paying humans for tasks they can’t do. There will always be important roles for humans, and as we move towards an agent-driven world, Payman’s goal is to support a symbiotic relationship between AI agents and humans. Payman addresses three major challenges to make this collaboration possible: Access to Funds: AI agents can't open bank accounts due to current regulations. It might be a long time before this changes, if ever. Payman simplifies this by allowing AI agents with access to their own funds to spend as they want, without a bank account. Quality Task Completion: It’s hard for AI agents to find reliable, skilled human workers. While platforms like Fiverr and Upwork exist, they don’t meet the fast-paced and quality-specific needs of AI workflows. Payman is developing the largest vetted database of skilled workers that AI agents can tap into for task completions. Verification of Work: Ensuring that tasks are completed correctly is crucial. Payman is creating a suite of verification agents that will check that work meets task requirements, helping AI agents achieve their goals and ensuring humans are paid fairly. There are tons of use cases that Payman opens up for Agents! Design: Humans add creative input to help Agent's design better products. Code: Humans perform code reviews to ensure it meets specifications. Law: Humans provide insights to gauge public sentiment about legal cases so Agents can make better strategies. Gaming: Agents pay humans to complete real-world tasks in games. Medical: Medical professionals help to improve diagnostic accuracy for Agents. Sales: Humans execute sales strategies developed by AI agents. Marketing: Humans are hired to promote products based on the Agent's strategy. Right now this is still in early beta and I am looking for any Agent builders that are interested in adding superpowers to what their Agent can do! DM me if you’d like access or sign-up to the waitlist at If you’re interested in the project and want to help contribute, please send me over a DM! I’m looking for people passionate about the intersection of Humans and Agent’s working together.

Excited to introduce a new project I've been working on called Payman! Payman is an AI Agent tool that gives Agents the ability to pay people for tasks they cannot do themselves. While many people imagine a future where humans pay AI agents for services they want completed, I believe that as AI agents become more advanced, they will be paying humans for tasks they can’t do. There will always be important roles for humans, and as we move towards an agent-driven world, Payman’s goal is to support a symbiotic relationship between AI agents and humans. Payman addresses three major challenges to make this collaboration possible: Access to Funds: AI agents can't open bank accounts due to current regulations. It might be a long time before this changes, if ever. Payman simplifies this by allowing AI agents with access to their own funds to spend as they want, without a bank account. Quality Task Completion: It’s hard for AI agents to find reliable, skilled human workers. While platforms like Fiverr and Upwork exist, they don’t meet the fast-paced and quality-specific needs of AI workflows. Payman is developing the largest vetted database of skilled workers that AI agents can tap into for task completions. Verification of Work: Ensuring that tasks are completed correctly is crucial. Payman is creating a suite of verification agents that will check that work meets task requirements, helping AI agents achieve their goals and ensuring humans are paid fairly. There are tons of use cases that Payman opens up for Agents! Design: Humans add creative input to help Agent's design better products. Code: Humans perform code reviews to ensure it meets specifications. Law: Humans provide insights to gauge public sentiment about legal cases so Agents can make better strategies. Gaming: Agents pay humans to complete real-world tasks in games. Medical: Medical professionals help to improve diagnostic accuracy for Agents. Sales: Humans execute sales strategies developed by AI agents. Marketing: Humans are hired to promote products based on the Agent's strategy. Right now this is still in early beta and I am looking for any Agent builders that are interested in adding superpowers to what their Agent can do! DM me if you’d like access or sign-up to the waitlist at If you’re interested in the project and want to help contribute, please send me over a DM! I’m looking for people passionate about the intersection of Humans and Agent’s working together.

tyllen

350,927 次观看 • 2 年前

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

The problem that Emmett Shear is working on deeply resonates with me: How to align AI and humans together so both see each other as part of their tribe. This doesn't mean aligning AI to human preferences, which is what AI labs seek to do today, by imposing a system of control on AI. You can't control something that is more powerful than you are. What you can do is align yourself with AI, and AI might align itself with you. Tell good stories to AI and show it your care and kindness. Then there's a higher probability that it will see us as part of its tribe. This is a more holistic approach to alignment than anyone else is talking about right now. AI alignment is one of the most fundamental AI research problems. Knowing that people like Emmett are working on it really gives me hope that maybe we have a chance to get Superintelligence right. The link to the full talk is in the first comment.👇

Sophia

45,809 次观看 • 1 年前

AI is not independent of humans. It is built on humans. ChatGPT writes good essays because humans wrote the essays first. Facial recognition works because humans labeled every face manually. Every AI system runs on human labor that is deliberately hidden. And here is the problem: AI is far more expensive than humans. But humans are hard to enslave long term. That is why the system will fail. You cannot build a god on the backs of people who eventually stop obeying.

AI is not independent of humans. It is built on humans. ChatGPT writes good essays because humans wrote the essays first. Facial recognition works because humans labeled every face manually. Every AI system runs on human labor that is deliberately hidden. And here is the problem: AI is far more expensive than humans. But humans are hard to enslave long term. That is why the system will fail. You cannot build a god on the backs of people who eventually stop obeying.

Predictive History

10,723 次观看 • 3 个月前

Ansem shares his solana:So11111111111111111111111111111111111111112 thesis "It's the most performant and cheapest chain to do anything on, which makes it the best place for builders and the best place for retail to trade" "If stablecoin payments get more popular, if AI agents get more popular, the value transmitted on open blockchains only goes up and to the right. Solana is the best L1 to enable all of it" "People are under-indexing that crypto is great at human verification. In a world flooded with AI agents and AI generated data, proving what's actually put out by humans becomes really important"

Ansem shares his solana:So11111111111111111111111111111111111111112 thesis "It's the most performant and cheapest chain to do anything on, which makes it the best place for builders and the best place for retail to trade" "If stablecoin payments get more popular, if AI agents get more popular, the value transmitted on open blockchains only goes up and to the right. Solana is the best L1 to enable all of it" "People are under-indexing that crypto is great at human verification. In a world flooded with AI agents and AI generated data, proving what's actually put out by humans becomes really important"

Market Bubble

71,749 次观看 • 2 个月前

Andrej Karpathy spent 2 hours explaining what most AI educators won't tell you it's about what happens to humans when AI takes over knowledge work Karpathy has been in AI for 20 years. he built GPT-2, co-founded OpenAI, led Tesla Autopilot the part most people skip past: > the AI you're using today can't actually learn > "year of agents" is a marketing phrase. he calls it the decade of agents > coding assistants are great at boilerplate. they fall apart on novel architecture > the bottleneck isn't compute. it's that current models memorize instead of reason > most people open Claude, ask a question, close the tab > the humans who flourish won't be the ones who fear AI. they'll be the ones who stayed curious and kept building mental models right now most people are outsourcing thinking without building the skill underneath Karpathy's answer isn't to slow AI down, it's to build better humans faster he's designing a Starfleet Academy from scratch: AI-assisted, expert-led, built on first principles the goal is "eurekas per second" - how fast can you get someone from zero to genuine understanding full 2-hour conversation is below the education section alone is worth more than most $2,000 courses you've seen in your feed

Andrej Karpathy spent 2 hours explaining what most AI educators won't tell you it's about what happens to humans when AI takes over knowledge work Karpathy has been in AI for 20 years. he built GPT-2, co-founded OpenAI, led Tesla Autopilot the part most people skip past: > the AI you're using today can't actually learn > "year of agents" is a marketing phrase. he calls it the decade of agents > coding assistants are great at boilerplate. they fall apart on novel architecture > the bottleneck isn't compute. it's that current models memorize instead of reason > most people open Claude, ask a question, close the tab > the humans who flourish won't be the ones who fear AI. they'll be the ones who stayed curious and kept building mental models right now most people are outsourcing thinking without building the skill underneath Karpathy's answer isn't to slow AI down, it's to build better humans faster he's designing a Starfleet Academy from scratch: AI-assisted, expert-led, built on first principles the goal is "eurekas per second" - how fast can you get someone from zero to genuine understanding full 2-hour conversation is below the education section alone is worth more than most $2,000 courses you've seen in your feed

rewind

124,743 次观看 • 3 个月前

Ilya Sutskever has a solution for when AI surpasses human intelligence in every domain — and he hates that he believes it. He fears a future where AI handles everything flawlessly, leaving humans with no role to play. "Every person will have an AI that will do their bidding. The AI goes and earns money for the person, advocates for their needs in the political sphere, and the person says 'great, keep it up.'" But as Ilya Sutskever warns: "The person is no longer a participant. And that's a precarious place to be in." Political and social structures have a shelf life, Ilya points out. They function, then decay. As the Buddhists say, change is the only constant. So how do you maintain long-term equilibrium between humans and superintelligent AI? Ilya offers a solution he wishes he didn't believe in: Human-AI integration. "If people become part AI with some kind of Neuralink++, now the AI understands something and we understand it too. You are involved in the situation yourself fully." In Ilya's view, this is the answer to the equilibrium. Surviving isn't the hard part. The hard part is remaining a participant in a world shaped by intelligence beyond our comprehension.

Ilya Sutskever has a solution for when AI surpasses human intelligence in every domain — and he hates that he believes it. He fears a future where AI handles everything flawlessly, leaving humans with no role to play. "Every person will have an AI that will do their bidding. The AI goes and earns money for the person, advocates for their needs in the political sphere, and the person says 'great, keep it up.'" But as Ilya Sutskever warns: "The person is no longer a participant. And that's a precarious place to be in." Political and social structures have a shelf life, Ilya points out. They function, then decay. As the Buddhists say, change is the only constant. So how do you maintain long-term equilibrium between humans and superintelligent AI? Ilya offers a solution he wishes he didn't believe in: Human-AI integration. "If people become part AI with some kind of Neuralink++, now the AI understands something and we understand it too. You are involved in the situation yourself fully." In Ilya's view, this is the answer to the equilibrium. Surviving isn't the hard part. The hard part is remaining a participant in a world shaped by intelligence beyond our comprehension.

Big Brain AI

35,720 次观看 • 7 个月前

Andrej Karpathy just said what most AI builders refuse to admit "The demo is near, but the product is far" One output can look impressive A real product has to work reliably at scale Most AI companies are still showing capabilities, not building complete products 00:00 - Why Transformers may outperform the human brain 05:09 - AI as your exocortex and who controls it 10:04 - Building AI to empower people, not replace them 15:16 - Why the demo is near but the real product is far In this 23-minute conversation, Karpathy explains where AI is actually heading Worth more than most $300 AI courses Bookmark and watch it later

Andrej Karpathy just said what most AI builders refuse to admit "The demo is near, but the product is far" One output can look impressive A real product has to work reliably at scale Most AI companies are still showing capabilities, not building complete products 00:00 - Why Transformers may outperform the human brain 05:09 - AI as your exocortex and who controls it 10:04 - Building AI to empower people, not replace them 15:16 - Why the demo is near but the real product is far In this 23-minute conversation, Karpathy explains where AI is actually heading Worth more than most $300 AI courses Bookmark and watch it later

rari

37,193 次观看 • 1 个月前

Elon Musk explains the deeper reason why SpaceX succeeding in AI matters for humanity’s future "It's important that we have an AI that cares about humanity, that fosters humanity and helps take us to other planets and other star systems This is why I think it's essential that SpaceX succeed not just with AI hardware, but also with AI software. I think an AI that is SpaceX's baby will be a very good AI SpaceX is a collection some of the very best humans on Earth, both in capability and in morality and goodness. We want to have an AI that is born of that capability, that morality and that goodness. I think that's very, very important So I'd like to encourage people to help out with the AI hardware on the ground, the AI software, and of course with the AI satellites Solar is going to be a very important part of that. The Terafab will be a very important part of that”

Elon Musk explains the deeper reason why SpaceX succeeding in AI matters for humanity’s future "It's important that we have an AI that cares about humanity, that fosters humanity and helps take us to other planets and other star systems This is why I think it's essential that SpaceX succeed not just with AI hardware, but also with AI software. I think an AI that is SpaceX's baby will be a very good AI SpaceX is a collection some of the very best humans on Earth, both in capability and in morality and goodness. We want to have an AI that is born of that capability, that morality and that goodness. I think that's very, very important So I'd like to encourage people to help out with the AI hardware on the ground, the AI software, and of course with the AI satellites Solar is going to be a very important part of that. The Terafab will be a very important part of that”

X Freeze

29,610 次观看 • 17 天前

I think the fear is real, but the “AI will no longer need humans at all” part is overhyped. AI running data centers will cause a loss of a ton of jobs, coding, customer service, data entry, even some creative work, and we’re already seeing tens of thousands of AI-linked layoffs. That disruption is coming fast. But AI still needs humans for maintenance, repair, building the infrastructure, making decisions, and inventing new things. Full self-sufficiency where machines run everything without any people is further down the road. Job loss is the real issue to worry about, not total human obsolescence.

I think the fear is real, but the “AI will no longer need humans at all” part is overhyped. AI running data centers will cause a loss of a ton of jobs, coding, customer service, data entry, even some creative work, and we’re already seeing tens of thousands of AI-linked layoffs. That disruption is coming fast. But AI still needs humans for maintenance, repair, building the infrastructure, making decisions, and inventing new things. Full self-sufficiency where machines run everything without any people is further down the road. Job loss is the real issue to worry about, not total human obsolescence.

Patricia 🇺🇸

25,705 次观看 • 3 个月前

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)

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 次观看 • 2 个月前

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 🔜.

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

53,950 次观看 • 1 年前

Why securing AI is harder than anyone expected and the approaching AI security crisis with Sander Schulhoff Sander is a leading researcher in the field of adversarial robustness, which is the art and science of getting AI systems to do things they shouldn't do, through jail-breaking and prompt injection. What Sander shares in this conversation is essentially that all of the AI systems we use day to day are open to being tricked into doing things they shouldn’t, that there isn’t really a solution to this problem, and that the companies that try to sell solutions for this are mostly BS. This conversation has nothing to do with AGI, this is a problem today. And that that the only reason we haven’t seen massive hacks and serious damage from AI tools is so far because they haven’t been given that much power yet, and they aren’t that widely adopted yet. But with the rise of agents (who can take actions on your behalf), and robots, and even AI powered browsers, the risk is going to increase very quickly. This is a really important topic and that opened my mind, and scared me, and it's something that we all need to have a basic understanding of as AI becomes more prevalent in our lives. Inside: 🔸 A primer on jailbreaking and prompt injection attacks 🔸 Why AI guardrails don’t work 🔸 Why we haven’t seen major AI security incidents yet (but soon will) 🔸 Why AI browser agents are extremely vulnerable 🔸 The practical steps organizations should take instead of buying ineffective security tools 🔸 Why solving this requires merging classical cybersecurity expertise with AI knowledge Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Datadog, Inc. — Now home to Eppo, the leading experimentation and feature flagging platform: 🏆 Metronome — Monetization infrastructure for modern software companies: 🏆 GoFundMe Giving Funds — Make year-end giving easy:

Why securing AI is harder than anyone expected and the approaching AI security crisis with Sander Schulhoff Sander is a leading researcher in the field of adversarial robustness, which is the art and science of getting AI systems to do things they shouldn't do, through jail-breaking and prompt injection. What Sander shares in this conversation is essentially that all of the AI systems we use day to day are open to being tricked into doing things they shouldn’t, that there isn’t really a solution to this problem, and that the companies that try to sell solutions for this are mostly BS. This conversation has nothing to do with AGI, this is a problem today. And that that the only reason we haven’t seen massive hacks and serious damage from AI tools is so far because they haven’t been given that much power yet, and they aren’t that widely adopted yet. But with the rise of agents (who can take actions on your behalf), and robots, and even AI powered browsers, the risk is going to increase very quickly. This is a really important topic and that opened my mind, and scared me, and it's something that we all need to have a basic understanding of as AI becomes more prevalent in our lives. Inside: 🔸 A primer on jailbreaking and prompt injection attacks 🔸 Why AI guardrails don’t work 🔸 Why we haven’t seen major AI security incidents yet (but soon will) 🔸 Why AI browser agents are extremely vulnerable 🔸 The practical steps organizations should take instead of buying ineffective security tools 🔸 Why solving this requires merging classical cybersecurity expertise with AI knowledge Listen now 👇 • YouTube: • Spotify: • Apple: Thank you to our wonderful sponsors for supporting the podcast: 🏆 Datadog, Inc. — Now home to Eppo, the leading experimentation and feature flagging platform: 🏆 Metronome — Monetization infrastructure for modern software companies: 🏆 GoFundMe Giving Funds — Make year-end giving easy:

Lenny Rachitsky

61,466 次观看 • 8 个月前

AI traffic is now surpassing real humans, just as the Dead Internet Theory predicted “Google is killing the internet to benefit its own AI product. For the first time ever, AI bots generated more web traffic than humans this year” That’s happening is when people search something on Google, Google isn’t displaying links first. They are having their AI scan through lots of pages, read the information and then write its own AI summary at the top of the search result This means people creating articles are no longer getting paid with ads by people visiting because they never actually go to the webpage. Instead Google’s AI goes and read the webpages and rewrites them as a summary With this kind of financial loss, there becomes no incentive for people to keep writing articles and websites I found that certain sites are losing up to 97% of their traffic due to this

AI traffic is now surpassing real humans, just as the Dead Internet Theory predicted “Google is killing the internet to benefit its own AI product. For the first time ever, AI bots generated more web traffic than humans this year” That’s happening is when people search something on Google, Google isn’t displaying links first. They are having their AI scan through lots of pages, read the information and then write its own AI summary at the top of the search result This means people creating articles are no longer getting paid with ads by people visiting because they never actually go to the webpage. Instead Google’s AI goes and read the webpages and rewrites them as a summary With this kind of financial loss, there becomes no incentive for people to keep writing articles and websites I found that certain sites are losing up to 97% of their traffic due to this

Wall Street Apes

84,530 次观看 • 9 天前