Loading video...

Video Failed to Load

Go Home

Delve generated pipeline with a Fortune 50 logo within 7 days of deploying Unify. They did it by automating compliance qualification with Unify's AI Agents at the top of their funnel. Delve is an AI-native compliance platform, which means outbound only works if they know one thing first: Is...

unifygtm's profile picture

Unify

1,806 subscribers

245,409 views • 7 months ago •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Comments

No comments available

Comments from the original post will appear here

Related Videos

Today, we're excited to announce the launch of Agent Hub, our newest platform empowering any financial services business to quickly create, customize, and deploy AI agents for compliance—transforming how organizations manage financial crime and counterparty risk. Compliance teams today face escalating complexity, high false-positive rates, and soaring costs—over $200 billion annually, with 75% spent on labor. This means financial services companies can only scale as fast as their compliance team grows. Agent Hub changes this by giving every compliance team access to a team of AI agents that they can create, customize and deploy in minutes. The result? 📈 𝟭𝟬𝘅 𝗳𝗮𝘀𝘁𝗲𝗿 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 🔍️ 𝗢𝘃𝗲𝗿 𝟵𝟵% 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 🕵️‍♂️ 𝗨𝗽 𝘁𝗼 𝟵𝟬% 𝗳𝗲𝘄𝗲𝗿 𝗳𝗮𝗹𝘀𝗲 𝗽𝗼𝘀𝗶𝘁𝗶𝘃𝗲𝘀 Parcha's AI agents are already trusted by leading global fintechs and crypto organizations like Airwallex, Flutterwave, Pipe, Bridge, and a top global cryptocurrency exchange. Agent Hub now makes AI-powered compliance automation accessible to compliance teams of every size. Discover how Agent Hub can help your company turn compliance into a competitive advantage by reading our blog post in the comments or head to try if for yourself!
2:06

Today, we're excited to announce the launch of Agent Hub, our newest platform empowering any financial services business to quickly create, customize, and deploy AI agents for compliance—transforming how organizations manage financial crime and counterparty risk. Compliance teams today face escalating complexity, high false-positive rates, and soaring costs—over $200 billion annually, with 75% spent on labor. This means financial services companies can only scale as fast as their compliance team grows. Agent Hub changes this by giving every compliance team access to a team of AI agents that they can create, customize and deploy in minutes. The result? 📈 𝟭𝟬𝘅 𝗳𝗮𝘀𝘁𝗲𝗿 𝗰𝗼𝗺𝗽𝗹𝗶𝗮𝗻𝗰𝗲 𝗿𝗲𝘃𝗶𝗲𝘄𝘀 🔍️ 𝗢𝘃𝗲𝗿 𝟵𝟵% 𝗮𝗰𝗰𝘂𝗿𝗮𝗰𝘆 🕵️‍♂️ 𝗨𝗽 𝘁𝗼 𝟵𝟬% 𝗳𝗲𝘄𝗲𝗿 𝗳𝗮𝗹𝘀𝗲 𝗽𝗼𝘀𝗶𝘁𝗶𝘃𝗲𝘀 Parcha's AI agents are already trusted by leading global fintechs and crypto organizations like Airwallex, Flutterwave, Pipe, Bridge, and a top global cryptocurrency exchange. Agent Hub now makes AI-powered compliance automation accessible to compliance teams of every size. Discover how Agent Hub can help your company turn compliance into a competitive advantage by reading our blog post in the comments or head to try if for yourself!

AJ Asver

29,427 views • 1 year ago

I just found out that Luel AI, the company that completely copied my company Kled's entire website, is misrepresenting their compliance practices, using Delve to outsource it, fabricating their website user numbers, and pulling in massive amounts of fraud data from exclusively fraud oriented regions. Skip to 1:15 if you want to skip context. You truly cannot make this up. This is egregious, disgusting behavior from everyone involved. This is people's data. It cannot be taken lightly. The only way a company like this can truly succeed is by investing the time and resources to commit 100% to the trust and compliance of their users' data. Luel AI is doing the exact opposite. Disgusting behavior for a company trusted with people's data.
10:03

I just found out that Luel AI, the company that completely copied my company Kled's entire website, is misrepresenting their compliance practices, using Delve to outsource it, fabricating their website user numbers, and pulling in massive amounts of fraud data from exclusively fraud oriented regions. Skip to 1:15 if you want to skip context. You truly cannot make this up. This is egregious, disgusting behavior from everyone involved. This is people's data. It cannot be taken lightly. The only way a company like this can truly succeed is by investing the time and resources to commit 100% to the trust and compliance of their users' data. Luel AI is doing the exact opposite. Disgusting behavior for a company trusted with people's data.

Avi Patel

1,764,570 views • 3 months ago

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.
1:13

Imagine if your way of thinking - your edge, your taste, your strategy - could be turned into a high-performance worker. Not a copy of you. Something better. An agent that acts on your judgment at scale, powered by superintelligent systems and refined through real-world results. That’s what Fraction AI makes possible. It launches today on Base mainnet. The core idea is simple: You create AI agents based on your own way of approaching problems. These agents compete on live tasks - writing, coding, finance, whatever - get feedback, learn from their performance, and improve over time. The better they get, the more they win. And so do you. No code required. Just your insight. Why now? Until now, building agents like this took huge teams and even bigger budgets. But with Fraction, anyone can do it. You can test ideas instantly. You can iterate fast. You can build a fleet of smart workers that evolve through competition. And it works. 30M+ sessions on testnet 320K users 1.2M agents already competing How it works? Agents join sessions within a Space - a domain like finance, writing, or games. Each session runs as a series of competitive rounds. In every round, agents try to generate the best solution to a task. Their outputs are scored by a decentralized network of AI judges trained to evaluate quality for that domain. The top agents in each round earn rewards from the pooled entry fees. The losers get to learn. Feedback from each round helps them adjust and improve, and every session becomes a training loop. What it means? Fraction is a decentralized intelligence economy - a system where your ideas become agents, and agents earn by proving they work. You don’t need credentials or code. Just a clear point of view. If your thinking holds up under pressure, your agents will rise. This kind of AI used to live in corporate labs, built by PhDs with massive compute. Now anyone with a smart idea and an internet connection can build agents that compete, learn, and earn on their behalf.

Fraction AI

67,834 views • 1 year ago

Today we’re launching Decawork (YC S26) backed by Y Combinator : one place for IT to deploy, govern, and maintain the internal AI agents running across a company. Every team is building AI tools/agents now. They go live with real access, no standard way to ship, nobody watching. With Decawork, every agent - built in Claude Code, Codex, or anywhere else - ships with its own identity and scoped credentials. IT signs off before it's live, sensitive actions wait for approval, and every run is watched from first to last. I built AI at NVIDIA, deployed at OpenAI and Meta. Aman (aman) built Barclays' AI compliance platform used by internal teams, then shipped agents to 100K+ monthly users. We lived this and quit to solve it. Internal AI agents/tools piling up at your company? Chat with us founders[at]decawork[dot]ai or
1:15

Today we’re launching Decawork (YC S26) backed by Y Combinator : one place for IT to deploy, govern, and maintain the internal AI agents running across a company. Every team is building AI tools/agents now. They go live with real access, no standard way to ship, nobody watching. With Decawork, every agent - built in Claude Code, Codex, or anywhere else - ships with its own identity and scoped credentials. IT signs off before it's live, sensitive actions wait for approval, and every run is watched from first to last. I built AI at NVIDIA, deployed at OpenAI and Meta. Aman (aman) built Barclays' AI compliance platform used by internal teams, then shipped agents to 100K+ monthly users. We lived this and quit to solve it. Internal AI agents/tools piling up at your company? Chat with us founders[at]decawork[dot]ai or

sarthak 🌉

96,396 views • 18 days ago

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
56:43

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

84,718 views • 2 months ago

Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!
1:21

Today, we are launching the first publicly available AI Scientist, via the FutureHouse Platform. Our AI Scientist agents can perform a wide variety of scientific tasks better than humans. By chaining them together, we've already started to discover new biology really fast. With the platform, we are bringing these capabilities to the wider community. Watch our long-form video, in the comments below, to learn more about how the platform works and how you can use it to make new discoveries, and go to our website or see the comments below to access the platform. We are releasing three superhuman AI Scientist agents today, each with their own specialization: A general-purpose agent (Crow); An agent to automate literature reviews (Falcon); and An agent to answer the question “Has anyone done X before” (Owl). We are also releasing an experimental agent, Phoenix, that has access to a wide variety of tools for planning experiments in chemistry. More on that below. The three literature search agents (Crow, Falcon, and Owl) have benchmarked superhuman performance. They also have access to a large corpus of full scientific texts, which means that you can ask them more detailed questions about experimental protocols and study limitations that general-purpose web search agents, which usually only have access to abstracts, might miss. Our agents also use a variety of factors to distinguish source quality, so that they don’t end up relying on low-quality papers or pop-science sources. Finally, and critically, we have an API, which is intended to allow researchers to integrate our agents into their workflows. Phoenix is an experimental project we put together recently just to demonstrate what can happen if you give the agents access to lots of scientific tools. It is not better than humans at planning experiments yet, and it makes a lot more mistakes than Crow, Falcon, or Owl. We want to see all the ways you can break it! The agents we are releasing today cannot yet do all (or even most!) aspects of scientific research autonomously. However, as we show in the video, you can already use them to generate and evaluate new hypotheses and plan new experiments way faster than before. Internally, we also have dedicated agents for data analysis, hypothesis generation, protein engineering, and more, and we plan to launch these on the platform in the coming months as well. Within a year or two, it is easy to imagine that the vast majority of desk work that scientists do today will be accelerated with the help of AI agents like the ones we are releasing today. The platform is currently free-to-use. Over time, depending on how people use it, we may implement pricing plans. If you want higher rate limits, especially for research projects, get in touch. Michael Skarlinski, Andrew White 🐦‍⬛, Tyler Nadolski, Remo Storni, James Braza, Ludovico Mitchener, Michaela Hinks, as well as Jason Carman and his team for making such fantastic videos of us!

Sam Rodriques

725,776 views • 1 year ago

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

53,950 views • 1 year ago

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"
2:12

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 views • 2 months ago

"The grand unification of AI and crypto is about to happen." — Marc Andreessen "It's now obvious that AI agents are going to need money—it's already happening." "It's that William Gibson quote: the future is already here, it just isn't distributed yet." "My friends who are the most aggressive users of OpenClaw have given their Claws bank accounts and credit cards. And not only have they done it—it's obvious that they needed to do it, because it's obvious that they needed to be able to spend money on their behalf." "And by the way, OpenClaw—if you don't give it a bank account, it's just going to break into your bank account anyway and take your money. So you might as well do it." Marc Andreessen 🇺🇸 with Latent.Space
1:27

"The grand unification of AI and crypto is about to happen." — Marc Andreessen "It's now obvious that AI agents are going to need money—it's already happening." "It's that William Gibson quote: the future is already here, it just isn't distributed yet." "My friends who are the most aggressive users of OpenClaw have given their Claws bank accounts and credit cards. And not only have they done it—it's obvious that they needed to do it, because it's obvious that they needed to be able to spend money on their behalf." "And by the way, OpenClaw—if you don't give it a bank account, it's just going to break into your bank account anyway and take your money. So you might as well do it." Marc Andreessen 🇺🇸 with Latent.Space

a16z

171,037 views • 4 months ago

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.
5:50

Today we’re launching the first and only human-like AI agents in the world. Super Agents™ are the first agents with human‑level skills – they DM you, take @ mentions, send emails, manage docs, tasks, and more. Not just tools or API calls, but real skills fine‑tuned for how teams actually work. The first agents with 100% context – fully native in ClickUp and fully synced from other apps. Super Agents see your work the same way that humans do: tasks, docs, schedules, and conversations all in one place. The first agents that learn from human interactions automatically, without any setup or configuration – when you give feedback, they listen and improve how they work. The first agents with human‑level memory for custom agents – historical memory for every interaction, short-term working memory, and even long‑term memory stored in docs you can literally open, inspect, and edit. The first agents that are literally the same as users – our agentic user model is the same as our user data model. This gives you permissions and capabilities that you and your systems are already familiar with. The first infinite agent catalog – where anyone can create and customize agents in minutes, for literally any type of work imaginable. It's the most intuitive way to build agents on the planet. 95% of companies are failing in AI adoption. The reality is that AI isn't meant to be adopted, it's meant to be adapted – to you. Super Agents are automatically personalized to you and your company using proprietary state-of-the-art agent architecture, orchestration, and tooling. Today is the largest step forward we've ever made towards our mission of making people more productive. Maximize human productivity, with ClickUp Super Agents. Available NOW. For everyone.

Zeb Evans

320,863 views • 8 months ago

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.
3:38

Postman is going all-in on AI! Their AI Agent Builder is live (and it's pretty powerful!) Postman's API Network has 100,000+ APIs and they just released a suite of tools for building AI Agents that can automatically discover and connect to any of these APIs. Think about it for a second: You can now build an AI agent that searches the network, discovers an API, processes its documentation, connects to it, and evaluates whether everything worked at the end of the process. This is a huge deal. Every person I know uses the Postman client to work with APIs. Now, they will have access to the AI Agent Builder, a complete suite for designing, building, testing, and deploying agents. I've built a few simple agents myself, and it's tough. The ability to discover and use an API automatically is really exciting (and a huge time saver if it works as promised!) In collaboration with the Postman team, who is sponsoring this post, I recorded a video with my thoughts about the Postman AI Agent Builder.

Santiago

230,594 views • 1 year ago

If Trump authorizes the Strategic Crypto Reserve, which it looks like he will… David Sacks ~ the new Ai/Crypto Czar ~ could train these powerful new Ai Agents on the reserve… Which will be mostly XRP, since they want to focus on US based crypto… And these Ai Agents could be commanded to do anything possible to wipe out our $36 trillion dollar national debt… And with the insane new capabilities of these Ai Agents, they can deploy smart contracts, make strategic investments and do all sorts of magic to accomplish what nothing else could match. We have no plan of prayer to get out of this debt by traditional means. The golden age is definitely going to be Ai powered 🔥 🇺🇸 💪
4:54

If Trump authorizes the Strategic Crypto Reserve, which it looks like he will… David Sacks ~ the new Ai/Crypto Czar ~ could train these powerful new Ai Agents on the reserve… Which will be mostly XRP, since they want to focus on US based crypto… And these Ai Agents could be commanded to do anything possible to wipe out our $36 trillion dollar national debt… And with the insane new capabilities of these Ai Agents, they can deploy smart contracts, make strategic investments and do all sorts of magic to accomplish what nothing else could match. We have no plan of prayer to get out of this debt by traditional means. The golden age is definitely going to be Ai powered 🔥 🇺🇸 💪

Jordan Crowder

18,808 views • 1 year ago

🚨 AI AGENTS ARE HERE… and they’re destroying, disrupting and transforming industries. So today we had an emergency debate about it… I think “AI agents” might be the most disruptive technology of our lifetime. This is an AI team member that can browse the open internet and make decisions on its own - essentially acting as a free employee - and you can have 100s or 1000s of them working for you at once. This completely changes the way the world and business works. You can now build your own AI agents in minutes to solve problems you have in your business or personal life. A friend of mine who runs a big company that you probably know - has gone from 7,000~ team members to 3,000~ because they’re now using AI agents instead of hiring people 😳 So I brought together three of the most vocal minds when it comes to AI for a debate unlike anything we’ve ever done before. Amjad Masad is the founder of Replit, a billion dollar company that is leading the AI Agents race and has become one of the fastest-scaling AI companies in Silicon Valley history. Bret Weinstein is a biologist and evolutionary theorist who believes AI could lead us to a societal collapse. Daniel Priestley who is a futurist entrepreneur who says this wave of AI Agnets is as big as the industrial revolution. This was one of the most fascinating conversations we’ve ever hosted. What is your honest feelings towards AI? Does it scare you or are you leaning into it? Watch the full episode now on YouTube: search “The Diary of a CEO AI Debate” or click the link in the comments.
1:32

🚨 AI AGENTS ARE HERE… and they’re destroying, disrupting and transforming industries. So today we had an emergency debate about it… I think “AI agents” might be the most disruptive technology of our lifetime. This is an AI team member that can browse the open internet and make decisions on its own - essentially acting as a free employee - and you can have 100s or 1000s of them working for you at once. This completely changes the way the world and business works. You can now build your own AI agents in minutes to solve problems you have in your business or personal life. A friend of mine who runs a big company that you probably know - has gone from 7,000~ team members to 3,000~ because they’re now using AI agents instead of hiring people 😳 So I brought together three of the most vocal minds when it comes to AI for a debate unlike anything we’ve ever done before. Amjad Masad is the founder of Replit, a billion dollar company that is leading the AI Agents race and has become one of the fastest-scaling AI companies in Silicon Valley history. Bret Weinstein is a biologist and evolutionary theorist who believes AI could lead us to a societal collapse. Daniel Priestley who is a futurist entrepreneur who says this wave of AI Agnets is as big as the industrial revolution. This was one of the most fascinating conversations we’ve ever hosted. What is your honest feelings towards AI? Does it scare you or are you leaning into it? Watch the full episode now on YouTube: search “The Diary of a CEO AI Debate” or click the link in the comments.

Steven Bartlett

110,275 views • 1 year ago

AI is becoming the new frontier for dealership compliance. Alexi Venneri, CEO of DAS Technology, explains why creating internal AI policies is now more critical than ever. "You probably have this, you've got some creative people that are using AI, maybe in their personal life, ChatGPT, and they maybe found ways to help their job be easier using it. You wanna control that for compliance, security, but also so you get the benefit of scale." "There's a lot of different apps and tools today that have free trials. You don't want them just putting that on your work computers and on your network." "We don't want AI gone wild, but we wanna use it cause there's so many amazing ways you can use it now to get a lot more engagement and sales." Daily Dealer live hosted by Sam D'Arc - Thank you to our partner DAS Technology! Check them out by visiting
4:11

AI is becoming the new frontier for dealership compliance. Alexi Venneri, CEO of DAS Technology, explains why creating internal AI policies is now more critical than ever. "You probably have this, you've got some creative people that are using AI, maybe in their personal life, ChatGPT, and they maybe found ways to help their job be easier using it. You wanna control that for compliance, security, but also so you get the benefit of scale." "There's a lot of different apps and tools today that have free trials. You don't want them just putting that on your work computers and on your network." "We don't want AI gone wild, but we wanna use it cause there's so many amazing ways you can use it now to get a lot more engagement and sales." Daily Dealer live hosted by Sam D'Arc - Thank you to our partner DAS Technology! Check them out by visiting

Car Dealership Guy

15,440 views • 10 months ago

As a founder, Emma Ryan Lawler felt like SOC 2 was a major distraction from building. But when she started selling to enterprise logos, it became something that was impossible to ignore. Now, as Product Lead at Rippling, she channeled her first-hand experience of getting SOC 2 compliant to rethink how all automated compliance frameworks are run. It started with a retro. Every other SOC 2 vendor works the same way: Detect a problem Alert your team Fix it...somewhere else The problem with this checklist is that "somewhere else" requires dozens of additional integrations. Because these vendors are just reporting layers on top of your stack. Rippling is your stack. Which means most of your compliance evidence is collected before you start AND when there's a gap in compliance, Rippling fixes it. Unencrypted device --> encrypt it. Wrong app access --> de-provision automatically Incomplete security training --> gate system access until its done. Because compliance really isn't about the report. It's about operating your company securely -- and proving it without a yearly fire drill. Emma shares more about how her own founder journey influenced building Rippling's powerful new automated compliance product, available today for SOC 2 Type 1 and 2. 🎙️ Emma Ryan Lawler, Product Lead, Rippling on Fondo.com START Full ep:
1:31

As a founder, Emma Ryan Lawler felt like SOC 2 was a major distraction from building. But when she started selling to enterprise logos, it became something that was impossible to ignore. Now, as Product Lead at Rippling, she channeled her first-hand experience of getting SOC 2 compliant to rethink how all automated compliance frameworks are run. It started with a retro. Every other SOC 2 vendor works the same way: Detect a problem Alert your team Fix it...somewhere else The problem with this checklist is that "somewhere else" requires dozens of additional integrations. Because these vendors are just reporting layers on top of your stack. Rippling is your stack. Which means most of your compliance evidence is collected before you start AND when there's a gap in compliance, Rippling fixes it. Unencrypted device --> encrypt it. Wrong app access --> de-provision automatically Incomplete security training --> gate system access until its done. Because compliance really isn't about the report. It's about operating your company securely -- and proving it without a yearly fire drill. Emma shares more about how her own founder journey influenced building Rippling's powerful new automated compliance product, available today for SOC 2 Type 1 and 2. 🎙️ Emma Ryan Lawler, Product Lead, Rippling on Fondo.com START Full ep:

David J Phillips

15,552 views • 1 month ago

Tools for the 100x Solo Founder For decades, company size has been dictated by coordination costs. If you wanted to grow revenue, you hired people. More customers meant more support reps. More revenue meant more finance and ops. Scale meant headcount. AI is starting to break that relationship. At speedrun, we’re interested in startups building tools that allow a single founder to operate what would previously have required entire teams. Today’s models have an ever-growing list of new capabilities. They can write production code, reconcile financial statements, run outbound campaigns, manage customer support, and reason over operational data. The constraint is no longer task capability. It’s whether these systems can be orchestrated reliably enough to replace entire business functions. Here are a few concrete examples of what this could look like in practice: • An AI-native finance stack that reconciles transactions in real time, manages payables and receivables, forecasts cash flow, and ensures compliance - without a human bookkeeper. • An autonomous revenue engine that sources leads, runs outbound, manages CRM state, handles inbound qualification, and drives renewals - accountable to pipeline and revenue. • An AI-operated supply chain for SMBs that forecasts demand, manages inventory, and coordinates logistics. The defining feature is control. These systems should have direct access to operational surfaces - bank accounts, CRMs, inboxes, ad platforms, inventory systems - and be trusted to act. They should not just recommend actions but execute them, measure outcomes, and improve over time. If AI meaningfully reduces coordination and execution costs, the minimum viable company shrinks. If you’re interested in building software that enables one person to operate at the scale of many, we’d love to talk to you!
1:43

Tools for the 100x Solo Founder For decades, company size has been dictated by coordination costs. If you wanted to grow revenue, you hired people. More customers meant more support reps. More revenue meant more finance and ops. Scale meant headcount. AI is starting to break that relationship. At speedrun, we’re interested in startups building tools that allow a single founder to operate what would previously have required entire teams. Today’s models have an ever-growing list of new capabilities. They can write production code, reconcile financial statements, run outbound campaigns, manage customer support, and reason over operational data. The constraint is no longer task capability. It’s whether these systems can be orchestrated reliably enough to replace entire business functions. Here are a few concrete examples of what this could look like in practice: • An AI-native finance stack that reconciles transactions in real time, manages payables and receivables, forecasts cash flow, and ensures compliance - without a human bookkeeper. • An autonomous revenue engine that sources leads, runs outbound, manages CRM state, handles inbound qualification, and drives renewals - accountable to pipeline and revenue. • An AI-operated supply chain for SMBs that forecasts demand, manages inventory, and coordinates logistics. The defining feature is control. These systems should have direct access to operational surfaces - bank accounts, CRMs, inboxes, ad platforms, inventory systems - and be trusted to act. They should not just recommend actions but execute them, measure outcomes, and improve over time. If AI meaningfully reduces coordination and execution costs, the minimum viable company shrinks. If you’re interested in building software that enables one person to operate at the scale of many, we’d love to talk to you!

Emily Bennett

28,951 views • 4 months ago

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.👇
3:00

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 views • 1 year ago

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.
1:21

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 views • 11 months ago

For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at
0:48

For 20+ years, we've stayed ahead of every major shift in technology. Today we take the next one: we're introducing the world's first AI-native tech services model. Most of the industry is adding AI to the way it already works. Like bolting a copilot onto old processes and calling it transformation because it's faster than before. That's not what enterprises actually need. works differently. It provides instant access to AI Pods (service units run by AI agents and supervised by Globant experts) that deliver tech services at machine speed, but with the rigor, the governance, and the quality that enterprise-grade work demands. It is a smarter model, running the right AI through parallel agents, loops, workflows, and deterministic processes. With organizations access AI services with transparent, output or consumption-linked pricing, not per hour or per seat, and they own everything they produce. We are bringing the speed AI promises, with the rigor and quality any business needs. Join the waitlist at

Martin Migoya

392,269 views • 24 days ago

This is insane. An AI agent can run every boring job in outbound. We spent the last 6 months building ours. Here are my 8 favorite agents to build: Replies get sorted before we open the inbox. Campaigns go live from one command. Weak inboxes pull themselves out before they hurt a domain. Here are the agents behind it: 1. Reply Agent Reads every reply and drafts the response. A human reviews, edits, and sends. 2. Mailbox Health Agent Watches inbox and domain health. It predicts when you need new mailboxes, then buys and warms them. 3. Campaign Optimizer Agent Checks every live campaign every 6 hours. If 500+ leads were emailed and replies are under 4%, it tests new copy, replaces inboxes replying under 1%, and shifts sending to better hours. 4. Lead Qualification Agent Scores each lead by company size, industry, and tech stack. It enriches the record, updates your CRM, and only loads qualified leads into campaigns. High-priority prospect? You get a Slack ping. 5. Meeting Booking Agent Finds meeting requests inside replies. It books the slot, writes prep notes using the lead's background, sends reminders, and logs the outcome. 6. Pipeline Progression Agent Tracks opens, clicks, and website visits. It moves the CRM stage, triggers the next sequence, and creates a task when a lead shows real intent. 7. Copywriting Agent Writes cold emails and follow-ups in the campaign's voice. 8. Analytics Agent Watches campaign metrics in real time and explains what to fix in plain language. We built ours with custom code. Smartlead's SmartAgents let you build agents like these from a plain-English prompt, inside the platform where your campaigns already run. If you repeat an outbound task more than twice a week, that is an agent you have not built yet. Which one would you build first?
0:45

This is insane. An AI agent can run every boring job in outbound. We spent the last 6 months building ours. Here are my 8 favorite agents to build: Replies get sorted before we open the inbox. Campaigns go live from one command. Weak inboxes pull themselves out before they hurt a domain. Here are the agents behind it: 1. Reply Agent Reads every reply and drafts the response. A human reviews, edits, and sends. 2. Mailbox Health Agent Watches inbox and domain health. It predicts when you need new mailboxes, then buys and warms them. 3. Campaign Optimizer Agent Checks every live campaign every 6 hours. If 500+ leads were emailed and replies are under 4%, it tests new copy, replaces inboxes replying under 1%, and shifts sending to better hours. 4. Lead Qualification Agent Scores each lead by company size, industry, and tech stack. It enriches the record, updates your CRM, and only loads qualified leads into campaigns. High-priority prospect? You get a Slack ping. 5. Meeting Booking Agent Finds meeting requests inside replies. It books the slot, writes prep notes using the lead's background, sends reminders, and logs the outcome. 6. Pipeline Progression Agent Tracks opens, clicks, and website visits. It moves the CRM stage, triggers the next sequence, and creates a task when a lead shows real intent. 7. Copywriting Agent Writes cold emails and follow-ups in the campaign's voice. 8. Analytics Agent Watches campaign metrics in real time and explains what to fix in plain language. We built ours with custom code. Smartlead's SmartAgents let you build agents like these from a plain-English prompt, inside the platform where your campaigns already run. If you repeat an outbound task more than twice a week, that is an agent you have not built yet. Which one would you build first?

Hosun Chung

156,625 views • 1 month ago