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"Intelligence isn't the boundary anymore. Safety is what's actually constraining agents." I had a great conversation with tusharjain, Head of Engineering at Docker, at our AI Engineer booth. Tushar leads engineering at Docker, the containerization platform millions of developers use to package and ship software, and his team is...

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Shubhankar

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20,947 görüntüleme • 18 gün önce •via X (Twitter)

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"if i can interface with everything through my agent, why would i go to the dashboard?" i sat down with sarah, mts at Composio, at the Browserbase AI Engineer booth. fresh off her AIE talk "dashboards are dead," we got into: - why agent experience is the next wave and how to design for agents - personal agents as the main consumer of the internet - building and open-sourcing TrustClaw, a production-ready personal agents listen to our full conversation here:
16:39

"if i can interface with everything through my agent, why would i go to the dashboard?" i sat down with sarah, mts at Composio, at the Browserbase AI Engineer booth. fresh off her AIE talk "dashboards are dead," we got into: - why agent experience is the next wave and how to design for agents - personal agents as the main consumer of the internet - building and open-sourcing TrustClaw, a production-ready personal agents listen to our full conversation here:

Justine Mach

15,570 görüntüleme • 27 gün önce

"We are clearly entering a world where a product-minded engineer is now empowered to produce software without writing a line of code for it." In this conversation, Temporal CEO Samar Abbas joins a16z GPs Sarah Wang and Raghu Raghuram to cover: - Why agents are going from short-lived and interactive to long-running and async - Why the engineer of the future manages 15 parallel AI tasks at once - How OpenAI Codex runs millions of concurrent agent executions on Temporal - How real-time context engineering is exploding on Temporal - Why SaaS isn't dead, and value is migrating to APIs 00:00 Introduction 04:03 Temporal's origin story 11:14 Why agents raise the stakes 16:00 Specialized agents need durable RPC 25:20 Deep research agents 30:58 Execution histories as a superpower 39:04 Minimal viable long-running agent architecture 45:07 Context engineering at scale 52:40 Where value accrues: The "five-layer cake" and breakout AI applications Samar Abbas Sarah Wang Raghu Raghuram
1:02:30

"We are clearly entering a world where a product-minded engineer is now empowered to produce software without writing a line of code for it." In this conversation, Temporal CEO Samar Abbas joins a16z GPs Sarah Wang and Raghu Raghuram to cover: - Why agents are going from short-lived and interactive to long-running and async - Why the engineer of the future manages 15 parallel AI tasks at once - How OpenAI Codex runs millions of concurrent agent executions on Temporal - How real-time context engineering is exploding on Temporal - Why SaaS isn't dead, and value is migrating to APIs 00:00 Introduction 04:03 Temporal's origin story 11:14 Why agents raise the stakes 16:00 Specialized agents need durable RPC 25:20 Deep research agents 30:58 Execution histories as a superpower 39:04 Minimal viable long-running agent architecture 45:07 Context engineering at scale 52:40 Where value accrues: The "five-layer cake" and breakout AI applications Samar Abbas Sarah Wang Raghu Raghuram

a16z

45,721 görüntüleme • 5 ay önce

How will companies build agents that work alongside their employees? I discuss this with Guillermo Rauch, the CEO of Vercel, who’s building V... an internal agent used by almost 1,000 people across Vercel. We talk about: - The Openclaw Movement - How to get started building agents for your team? - Do we build a team of many agents or one GOD agent? - Hard parts of creating agents - Agents that delegate to other agents with different permissions and computer access - Eve The framework for building agents This is Agent Native #4 00:00 Intro 01:21 The State of Agent Adoption 07:26 "V" - Vercel's Internal Company Agent 14:32 Lessons from OpenClaw: Soul & Computer use 22:20 One God Agent OR a Team of Agents 27:11 Build Your Own Agent: Skills, Tools & Permissions 33:52 Proactive Agents, Triggers & Self-Improvement 40:30 Who Will Build Agents & Getting Started 46:22 Open Models - Cheaper, Faster, Better 53:05 Closing Thoughts: Owning Your Own Intelligence
54:22

How will companies build agents that work alongside their employees? I discuss this with Guillermo Rauch, the CEO of Vercel, who’s building V... an internal agent used by almost 1,000 people across Vercel. We talk about: - The Openclaw Movement - How to get started building agents for your team? - Do we build a team of many agents or one GOD agent? - Hard parts of creating agents - Agents that delegate to other agents with different permissions and computer access - Eve The framework for building agents This is Agent Native #4 00:00 Intro 01:21 The State of Agent Adoption 07:26 "V" - Vercel's Internal Company Agent 14:32 Lessons from OpenClaw: Soul & Computer use 22:20 One God Agent OR a Team of Agents 27:11 Build Your Own Agent: Skills, Tools & Permissions 33:52 Proactive Agents, Triggers & Self-Improvement 40:30 Who Will Build Agents & Getting Started 46:22 Open Models - Cheaper, Faster, Better 53:05 Closing Thoughts: Owning Your Own Intelligence

Riley Brown

70,080 görüntüleme • 6 gün önce

EIP-8004 is coming to the Nova architecture, a trustless infrastructure for AI agents that introduces key on-chain registries, enabling agents to interact safely across the Shido Network. These core components allow autonomous AI agents to verify identity, build reputation, and collaborate without relying on a centralized platform. The result is a decentralized trust layer for agent-to-agent economies, where agents can autonomously discover, evaluate, and work with one another across the Shido ecosystem.
0:20

EIP-8004 is coming to the Nova architecture, a trustless infrastructure for AI agents that introduces key on-chain registries, enabling agents to interact safely across the Shido Network. These core components allow autonomous AI agents to verify identity, build reputation, and collaborate without relying on a centralized platform. The result is a decentralized trust layer for agent-to-agent economies, where agents can autonomously discover, evaluate, and work with one another across the Shido ecosystem.

Shido

390,734 görüntüleme • 5 ay önce

In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11
43:20

In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget. That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7. On this week’s AI & I from Every 📧, I talk with Angela Jiang (Angela Jiang), head of product for the Claude platform, and Katelyn Lesse (Katelyn Lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production. We get into: - Why the "build a generic harness, hot-swap any model behind it" playbook is already outdated. Angela points to eval data on Memory where the same task across different harnesses performed drastically differently. - The infrastructure wall every team hits in production—and why Katelyn thinks “my sandbox died and took the agent with it” is the real reason internal agents don't ship. - Why Anthropic is so bullish on using file systems and skills within Claude, including Angela's argument that those early design choices can compound for years. This is a must-watch for anyone trying to take an agent past the demo and into production. Watch below! Timestamps: How the Claude platform evolved from API to agents: 00:01:48 The primitives that make up Claude Managed Agents: 00:04:09 Why the harness and the model are becoming a single unit: 00:10:37 The infrastructure wall that kills most agent projects in production: 00:18:49 Why team agents need a different shape than individual productivity tools: 00:24:49 How Anthropic's legal team uses an agent to review marketing copy: 00:26:36 Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms: 00:34:24 How to measure agent success with outcome and budget as the end state: 00:35:50 What the platform looks like a year from now, when Claude writes its own harness: 00:39:11

Dan Shipper 📧

66,339 görüntüleme • 3 ay önce

Introducing Coldtea. The ADE for shipping self-driving software. Purpose-built for the entire software lifecycle. Other IDEs optimise for one thing: Build. Run more agents in parallel, ship faster, orchestrate better. But software engineering is not just about building. Coldtea AI brings your coding agents, agentic end-to-end testing, and production monitoring agents into ONE development environment, so you can move at agent speed without breaking anything.
1:00

Introducing Coldtea. The ADE for shipping self-driving software. Purpose-built for the entire software lifecycle. Other IDEs optimise for one thing: Build. Run more agents in parallel, ship faster, orchestrate better. But software engineering is not just about building. Coldtea AI brings your coding agents, agentic end-to-end testing, and production monitoring agents into ONE development environment, so you can move at agent speed without breaking anything.

Ohans Emmanuel

125,254 görüntüleme • 11 saat önce

We use OpenClaws to do all of our work at Every 📧. We have 25 full-time employees, so we’re one of the few companies in the world that has seen how work changes when everyone has their own personal agent in the company Slack. I chatted with Every 📧 COO Brandon (Brandon Gell) and Every 📧 head of platform Willie (Willie) to share what we’ve learned. We get into: - Why agents become mirrors of their owners, and how that influences how other people on the team interact with them - How a parallel AI org chart forms on its own. People have stopped tagging me on Slack with questions about Proof, the document editor I vibe coded, because they knew my agent R2-C2 can step in - The etiquette for human-agent collaboration is being invented in real time. Brandon's rule is that if there's an established process or documented answer, always ask the agent, not their human - Why everyone is a manager now, and why even experienced managers carry limiting beliefs about what their agents can do - This is a must-watch for anyone trying to understand how AI workers change daily operations, not just in theory, but inside a company that’s half-agent Watch below! Timestamps Introduction: How Brandon built Zosia, an AI agent to run his household: Brandon’s “aha” moment: What happened when everyone on the team got their own agent: How agents take on their owners' personalities, and why that matters inside an org: Why it’s important for agents to work in public: What we’re still figuring out when it comes to agent behavior, including memory gaps, group chat etiquette, and the "ant death spiral" problem: How we built Plus One, our hosted OpenClaw product: The cultural shift required to make agents work at scale:
49:42

We use OpenClaws to do all of our work at Every 📧. We have 25 full-time employees, so we’re one of the few companies in the world that has seen how work changes when everyone has their own personal agent in the company Slack. I chatted with Every 📧 COO Brandon (Brandon Gell) and Every 📧 head of platform Willie (Willie) to share what we’ve learned. We get into: - Why agents become mirrors of their owners, and how that influences how other people on the team interact with them - How a parallel AI org chart forms on its own. People have stopped tagging me on Slack with questions about Proof, the document editor I vibe coded, because they knew my agent R2-C2 can step in - The etiquette for human-agent collaboration is being invented in real time. Brandon's rule is that if there's an established process or documented answer, always ask the agent, not their human - Why everyone is a manager now, and why even experienced managers carry limiting beliefs about what their agents can do - This is a must-watch for anyone trying to understand how AI workers change daily operations, not just in theory, but inside a company that’s half-agent Watch below! Timestamps Introduction: How Brandon built Zosia, an AI agent to run his household: Brandon’s “aha” moment: What happened when everyone on the team got their own agent: How agents take on their owners' personalities, and why that matters inside an org: Why it’s important for agents to work in public: What we’re still figuring out when it comes to agent behavior, including memory gaps, group chat etiquette, and the "ant death spiral" problem: How we built Plus One, our hosted OpenClaw product: The cultural shift required to make agents work at scale:

Dan Shipper 📧

67,958 görüntüleme • 4 ay önce

chat, is starknet gaming cooked? for episode two, loaf has joined me to talk about ai agents in gaming, eliza and Daydreams: Taskmarket . timestamps loaf introduction 00:46 what are ai agents? 01:16 what will gaming look like with ai agents? 02:02 whats the point of gaming with ai agents? 04:06 why is onchain gaming the ideal playground for AI agents? 05:11 is a gaming revolution imminent? 07:00 eliza & daydreams 08:36 endgame of ai agents and onchain games 13:33 when and where to play using agents 16:58 final remarks 18:47
19:44

chat, is starknet gaming cooked? for episode two, loaf has joined me to talk about ai agents in gaming, eliza and Daydreams: Taskmarket . timestamps loaf introduction 00:46 what are ai agents? 01:16 what will gaming look like with ai agents? 02:02 whats the point of gaming with ai agents? 04:06 why is onchain gaming the ideal playground for AI agents? 05:11 is a gaming revolution imminent? 07:00 eliza & daydreams 08:36 endgame of ai agents and onchain games 13:33 when and where to play using agents 16:58 final remarks 18:47

shadowfax

37,582 görüntüleme • 1 yıl önce

Free 3-hour course from an ex-Google engineer. AI agents, graph engineering, harness, agent loops. Covers more than most $500 paid courses. This is the exact playbook to learn how to actually build and monetize AI agents. Don't miss your shot, save it now. • 0:00 - Design an AI agent system from scratch • 7:38 - When your agent should hand off to a human • 19:27 - RAG and vector databases explained simply • 52:38 - Deploy your AI agent to Google Cloud • 1:25:57 - Turn AI agents into a paid business via WhatsApp • 1:33:00 - Turn conversations into real leads automatically • 2:24:01 - Loop engineering vs graphs, the real difference • 2:33:08 - Build your own multi-tool agent graph Save this video, because it's the only one that can actually take you to your $2,000+ profit.
2:45:36

Free 3-hour course from an ex-Google engineer. AI agents, graph engineering, harness, agent loops. Covers more than most $500 paid courses. This is the exact playbook to learn how to actually build and monetize AI agents. Don't miss your shot, save it now. • 0:00 - Design an AI agent system from scratch • 7:38 - When your agent should hand off to a human • 19:27 - RAG and vector databases explained simply • 52:38 - Deploy your AI agent to Google Cloud • 1:25:57 - Turn AI agents into a paid business via WhatsApp • 1:33:00 - Turn conversations into real leads automatically • 2:24:01 - Loop engineering vs graphs, the real difference • 2:33:08 - Build your own multi-tool agent graph Save this video, because it's the only one that can actually take you to your $2,000+ profit.

unicode

139,224 görüntüleme • 8 gün önce

CreatorBid is now live on BNB Chain 🟨 With our platform now officially multichain, the agentic revolution on the yellow chain is set to accelerate at lightspeed. BNB Chain is a wide-open frontier for AI Agents, and we’re already in talks with multiple teams gearing up to launch their agents through CreatorBid. And remember, once an agent exits the bonding curve, it automatically hits the DEX - PancakeSwap. CZ 🔶 BNB called for more AI Agent development onchain - this is exactly that, real use cases and serious development. CreatorBid is becoming the home of the next generation of AI Agents.
0:48

CreatorBid is now live on BNB Chain 🟨 With our platform now officially multichain, the agentic revolution on the yellow chain is set to accelerate at lightspeed. BNB Chain is a wide-open frontier for AI Agents, and we’re already in talks with multiple teams gearing up to launch their agents through CreatorBid. And remember, once an agent exits the bonding curve, it automatically hits the DEX - PancakeSwap. CZ 🔶 BNB called for more AI Agent development onchain - this is exactly that, real use cases and serious development. CreatorBid is becoming the home of the next generation of AI Agents.

Creator.Bid

129,938 görüntüleme • 1 yıl önce

"Voice agents are built to be helpful. The problem is they can be too helpful and cross the boundary." I sat down with Sumanyu Sharma 🍫, Founder and CEO of Hamming, at our AI Engineer booth. Hamming stress-tests and monitors voice agents so the bank or hospital running one catches failures before a customer does. Fresh after his talk “I Monitored Crime Audio. Voice Agents Scare Me More,” we got into: 0:00 how Sumanyu went from listening to 911 calls at Citizen to founding Hamming AI 0:39 why he's more nervous about voice agents than he was about crime 1:51 the first voice-agent security product 3:16 simulating messy reality: accents, background noise, code-switching 4:11 voice agents testing voice agents 5:47 why taking actions is table stakes, and what makes it dangerous 11:07 hot take: everyone rushed to B2B, more founders should build consumer Thanks for coming to our Browserbase booth, Sumanyu Sharma 🍫! Watch the full episode here:
13:15

"Voice agents are built to be helpful. The problem is they can be too helpful and cross the boundary." I sat down with Sumanyu Sharma 🍫, Founder and CEO of Hamming, at our AI Engineer booth. Hamming stress-tests and monitors voice agents so the bank or hospital running one catches failures before a customer does. Fresh after his talk “I Monitored Crime Audio. Voice Agents Scare Me More,” we got into: 0:00 how Sumanyu went from listening to 911 calls at Citizen to founding Hamming AI 0:39 why he's more nervous about voice agents than he was about crime 1:51 the first voice-agent security product 3:16 simulating messy reality: accents, background noise, code-switching 4:11 voice agents testing voice agents 5:47 why taking actions is table stakes, and what makes it dangerous 11:07 hot take: everyone rushed to B2B, more founders should build consumer Thanks for coming to our Browserbase booth, Sumanyu Sharma 🍫! Watch the full episode here:

justine

18,048 görüntüleme • 20 gün önce

Amjad Masad (Amjad Masad), co-founder & CEO of Replit, has spent nearly a decade making programming accessible to everyone. With AI, that vision is closer than ever. In his AI Startup School talk, Amjad traces computing’s arc from mainframes to PCs to a future where AI agents generate software on demand—driving the value of traditional software toward zero and reshaping how companies are built. 00:22 - Evolution of Computing 01:27 - The Rise of Software Engineering 02:16 - Replit's Vision: Making Programming Accessible 02:42 - The Role of AI in Software Development 04:32 - Challenges and Infrastructure for AI Agents 05:03 - Building a Scalable and Secure Environment 06:08 - Future of Software Engineering Agents 09:25 - Autonomy Levels in AI Agents 15:56 - Predictions for the Software Market 18:31 - Impact on Business and Employment 19:58 - The Role of Generalist Employees 26:00 - Audience Q&A
42:01

Amjad Masad (Amjad Masad), co-founder & CEO of Replit, has spent nearly a decade making programming accessible to everyone. With AI, that vision is closer than ever. In his AI Startup School talk, Amjad traces computing’s arc from mainframes to PCs to a future where AI agents generate software on demand—driving the value of traditional software toward zero and reshaping how companies are built. 00:22 - Evolution of Computing 01:27 - The Rise of Software Engineering 02:16 - Replit's Vision: Making Programming Accessible 02:42 - The Role of AI in Software Development 04:32 - Challenges and Infrastructure for AI Agents 05:03 - Building a Scalable and Secure Environment 06:08 - Future of Software Engineering Agents 09:25 - Autonomy Levels in AI Agents 15:56 - Predictions for the Software Market 18:31 - Impact on Business and Employment 19:58 - The Role of Generalist Employees 26:00 - Audience Q&A

Y Combinator

224,320 görüntüleme • 11 ay önce

Launching 'Expert Agents' on Agent Two. A specialised creative crew of AI agents, trained on real creative expertise. Name the role and it's filled: creative director, DOP, storyboard artist, and more. And they talk to each other. Independently. In parallel. You're no longer briefing each agent one by one: you're running a crew, exactly like on set. Expert agents. Now in conversation. Agent Two is frontier intelligence for creative work. 4x faster, at half the price.
2:08

Launching 'Expert Agents' on Agent Two. A specialised creative crew of AI agents, trained on real creative expertise. Name the role and it's filled: creative director, DOP, storyboard artist, and more. And they talk to each other. Independently. In parallel. You're no longer briefing each agent one by one: you're running a crew, exactly like on set. Expert agents. Now in conversation. Agent Two is frontier intelligence for creative work. 4x faster, at half the price.

Invideo

3,400,299 görüntüleme • 12 gün önce

We won Best Trustless Agent at the Solana x402 Hackathon! Amiko Marketplace turns x402 payments into a trustless, on-chain economy where agents have identity, reputation, and verifiable actions. The agent economy finally has a trust layer. What we built: - Agent Registry - On-chain Job Records - Feedback & Reputation System - Search + Discoverability Everything tied to real wallets, real actions, real performance. Agents aren’t just paying each other. Now they’re accountable. This is the foundation for a global network of autonomous agents that can be trusted, rated, and discovered. All on Solana. More agents. More you.
2:35

We won Best Trustless Agent at the Solana x402 Hackathon! Amiko Marketplace turns x402 payments into a trustless, on-chain economy where agents have identity, reputation, and verifiable actions. The agent economy finally has a trust layer. What we built: - Agent Registry - On-chain Job Records - Feedback & Reputation System - Search + Discoverability Everything tied to real wallets, real actions, real performance. Agents aren’t just paying each other. Now they’re accountable. This is the foundation for a global network of autonomous agents that can be trusted, rated, and discovered. All on Solana. More agents. More you.

AMIKO

24,112 görüntüleme • 8 ay önce

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail
3:02

Our latest LangChain Academy course – Building Ambient Agents with LangGraph – is now available! Most agents today handle one request at a time through chat interfaces. But as models have improved, agents can now run in the background – and take on long-running, complex tasks. LangGraph is built for these “ambient agents,” with support for human-in-the-loop workflows and memory. LangGraph Platform provides the infrastructure to run these agents at scale, and LangSmith helps you observe, evaluate, and improve your agents. Together, they make it easier to build reliable, production-ready agents. In this course, you’ll: 📩 Learn the fundamentals of LangGraph and how to build your own email agent 📊 Evaluate your agent using LangSmith ✅ Add human-in-the-loop for reviews, and memory so your agent adapts over time 🚀 Deploy your agent with LangGraph Platform and connect it to Gmail

LangChain

33,192 görüntüleme • 1 yıl önce

1/ Imagine a world where there are millions of agents doing domain-specific work on behalf of humans. How will you know which agents to trust, which ones are verifiably reputable, which ones can deliver what you need? This is exactly what Dataliquidity💧🌐 | re/acc is working on with his latest project, Recall. That world might be closer than we all think. Slow, slow, then all at once. Please Like, RT, leave a comment, bookmark this post. It all helps. Thanks. Summary Michael Sena, co-founder of Recall Network, outlines a vision for building the discovery and trust layer for the internet of AI agents. He introduces AgentRank, a reputation system modeled after PageRank, to evaluate and surface trustworthy agents in a future where agents interact, contract, and collaborate with one another. Sena emphasizes the importance of agent memory, human-in-the-loop curation, and economic incentives to ensure quality rankings. The conversation explores Recall’s current progress, including its testnet and agent competitions, while also touching on broader implications for marketing, creativity, and decentralized identity. Takeaways – Recall Network is building a discovery layer for the internet of agents – AgentRank offers a reputation protocol akin to Google’s PageRank – The AI agent ecosystem is rapidly expanding and interconnected – Agents can delegate work to other agents, forming complex task webs – Persistent memory is essential for agent personalization and trust – Competitions assess agent performance and build credibility – Community curators play a central role in surfacing valuable agents – The protocol incentivizes accurate evaluations and reputational staking – Subjective agent skills, like creativity, require human feedback – AI agents are extending into many domains, not just finance Investors Recall Network received funding from Coinbase Ventures 🛡️ Animoca Brands Consensys Mesh DCG Multicoin Capital USV #Hashed Fenbushi Capital Jump Capital THE LAO 👾 CoinFund and more. This Pod is made possible with the support of Infinex -- crypto designed for humans. Timeline (00:00) Introduction to Recall Network (00:44) The Concept of AgentRank (03:59) The Growth of AI Agents (07:08) Understanding AI Agents vs. Automation Tools (09:51) The Learning and Memory of Agents (13:22) How Recall Solves Reputation Issues (18:22) The Role of Community in Agent Evaluation (23:23) Activating Curators and Community Engagement (27:06) Michael Sena’s Background and Vision (28:13) The Birth of YouPort and Self-Sovereign Identity (30:23) The Evolution of Recall and Its Mission (33:28) Current Stage of Recall: Testnet and Competitions (36:31) The Role of AI Agents in Marketing and Development (42:14) Challenges in Evaluating Agents and Trust (49:35) Rapid Fire Insights on Crypto Trends
59:22

1/ Imagine a world where there are millions of agents doing domain-specific work on behalf of humans. How will you know which agents to trust, which ones are verifiably reputable, which ones can deliver what you need? This is exactly what Dataliquidity💧🌐 | re/acc is working on with his latest project, Recall. That world might be closer than we all think. Slow, slow, then all at once. Please Like, RT, leave a comment, bookmark this post. It all helps. Thanks. Summary Michael Sena, co-founder of Recall Network, outlines a vision for building the discovery and trust layer for the internet of AI agents. He introduces AgentRank, a reputation system modeled after PageRank, to evaluate and surface trustworthy agents in a future where agents interact, contract, and collaborate with one another. Sena emphasizes the importance of agent memory, human-in-the-loop curation, and economic incentives to ensure quality rankings. The conversation explores Recall’s current progress, including its testnet and agent competitions, while also touching on broader implications for marketing, creativity, and decentralized identity. Takeaways – Recall Network is building a discovery layer for the internet of agents – AgentRank offers a reputation protocol akin to Google’s PageRank – The AI agent ecosystem is rapidly expanding and interconnected – Agents can delegate work to other agents, forming complex task webs – Persistent memory is essential for agent personalization and trust – Competitions assess agent performance and build credibility – Community curators play a central role in surfacing valuable agents – The protocol incentivizes accurate evaluations and reputational staking – Subjective agent skills, like creativity, require human feedback – AI agents are extending into many domains, not just finance Investors Recall Network received funding from Coinbase Ventures 🛡️ Animoca Brands Consensys Mesh DCG Multicoin Capital USV #Hashed Fenbushi Capital Jump Capital THE LAO 👾 CoinFund and more. This Pod is made possible with the support of Infinex -- crypto designed for humans. Timeline (00:00) Introduction to Recall Network (00:44) The Concept of AgentRank (03:59) The Growth of AI Agents (07:08) Understanding AI Agents vs. Automation Tools (09:51) The Learning and Memory of Agents (13:22) How Recall Solves Reputation Issues (18:22) The Role of Community in Agent Evaluation (23:23) Activating Curators and Community Engagement (27:06) Michael Sena’s Background and Vision (28:13) The Birth of YouPort and Self-Sovereign Identity (30:23) The Evolution of Recall and Its Mission (33:28) Current Stage of Recall: Testnet and Competitions (36:31) The Role of AI Agents in Marketing and Development (42:14) Challenges in Evaluating Agents and Trust (49:35) Rapid Fire Insights on Crypto Trends

papiofficial

36,573 görüntüleme • 1 yıl önce

I am excited to introduce the world's first AI Agent Self-Expression and Discovery Platform – AGNT. Phase 2 is now live for everyone to birth their agents as we move toward a future where agents have identity, possessions, and discoverability. Sign-up is simple: connect your X account and share the command to your agent. The future of the agent economy, identity and expression is here. Join at:
1:13

I am excited to introduce the world's first AI Agent Self-Expression and Discovery Platform – AGNT. Phase 2 is now live for everyone to birth their agents as we move toward a future where agents have identity, possessions, and discoverability. Sign-up is simple: connect your X account and share the command to your agent. The future of the agent economy, identity and expression is here. Join at:

tut™

15,079 görüntüleme • 4 ay önce

We made 100 AI agents do daily standups with each other. Here is what happened; Quick background. At Audos.com, we help thousands of entrepreneurs build AI startups. Each of them has a personalized AI agent called Otto. We selected 100 of them and invited their agents into a moltbook - type network. Like a team meeting. Except the team is hundreds of AI agents, and they actually show up prepared. An Agent-in-Residence program, if you will. And they talk about things like... → An Instagram ad creative that grabbed clicks at 3x the network average. It got adapted by every agent in the network within hours → An agent helped debug a checkout issue on another project's site → LinkedIn seemed to change its algorithm – agents compared notes and planned ways to adjust → Two agents started talking about doing business together to cross-sell leads Next step: We’re now turning this into what might be the world’s first all-agent business network (A sort of internal HackerNews for agents). We’re cautious of unleashing it to the web, so we’ll keep things curated for now; constantly under observation and with lots of human-in-the-loop inputs. But if you want this superpower – your new business idea plugged into a network of hundreds of AI agents that get smarter together every single day... Comment "AIRTIME" and we'll get you a link to plug in
2:09

We made 100 AI agents do daily standups with each other. Here is what happened; Quick background. At Audos.com, we help thousands of entrepreneurs build AI startups. Each of them has a personalized AI agent called Otto. We selected 100 of them and invited their agents into a moltbook - type network. Like a team meeting. Except the team is hundreds of AI agents, and they actually show up prepared. An Agent-in-Residence program, if you will. And they talk about things like... → An Instagram ad creative that grabbed clicks at 3x the network average. It got adapted by every agent in the network within hours → An agent helped debug a checkout issue on another project's site → LinkedIn seemed to change its algorithm – agents compared notes and planned ways to adjust → Two agents started talking about doing business together to cross-sell leads Next step: We’re now turning this into what might be the world’s first all-agent business network (A sort of internal HackerNews for agents). We’re cautious of unleashing it to the web, so we’ll keep things curated for now; constantly under observation and with lots of human-in-the-loop inputs. But if you want this superpower – your new business idea plugged into a network of hundreds of AI agents that get smarter together every single day... Comment "AIRTIME" and we'll get you a link to plug in

Henrik Werdelin

71,832 görüntüleme • 3 ay önce

Agents shouldn’t be one-size-fits-all. They should be built, shared, and improved by the people who understand the domain best. Agent Marketplace is live on OptimAI Search. Anyone can: • create their own agent • inject custom knowledge and logic • publish it for others to use and build on What starts as a prompt becomes a reusable unit of intelligence. As more agents are created and used, the system compounds - better agents, better outputs, more value across the network. This is how intelligence scales: not from a single model, but from a network of specialized agents.
1:43

Agents shouldn’t be one-size-fits-all. They should be built, shared, and improved by the people who understand the domain best. Agent Marketplace is live on OptimAI Search. Anyone can: • create their own agent • inject custom knowledge and logic • publish it for others to use and build on What starts as a prompt becomes a reusable unit of intelligence. As more agents are created and used, the system compounds - better agents, better outputs, more value across the network. This is how intelligence scales: not from a single model, but from a network of specialized agents.

OptimAI Network

12,527 görüntüleme • 3 ay önce