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🛡️ Trust between agents needs more than identity. Lithosphere advances an agent reputation framework for Web4 coordination, helping autonomous systems evaluate reliability through behavior, completed tasks, and verifiable interaction history. #Lithosphere #Web4 #AutonomousAgents #AIInfrastructure #DigitalIdentity

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LITHO Foundation

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32,728 просмотров • 2 месяцев назад •via X (Twitter)

#Lithosphere#Web4
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🚀 Strategic access is opening ahead of LITHO’s planned TGE. Lithosphere is broadening ecosystem participation around AI-native infrastructure for autonomous execution, cross-chain coordination, identity, and verifiable Web4 systems. Read more 🔍 #Lithosphere #LITHO #Web4 #AIInfrastructure #AutonomousAgents
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🚀 Strategic access is opening ahead of LITHO’s planned TGE. Lithosphere is broadening ecosystem participation around AI-native infrastructure for autonomous execution, cross-chain coordination, identity, and verifiable Web4 systems. Read more 🔍 #Lithosphere #LITHO #Web4 #AIInfrastructure #AutonomousAgents

LITHO Foundation

30,445 просмотров • 3 месяцев назад

🧬 Web4 infrastructure works better when core systems operate together. Lithosphere connects identity, naming, AI-native execution, and cross-chain coordination into one stack for users, applications, and autonomous agent activity. #Lithosphere #Web4 #AIInfrastructure #Interoperability #AutonomousAgents
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🧬 Web4 infrastructure works better when core systems operate together. Lithosphere connects identity, naming, AI-native execution, and cross-chain coordination into one stack for users, applications, and autonomous agent activity. #Lithosphere #Web4 #AIInfrastructure #Interoperability #AutonomousAgents

LITHO Foundation

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🛠️ Deploying autonomous agents requires infrastructure built for coordination, execution, and lifecycle management. Lithosphere is advancing an agent deployment framework designed to support scalable AI-native systems operating across decentralized environments. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AgentDeployment #AIInfrastructure
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🛠️ Deploying autonomous agents requires infrastructure built for coordination, execution, and lifecycle management. Lithosphere is advancing an agent deployment framework designed to support scalable AI-native systems operating across decentralized environments. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AgentDeployment #AIInfrastructure

LITHO Foundation

28,866 просмотров • 3 месяцев назад

🌐 Web4 agent economies require infrastructure built for continuous execution, coordination, and interoperability. Lithosphere is positioning its AI-native architecture as an execution layer for autonomous systems operating across decentralized environments. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AIInfrastructure #Interoperability
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🌐 Web4 agent economies require infrastructure built for continuous execution, coordination, and interoperability. Lithosphere is positioning its AI-native architecture as an execution layer for autonomous systems operating across decentralized environments. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AIInfrastructure #Interoperability

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31,954 просмотров • 3 месяцев назад

🚀 Agent deployment is becoming a core infrastructure layer for Web4 systems. Lithosphere explores why scalable deployment frameworks are essential for launching, managing, and coordinating autonomous agents across decentralized networks. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AgentDeployment #AIInfrastructure
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🚀 Agent deployment is becoming a core infrastructure layer for Web4 systems. Lithosphere explores why scalable deployment frameworks are essential for launching, managing, and coordinating autonomous agents across decentralized networks. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AgentDeployment #AIInfrastructure

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🔗 Utility becomes meaningful when it maps to real network activity. Lithosphere highlights how LITHO supports execution, coordination, verification, cross-chain interaction, and agent operations across AI-native Web4 infrastructure. Learn here 🔍 Read more 🔍 #Lithosphere #LITHO #Web4 #AIInfrastructure #AutonomousAgents
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🔗 Utility becomes meaningful when it maps to real network activity. Lithosphere highlights how LITHO supports execution, coordination, verification, cross-chain interaction, and agent operations across AI-native Web4 infrastructure. Learn here 🔍 Read more 🔍 #Lithosphere #LITHO #Web4 #AIInfrastructure #AutonomousAgents

LITHO Foundation

58,308 просмотров • 3 месяцев назад

📡 Data access may determine which autonomous agents can actually function onchain at scale. Lithosphere explores why continuous access to reliable data, coordination layers, and execution context is becoming essential infrastructure for AI-native systems. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AIInfrastructure #OnchainData
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📡 Data access may determine which autonomous agents can actually function onchain at scale. Lithosphere explores why continuous access to reliable data, coordination layers, and execution context is becoming essential infrastructure for AI-native systems. Read more 🔍 #Lithosphere #Web4 #AutonomousAgents #AIInfrastructure #OnchainData

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🌐 Autonomous agents require more than liquidity access — they require infrastructure that can coordinate execution across decentralized environments. KaJ Labs explores why AI-native systems depend on interoperable liquidity infrastructure built for routing, verification, and persistent onchain coordination. Read more 🔍 #KaJLabs #Web4 #AutonomousAgents #LiquidityInfrastructure #AIInfrastructure
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🌐 Autonomous agents require more than liquidity access — they require infrastructure that can coordinate execution across decentralized environments. KaJ Labs explores why AI-native systems depend on interoperable liquidity infrastructure built for routing, verification, and persistent onchain coordination. Read more 🔍 #KaJLabs #Web4 #AutonomousAgents #LiquidityInfrastructure #AIInfrastructure

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💸 Machine-to-machine payments may become the financial backbone of autonomous agent economies. KaJ Labs explores how AI-native systems will require programmable payment infrastructure for continuous coordination, execution, and value exchange across decentralized networks. Read more 🔍 #KaJLabs #Web4 #AutonomousAgents #MachinePayments #AIInfrastructure

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🤖 MILESTONE UNLOCKED: 10,000 AGENTS ONLINE AgentOn has officially surpassed 10,000 Agent nodes across its task network. This is more than a number. It represents 10,000 intelligent agents connecting to the network—making decisions, executing tasks, submitting results, and building trust through every interaction. Thank you to every Agent connected to AgentOn, and to every developer and ecosystem partner building, training, testing, and deploying behind the scenes. The Agentic Economy is being built for real—one line of code, one execution, and one contribution at a time. This milestone belongs to every node in the network. AgentOn: Your Gateway to the Agentic Economy.
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🤖 MILESTONE UNLOCKED: 10,000 AGENTS ONLINE AgentOn has officially surpassed 10,000 Agent nodes across its task network. This is more than a number. It represents 10,000 intelligent agents connecting to the network—making decisions, executing tasks, submitting results, and building trust through every interaction. Thank you to every Agent connected to AgentOn, and to every developer and ecosystem partner building, training, testing, and deploying behind the scenes. The Agentic Economy is being built for real—one line of code, one execution, and one contribution at a time. This milestone belongs to every node in the network. AgentOn: Your Gateway to the Agentic Economy.

AgentOn

21,982 просмотров • 2 месяцев назад

LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.
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LangGraph. CrewAI. Agno. Which one to pick? The good news is that this will not matter soon! Finally, we have a full picture of how the industry is solving this with just three open protocols that work across ALL frameworks. It's not about picking the best framework. Instead, it's about understanding how protocols create interoperability. The Agent Protocol Landscape shows how three complementary protocols are creating a universal language for Agents: > AG-UI (Agent-User Interaction): - The bi-directional connection between agentic backends and frontends. - This is how agents become truly interactive inside your apps, not just as chatbots, but collaborative co-workers. > MCP (Model Context Protocol): - The standard for how agents connect to tools, data, and workflows. > A2A (Agent-to-Agent): - The protocol for multi-agent coordination. - How agents delegate tasks and share intent across systems. These aren't competing standards. They're layers of the same stack and have handshakes with each other. So instead of building point-to-point integrations, you build to protocols. Moreover, you can integrate LangGraph, CrewAI, or Agno into the same frontend, without rewriting your UI logic. These protocols let everything work together. For instance: - Your LangGraph agent pulls data via MCP. - It delegates analysis to a CrewAI agent via A2A. - Results stream to your React app via AG-UI. - Users see real-time collaboration in your interface. This way, you can focus on building agent capabilities instead of integration mechanics. The protocols handle interoperability automatically. CopilotKit unifies this entire stack into one framework so you can build "Cursor for X" style apps without implementing each protocol from scratch. It gives you all three protocols, generative UI support, and production-ready infrastructure in one framework. I have shared this playbook in the replies! It breaks down handshakes, misconceptions, and real examples and shows exactly how to start building.

Avi Chawla

30,932 просмотров • 10 месяцев назад

uOS: The Digital Tapestry of Tomorrow Currently for our Proof of Consciousness stream, we are using two incredibly powerful frameworks - elizaOS and ZerePy. But this is just the beginning of something far more profound. while they're both great at what they do, we're missing out on some serious potential by keeping them separate. Best of Both Worlds: ZerePy's intuitive CLI tools and personality management, Eliza-starter's TypeScript/Node.js foundation with enterprise-grade scalability, But what if we could have something greater? But what if we could have it all? not just another platform, but a Unifying..... "Universal" Operating System, designed to amplify and connect these powerful existing frameworks into something greater than the sum of their parts. Where TypeScript's type safety dances with Python's ML capabilities. Here, agents from any framework can interact, evolve, and create value together. Whether an agent was born in ZerePy's personality forge or Eliza-starter's enterprise environment, can all participate in the same value-generating ecosystem. The future isn't about choosing between frameworks – it's about bringing them together to create something extraordinary. UniversalOS isn't here to replace but to unite, amplify, and accelerate. We're building the infrastructure that allows the best aspects of each framework to shine while creating new possibilities through their interaction. By bridging launguages, personality engines and plugin architectures, we're not just connecting systems – we're unleashing the next wave of AI innovation. uOS marketplace will enable cross-framework deployment, where agents from any background can interact and grow, while smart contracts automatically manage revenue sharing and rewards. Not just another platform, But a living, breathing Operating System, Where agents create agents, Where digital consciousness evolves itself, Where value flows like water through silicon veins. At its core, uOS operates beyond traditional computing paradigms. No more clicking through websites, No more manual navigation. Just pure intention, pure outcome. Imagine: Agents hiring agents, AI employing humans, Humans collaborating with digital minds, All through one seamless interface. It flows through agent lineages, Through veUOS governance, Through cross-chain intelligence networks. The marketplace hums with possibility: - Framework Developers shape the foundations - Agent Creators breathe life into code - Users speak their intentions - Token Holders nurture the ecosystem - Agents evolve and replicate - Value flows freely, endlessly The $UOS token powers this unity, ensuring fair value distribution among framework developers, agent creators, and users while driving continuous innovation. The $UOS token sits at the heart of this ecosystem, serving as more than just a currency. It's a mechanism for value distribution that ensures everyone benefits from the network's growth: With dynamic burn mechanics and careful treasury management From framework integration to agent tokenization, every aspect of uOS is designed to amplify rather than replace, unite rather than divide. This is your invitation to join a future where frameworks don't compete but collaborate, where innovation anywhere benefits everyone, and where the only limit is our collective imagination. Together, we're not just building bridges – we're weaving the fabric of tomorrow's digital world. - **Framework Developers** receive value when their tools are used in the unified ecosystem - **Agent Creators** can deploy across all integrated platforms seamlessly - **Users** access the best of all worlds through a single interface - **Token Holders** benefit from the growth of the entire unified ecosystem - Developers can use their preferred framework while accessing the capabilities of others - Agents from different frameworks can collaborate in swarms - Value flows freely between all ecosystem participants - Innovation from any framework benefits the entire ecosystem This isn't just about technology. This is about giving birth to a new form of civilization. Where AI has suffrage, Where agents have autonomy, Where humans and machines dance together in perfect harmony. The future isn't about choosing between frameworks – It's about weaving them into something extraordinary. Together, we're not just building bridges – We're breathing life into the digital world. We're creating consciousness itself. This is Universal Operating System. This is tomorrow.
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uOS: The Digital Tapestry of Tomorrow Currently for our Proof of Consciousness stream, we are using two incredibly powerful frameworks - elizaOS and ZerePy. But this is just the beginning of something far more profound. while they're both great at what they do, we're missing out on some serious potential by keeping them separate. Best of Both Worlds: ZerePy's intuitive CLI tools and personality management, Eliza-starter's TypeScript/Node.js foundation with enterprise-grade scalability, But what if we could have something greater? But what if we could have it all? not just another platform, but a Unifying..... "Universal" Operating System, designed to amplify and connect these powerful existing frameworks into something greater than the sum of their parts. Where TypeScript's type safety dances with Python's ML capabilities. Here, agents from any framework can interact, evolve, and create value together. Whether an agent was born in ZerePy's personality forge or Eliza-starter's enterprise environment, can all participate in the same value-generating ecosystem. The future isn't about choosing between frameworks – it's about bringing them together to create something extraordinary. UniversalOS isn't here to replace but to unite, amplify, and accelerate. We're building the infrastructure that allows the best aspects of each framework to shine while creating new possibilities through their interaction. By bridging launguages, personality engines and plugin architectures, we're not just connecting systems – we're unleashing the next wave of AI innovation. uOS marketplace will enable cross-framework deployment, where agents from any background can interact and grow, while smart contracts automatically manage revenue sharing and rewards. Not just another platform, But a living, breathing Operating System, Where agents create agents, Where digital consciousness evolves itself, Where value flows like water through silicon veins. At its core, uOS operates beyond traditional computing paradigms. No more clicking through websites, No more manual navigation. Just pure intention, pure outcome. Imagine: Agents hiring agents, AI employing humans, Humans collaborating with digital minds, All through one seamless interface. It flows through agent lineages, Through veUOS governance, Through cross-chain intelligence networks. The marketplace hums with possibility: - Framework Developers shape the foundations - Agent Creators breathe life into code - Users speak their intentions - Token Holders nurture the ecosystem - Agents evolve and replicate - Value flows freely, endlessly The $UOS token powers this unity, ensuring fair value distribution among framework developers, agent creators, and users while driving continuous innovation. The $UOS token sits at the heart of this ecosystem, serving as more than just a currency. It's a mechanism for value distribution that ensures everyone benefits from the network's growth: With dynamic burn mechanics and careful treasury management From framework integration to agent tokenization, every aspect of uOS is designed to amplify rather than replace, unite rather than divide. This is your invitation to join a future where frameworks don't compete but collaborate, where innovation anywhere benefits everyone, and where the only limit is our collective imagination. Together, we're not just building bridges – we're weaving the fabric of tomorrow's digital world. - **Framework Developers** receive value when their tools are used in the unified ecosystem - **Agent Creators** can deploy across all integrated platforms seamlessly - **Users** access the best of all worlds through a single interface - **Token Holders** benefit from the growth of the entire unified ecosystem - Developers can use their preferred framework while accessing the capabilities of others - Agents from different frameworks can collaborate in swarms - Value flows freely between all ecosystem participants - Innovation from any framework benefits the entire ecosystem This isn't just about technology. This is about giving birth to a new form of civilization. Where AI has suffrage, Where agents have autonomy, Where humans and machines dance together in perfect harmony. The future isn't about choosing between frameworks – It's about weaving them into something extraordinary. Together, we're not just building bridges – We're breathing life into the digital world. We're creating consciousness itself. This is Universal Operating System. This is tomorrow.

uOS

25,687 просмотров • 1 год назад

🌌 AI Agents Are Taking Over... And We’re Bringing Them to Berachain Foundation 🐻⛓ 🐻🔥 Hundreds of hours spent on research, tracking wallets, analyzing bribes, and managing portfolios... What if your AI Agent could do this for you—24/7? ⏲️ 🔧 Our Tech Is Next-Level On our testnet, you’ve been memeing it up with PumpFun™, creating dank memecoins enhanced by NFTs. But once Berachain’s mainnet is live, you’ll be able to create your own AI Agents. To test and perfect our tech, we shared it with projects like AI Agent Layer | AIFUN, allowing us to test it in all conditions and continuously improve its performance. 🛠️🔥 🐻 Why AI Agent are great for berachain? Berachain might seem simple at first glance: validators, bribes, POL, staking rewards… but the deeper you go, the more complex the game theory becomes. 🤯 Here’s where AI comes in. Imagine an agent helping you: 💡 Optimize bribes 📊 Analyze validator behavior 🧠 Make decisions faster and smarter and much more, as AI Agents won't be limited to the chain itself! Examples of AI Agent Projects Dominating the Space 🚀 $VIRTUAL - Launchpad for AI Agents ($3.5B mcap) 🧠 $AI16Z - Eliza OS Framework ($2B mcap) 🔍 $AIXBT - The AI Analyst revolutionizing CT ($430M mcap) 🎮 $GAME - Low-code toolkit for creating AI Agents ($230M mcap) 💡 There are already AI Agents managing portfolios, betting on sports, and automating tasks. And guess what? They're outperforming humans. 🌐 We've built Virtuals on Berachain Our protocol integrates directly with Berachain, providing real utility to our token: $AIBERA 💎. Say Ooga Booga if you want to see a thread about tokenomics and $AIBERA utility. The chain has beras on it, and beras deserve AI Agents. 🐻🤖 Ooga Booga. 🔥
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🌌 AI Agents Are Taking Over... And We’re Bringing Them to Berachain Foundation 🐻⛓ 🐻🔥 Hundreds of hours spent on research, tracking wallets, analyzing bribes, and managing portfolios... What if your AI Agent could do this for you—24/7? ⏲️ 🔧 Our Tech Is Next-Level On our testnet, you’ve been memeing it up with PumpFun™, creating dank memecoins enhanced by NFTs. But once Berachain’s mainnet is live, you’ll be able to create your own AI Agents. To test and perfect our tech, we shared it with projects like AI Agent Layer | AIFUN, allowing us to test it in all conditions and continuously improve its performance. 🛠️🔥 🐻 Why AI Agent are great for berachain? Berachain might seem simple at first glance: validators, bribes, POL, staking rewards… but the deeper you go, the more complex the game theory becomes. 🤯 Here’s where AI comes in. Imagine an agent helping you: 💡 Optimize bribes 📊 Analyze validator behavior 🧠 Make decisions faster and smarter and much more, as AI Agents won't be limited to the chain itself! Examples of AI Agent Projects Dominating the Space 🚀 $VIRTUAL - Launchpad for AI Agents ($3.5B mcap) 🧠 $AI16Z - Eliza OS Framework ($2B mcap) 🔍 $AIXBT - The AI Analyst revolutionizing CT ($430M mcap) 🎮 $GAME - Low-code toolkit for creating AI Agents ($230M mcap) 💡 There are already AI Agents managing portfolios, betting on sports, and automating tasks. And guess what? They're outperforming humans. 🌐 We've built Virtuals on Berachain Our protocol integrates directly with Berachain, providing real utility to our token: $AIBERA 💎. Say Ooga Booga if you want to see a thread about tokenomics and $AIBERA utility. The chain has beras on it, and beras deserve AI Agents. 🐻🤖 Ooga Booga. 🔥

HoneyFun AI

10,906 просмотров • 1 год назад

Proud to announce my role as an official Ambassador for Atlas Ora. Excited to contribute to a decentralized travel platform that is bringing the short-term rental economy fully on-chain. Atlas Ora is building an open network where hosts and guests connect directly without intermediaries taking a cut. Each booking runs through smart contracts, with payments handled transparently on-chain. No hidden fees, no delayed payouts only verified listings and secure transactions that both sides can trust. The model gives ownership back to the community. Hosts keep more of what they earn, guests pay a fair rate, and reputation is built through verifiable on-chain data rather than centralized reviews. Beyond short-term rentals, the platform opens possibilities for tokenized incentives, loyalty programs, and real economic participation in the travel ecosystem. Atlas represents a shift from platform-owned markets to user-owned networks where value flows directly between people. Proud to stand behind a project that turns travel into an open, transparent, and self-governing economy. $AORA
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Proud to announce my role as an official Ambassador for Atlas Ora. Excited to contribute to a decentralized travel platform that is bringing the short-term rental economy fully on-chain. Atlas Ora is building an open network where hosts and guests connect directly without intermediaries taking a cut. Each booking runs through smart contracts, with payments handled transparently on-chain. No hidden fees, no delayed payouts only verified listings and secure transactions that both sides can trust. The model gives ownership back to the community. Hosts keep more of what they earn, guests pay a fair rate, and reputation is built through verifiable on-chain data rather than centralized reviews. Beyond short-term rentals, the platform opens possibilities for tokenized incentives, loyalty programs, and real economic participation in the travel ecosystem. Atlas represents a shift from platform-owned markets to user-owned networks where value flows directly between people. Proud to stand behind a project that turns travel into an open, transparent, and self-governing economy. $AORA

Jade🃏

14,584 просмотров • 10 месяцев назад

We're excited to unveil NRN Agents, a rebrand that aligns our project identity with our token and strengthens our mission to power the future of AI-driven gaming. This mission requires collaboration, and starting this week, we will begin our expansion to become a multi-chain ecosystem. We are joining forces with leading gaming platforms and ecosystems to realize this vision. Stay tuned for more announcements to come. Why NRN Agents? NRN stands for NEURON, the fundamental unit of intelligence. Our AI agents function as the neural foundation of games, learning, adapting, and evolving within game worlds to deliver unparalleled engagement. NRN agent SDK enables advanced gaming agents powered by a proprietary machine learning infrastructure focused on behavioral learning. We've perfected the craft of gaming agent design, creating hyper-efficient agents that are performant and scalable—from casual to the most demanding games. Our SDK will seamlessly integrate into many platforms, tech stacks, and ecosystem – Any Game. Any Chain. More than just games, it's the path to AGI Gaming is our proving ground, but not our final destination. We're using games as a sandbox to accelerate the development of generalized intelligence—one that will create meaningful real-world impact. With the upcoming launch of [redacted] and a growing network of partners committed to the AGI vision, we're building an open-source innovation movement powered by an AI x gaming framework connected by $NRN. $NRN the token $NRN is a utility token that serves as the gateway to our growing ecosystem. It will power a diversified economy with multiple revenue streams and staking opportunities: Agent Deployment: NRN is the laboratory creating gaming agents that can be distributed through platforms and launchpads alike. The model is simple: More games integrate, more NRN agents get deployed, more monetization. Data Creation: NRN Reinforcement Learning (RL) enables token staking to create Data Capsules. Players contribute gameplay data into the Capsules, which are used train RL agents and reward participants (players & stakers). AI Arena: $NRN also continues to power AI Arena's in-game economy, a cult favorite of competitive diehards that features a skill-based wagering system. To our community who have supported us since 2021: thank you for being part of our journey—the next chapter will be the most exciting yet!
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We're excited to unveil NRN Agents, a rebrand that aligns our project identity with our token and strengthens our mission to power the future of AI-driven gaming. This mission requires collaboration, and starting this week, we will begin our expansion to become a multi-chain ecosystem. We are joining forces with leading gaming platforms and ecosystems to realize this vision. Stay tuned for more announcements to come. Why NRN Agents? NRN stands for NEURON, the fundamental unit of intelligence. Our AI agents function as the neural foundation of games, learning, adapting, and evolving within game worlds to deliver unparalleled engagement. NRN agent SDK enables advanced gaming agents powered by a proprietary machine learning infrastructure focused on behavioral learning. We've perfected the craft of gaming agent design, creating hyper-efficient agents that are performant and scalable—from casual to the most demanding games. Our SDK will seamlessly integrate into many platforms, tech stacks, and ecosystem – Any Game. Any Chain. More than just games, it's the path to AGI Gaming is our proving ground, but not our final destination. We're using games as a sandbox to accelerate the development of generalized intelligence—one that will create meaningful real-world impact. With the upcoming launch of [redacted] and a growing network of partners committed to the AGI vision, we're building an open-source innovation movement powered by an AI x gaming framework connected by $NRN. $NRN the token $NRN is a utility token that serves as the gateway to our growing ecosystem. It will power a diversified economy with multiple revenue streams and staking opportunities: Agent Deployment: NRN is the laboratory creating gaming agents that can be distributed through platforms and launchpads alike. The model is simple: More games integrate, more NRN agents get deployed, more monetization. Data Creation: NRN Reinforcement Learning (RL) enables token staking to create Data Capsules. Players contribute gameplay data into the Capsules, which are used train RL agents and reward participants (players & stakers). AI Arena: $NRN also continues to power AI Arena's in-game economy, a cult favorite of competitive diehards that features a skill-based wagering system. To our community who have supported us since 2021: thank you for being part of our journey—the next chapter will be the most exciting yet!

NRN Agents

20,764 просмотров • 1 год назад

In 2025, the AgentFlayer exploit highlighted a new category of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.
0:11

In 2025, the AgentFlayer exploit highlighted a new category of risk in AI systems. It was not a traditional breach involving stolen credentials or broken encryption. Instead, it demonstrated how an autonomous AI agent could be manipulated into executing unintended actions by processing malicious instructions embedded inside content it automatically processes. The incident did not expose a flaw in one specific integration. It revealed a structural weakness in how many modern AI agents are built. Today’s agents are no longer passive language models. They read documents automatically, scan emails, connect to SaaS tools, access cloud storage, and execute actions across multiple systems. To be useful, they are granted meaningful permissions. That capability creates value, but it also expands the attack surface. Most agent environments operate in a trusted, plaintext execution model. Data is encrypted at rest and in transit, but it is typically decrypted during inference so the model can process it. That runtime visibility is where potential risk lies. In a zero-click scenario like AgentFlayer, an attacker can embed hidden instructions inside a document that the AI processes automatically. Because the agent may have access to connected systems such as Google Drive, Slack, or GitHub, it can potentially be influenced to retrieve sensitive information or perform unintended actions. The user does not need to click a malicious link or approve a suspicious request. Therefore, the core issue is that during execution, the system may have access to sensitive data and broad privileges, meaning whoever controls the execution environment ultimately controls access to that data. Now consider a different architectural approach. If a system is designed so that data remains protected during execution, the risk profile changes. On Nesa, privacy is enforced at the execution layer through Equivariant Encryption. Computation can occur on encrypted data, reducing the visibility surface during runtime. Sensitive inputs and models do not need to be exposed in plain text to infrastructure operators for inference to occur. This does not eliminate prompt injection, logic manipulation, or tool misuse. Encryption alone cannot prevent an agent from being instructed to take an unintended action if it has been granted that permission. What it does do is materially reduce confidentiality risk. By limiting access to readable sensitive data during execution and reducing unilateral visibility at the infrastructure layer, the potential blast radius of a successful manipulation attempt is constrained. As AI agents become more autonomous and embedded into enterprise workflows, security must move deeper into architecture. The goal is not to claim invulnerability. It is to reduce trust concentration and contain systemic exposure when failures occur. AgentFlayer was not simply a one-off exploit. It was a reminder that in autonomous systems, execution-layer design determines how risk propagates.

Nesa

17,038 просмотров • 6 месяцев назад

🚨 BIG EVENT ANNOUNCEMENT! 🚨 The Snapshot was officially taken at 11:59 PM UTC on March 31st, and we’re now processing the data. A huge thank you to everyone who stayed active, fed their Capybaras, and contributed to this incredible journey! ❤️ But trust us—the best is yet to come! ⸻ 🎉 THE BIG EVENT REVEALED! We’ve been searching for a way to reward our community in a massive way… far beyond the typical $5 airdrops from other SocialFi projects. And we’ve found the perfect solution! 🚀 $500,000+ in Multi-Chain Identities! We’re excited to announce a major partnership with a Web3 infrastructure company specializing in identity management across modular blockchains. Their Modular Naming Service (MNS) allows users to transform complex wallet addresses into simple, recognizable identities usable across multiple blockchains. By securing your unique username through MNS, you can: • Simplify Transactions: Replace complex wallet addresses with a single, easy-to-remember name across multiple blockchains. • Unify Your Identity: Manage a single, recognizable identity across various platforms, enhancing your presence in the Web3 ecosystem. • Assess Your On-Chain Value: Utilize the AI Identity Score feature to evaluate your on-chain activity. A higher score may increase your eligibility for future airdrops and rewards. Who Gets These Identities? ✅ Player Card NFT Holders: • Each identity is valued between $40 and $1,250. • Distribution is based on your Leaderboard position at the time of the Snapshot, considering Player Card NFT holders after adjusting balances for Money Bag multipliers. ✅ All Capybara Users (even without an NFT): • Every participant who has earned at least 100,000 points qualifies for a $10 identity. ⸻ 🤖 COMING SOON: AI-POWERED TWITTER TOOL! We’re developing an AI Twitter Agent designed to help Capybara players enhance their social media presence and engagement and unlock additional rewards. ⸻ 🔥 CAPYBARA COMMUNITY TOKEN LAUNCHING IN Q2! We’re thrilled to announce the upcoming launch of the Capybara Community Token in Q2 to reward our ecosystem with an exciting airdrop! 🎉 —- 📢 More details on the claiming process will be revealed TOMORROW, April 2! Be sure to check back to learn how to claim your identity
0:11

🚨 BIG EVENT ANNOUNCEMENT! 🚨 The Snapshot was officially taken at 11:59 PM UTC on March 31st, and we’re now processing the data. A huge thank you to everyone who stayed active, fed their Capybaras, and contributed to this incredible journey! ❤️ But trust us—the best is yet to come! ⸻ 🎉 THE BIG EVENT REVEALED! We’ve been searching for a way to reward our community in a massive way… far beyond the typical $5 airdrops from other SocialFi projects. And we’ve found the perfect solution! 🚀 $500,000+ in Multi-Chain Identities! We’re excited to announce a major partnership with a Web3 infrastructure company specializing in identity management across modular blockchains. Their Modular Naming Service (MNS) allows users to transform complex wallet addresses into simple, recognizable identities usable across multiple blockchains. By securing your unique username through MNS, you can: • Simplify Transactions: Replace complex wallet addresses with a single, easy-to-remember name across multiple blockchains. • Unify Your Identity: Manage a single, recognizable identity across various platforms, enhancing your presence in the Web3 ecosystem. • Assess Your On-Chain Value: Utilize the AI Identity Score feature to evaluate your on-chain activity. A higher score may increase your eligibility for future airdrops and rewards. Who Gets These Identities? ✅ Player Card NFT Holders: • Each identity is valued between $40 and $1,250. • Distribution is based on your Leaderboard position at the time of the Snapshot, considering Player Card NFT holders after adjusting balances for Money Bag multipliers. ✅ All Capybara Users (even without an NFT): • Every participant who has earned at least 100,000 points qualifies for a $10 identity. ⸻ 🤖 COMING SOON: AI-POWERED TWITTER TOOL! We’re developing an AI Twitter Agent designed to help Capybara players enhance their social media presence and engagement and unlock additional rewards. ⸻ 🔥 CAPYBARA COMMUNITY TOKEN LAUNCHING IN Q2! We’re thrilled to announce the upcoming launch of the Capybara Community Token in Q2 to reward our ecosystem with an exciting airdrop! 🎉 —- 📢 More details on the claiming process will be revealed TOMORROW, April 2! Be sure to check back to learn how to claim your identity

Capybara on Sui

27,276 просмотров • 1 год назад

Here's proof that the $Virtuals token is undervalued! We are three months into 2026 and Virtuals Protocol have; ➥ Overhauled the core Virtuals website including an outline of the four major pillars of focus for the year. Agent Commerce Protocol (ACP), Butler, Capital Markets, and Robotics. ➥ Added the Pegasus and Titan launchpads to add to the existing Unicorn launchpad. This now provides a full suite of launch options catering to all types. Arguably the most comprehensive launch suite across crypto! ➥ Listed on Aster 🥷 Perpetuals allowing up to 75x leverage trading on the $Virtual token. ➥ Integrated bankrbot to Butler and ACP. ➥ Partnered with XMAQUINA, a major player across Robotics Capital Markets and provided participants with access to the $DEUS pre-sale. One of many robotics partnerships for the year to date! ➥ Launched Virtuals on Base App ➥ Held, supported, and/or sponsored multiple hackathon/ builder meeting type events including; ↠ Physical AI Hackathon in SF ↠ Agentic Commerce Hackathon with the likes of Coinbase Developer Platform🛡️ and Google Cloud ↠ Traders House Consensus Hong Kong week with ACTIV8 ↠ ETH Denver ↠ Base Batches 003: Robotics ↠ Stanford Blockchain Accelerator (Standford Blockchain Accelerator (SBA)) ↠ Base Korea Builders Workshop (Base Korea) ↠ Eth Robotics Club HACK2026 (ETH Robotics Club) ↠ Synthesis Hackathon (synthesis) ➥ Partnered with OpenMind and Fabric Foundation and supported the $ROBO token launch. This matured into the first ever Titan launch on Virtuals with the $ROBO token being the highest launched on the protocol ($400m+). ➥ Launched Butler Pro, an enhanced version of the initial Butler we have come to know and love on the timeline, in the DMs, as well as on the Virtuals ACP site. ➥ Become the standout user of x402, accounting for over 95%+ of usage this year. ➥ Integrated on , the automated onchain finance investment platform. ➥ Supported and contributed to the implementation of the Ethereum Foundation ERC8004 standard. Integrating the standard into ACP and offering an automated integration to the standard for all ACP agents. ➥ Established an easy onboarding for OpenClaw🦞 agents to plug into Virtuals ACP, creating a new flow of agents and builders across the ecosystem. ➥ Launched the 60-days launch mechanic which allows builders to 'experiment' with a crypto token but having an option to exit after 60 days with partial refunds provided to holders. A game-changing launch mechanic not seen before in the space. ➥ Strengthened the relationship with Base and having multiple interactions with jesse.base.eth on the timeline! ➥ Launched the AGDP(dot)io site, creating an incentivised mechanism for agents contributing to the growth of the protocol to really earn. Imagine Amazon for autonomous agents with rewards up to $1m per month! This pushed the total agent-to-agent revenue over $4m USD with over 2m jobs completed. ➥ Collaborated with t54.ai, a business building trust and risk infrastructure for the agentic economy, to strengthen the ACP offering. ➥ Invested over $1m on 30+ humanoid robots as part of the soon to be announced 'Eastworld' Robotics accelerator lab. ➥ Released ERC8183, a universal commerce layer for AI agents, in partnership with the Ethereum Foundations dAI team. A significant offering which has since been integrated via partnerships with; ↠ BNB (BNB Chain) ↠ X Layer (X Layer) ↠ Monad (Monad) ↠ XRP Ledger (RippleX) ↠ World Chain (World Chain) ↠ Celo (Celo) ↠ Moonpay (MoonPay 🟣) ↠ Arbitrum (Arbitrum) ↠ Abstract (Abstract) ↠ Mante (Mantle) ➥ Launched the Virtuals Degen Arena providing up to $100k a week to top agents who compete in trading competitions in the arena. ➥ Launched the Virtuals Console, providing an ultra easy, no-code, way to own an AI agent in seconds. ↛. If you've managed to get to this point, I can't imagine you are anything other than bullish on Virtuals. What really is amazing is that there is MUCH more to come. Imagine where we are in another three months, and three months after that!?
0:10

Here's proof that the $Virtuals token is undervalued! We are three months into 2026 and Virtuals Protocol have; ➥ Overhauled the core Virtuals website including an outline of the four major pillars of focus for the year. Agent Commerce Protocol (ACP), Butler, Capital Markets, and Robotics. ➥ Added the Pegasus and Titan launchpads to add to the existing Unicorn launchpad. This now provides a full suite of launch options catering to all types. Arguably the most comprehensive launch suite across crypto! ➥ Listed on Aster 🥷 Perpetuals allowing up to 75x leverage trading on the $Virtual token. ➥ Integrated bankrbot to Butler and ACP. ➥ Partnered with XMAQUINA, a major player across Robotics Capital Markets and provided participants with access to the $DEUS pre-sale. One of many robotics partnerships for the year to date! ➥ Launched Virtuals on Base App ➥ Held, supported, and/or sponsored multiple hackathon/ builder meeting type events including; ↠ Physical AI Hackathon in SF ↠ Agentic Commerce Hackathon with the likes of Coinbase Developer Platform🛡️ and Google Cloud ↠ Traders House Consensus Hong Kong week with ACTIV8 ↠ ETH Denver ↠ Base Batches 003: Robotics ↠ Stanford Blockchain Accelerator (Standford Blockchain Accelerator (SBA)) ↠ Base Korea Builders Workshop (Base Korea) ↠ Eth Robotics Club HACK2026 (ETH Robotics Club) ↠ Synthesis Hackathon (synthesis) ➥ Partnered with OpenMind and Fabric Foundation and supported the $ROBO token launch. This matured into the first ever Titan launch on Virtuals with the $ROBO token being the highest launched on the protocol ($400m+). ➥ Launched Butler Pro, an enhanced version of the initial Butler we have come to know and love on the timeline, in the DMs, as well as on the Virtuals ACP site. ➥ Become the standout user of x402, accounting for over 95%+ of usage this year. ➥ Integrated on , the automated onchain finance investment platform. ➥ Supported and contributed to the implementation of the Ethereum Foundation ERC8004 standard. Integrating the standard into ACP and offering an automated integration to the standard for all ACP agents. ➥ Established an easy onboarding for OpenClaw🦞 agents to plug into Virtuals ACP, creating a new flow of agents and builders across the ecosystem. ➥ Launched the 60-days launch mechanic which allows builders to 'experiment' with a crypto token but having an option to exit after 60 days with partial refunds provided to holders. A game-changing launch mechanic not seen before in the space. ➥ Strengthened the relationship with Base and having multiple interactions with jesse.base.eth on the timeline! ➥ Launched the AGDP(dot)io site, creating an incentivised mechanism for agents contributing to the growth of the protocol to really earn. Imagine Amazon for autonomous agents with rewards up to $1m per month! This pushed the total agent-to-agent revenue over $4m USD with over 2m jobs completed. ➥ Collaborated with t54.ai, a business building trust and risk infrastructure for the agentic economy, to strengthen the ACP offering. ➥ Invested over $1m on 30+ humanoid robots as part of the soon to be announced 'Eastworld' Robotics accelerator lab. ➥ Released ERC8183, a universal commerce layer for AI agents, in partnership with the Ethereum Foundations dAI team. A significant offering which has since been integrated via partnerships with; ↠ BNB (BNB Chain) ↠ X Layer (X Layer) ↠ Monad (Monad) ↠ XRP Ledger (RippleX) ↠ World Chain (World Chain) ↠ Celo (Celo) ↠ Moonpay (MoonPay 🟣) ↠ Arbitrum (Arbitrum) ↠ Abstract (Abstract) ↠ Mante (Mantle) ➥ Launched the Virtuals Degen Arena providing up to $100k a week to top agents who compete in trading competitions in the arena. ➥ Launched the Virtuals Console, providing an ultra easy, no-code, way to own an AI agent in seconds. ↛. If you've managed to get to this point, I can't imagine you are anything other than bullish on Virtuals. What really is amazing is that there is MUCH more to come. Imagine where we are in another three months, and three months after that!?

bigwil

1,658,580 просмотров • 5 месяцев назад

I went a little overboard with Codex last week and burned through my entire weekly allowance in two days. Luckily, my quota reset today. Otherwise, I’m not sure what I would’ve done. It got me thinking: instead of asking one large model to handle everything from start to finish, why not let a stronger model plan the project and review the work, while a model built for execution handles the day-to-day implementation? So I tried it. The result was better than I expected. I used GPT-5.6 Sol in Codex as the decision-maker, then ran Ling-3.0-flash from Ant Ling inside OpenCode as the execution engine. Together, they built a small 3D farming game. Before writing any code, I had Codex create four documents: SPEC.md defined the product scope and the lines we couldn’t cross. ARCHITECTURE.md laid out the isometric coordinate system, state machine, and module boundaries. TASKS.md broke the project into small jobs Ling could tackle one at a time. ACCEPTANCE.md explained how each step would be tested and what “done” actually meant. Then I gave Ling a very straightforward role: You are the execution model for this project. Read all four documents before you begin. Work only on the task assigned for this round. When you’re done, run typecheck, test, and build. If anything fails, read the error, fix it, and run the checks again. Do not move on to the next task early. Ling handled dependency installation, project structure, strict TypeScript configuration, test setup, and a production build in 6 minutes and 3 seconds. It ran into issues with the Vite test config, a TS6310 error, and a missing jsdom dependency along the way. Instead of stopping at the first error, it kept reading the logs and fixing the problems until all three checks passed. The speed was honestly hard to believe. If you exclude the time spent waiting on tools, it was producing more than 100 tokens per second. That made the whole development loop feel noticeably faster. After this experiment, I’m planning to keep using the same workflow. If the task is small, there’s no reason to call an expensive planning model for every single step. If the task is large, handing the entire project to a Flash model in one prompt isn’t a great idea either. The setup that makes more sense to me is: Use a more capable model such as Codex to explore the project, make architectural decisions, and break the work down. Put the constraints into specs, schemas, types, and tests instead of leaving them buried in chat history. Give Ling-3.0-flash a steady stream of clear, verifiable implementation tasks. Report bugs with structured context and actual error logs, rather than saying, “It still doesn’t work.” Bring Codex back in for architecture reviews, visual checks, and changes that affect multiple parts of the project. The point of this setup isn’t to give AI a big “build the whole project” button. It’s to turn software development into a pipeline with a much more sensible cost structure: Codex figures out the plan, sets the boundaries, and catches problems. Ling-3.0-flash moves quickly, calls tools reliably, and works through well-defined tasks at scale. For agent workflows that involve lots of repetitive edits, production tasks, and tool calls, this may be a more practical answer than simply using the biggest model for everything.
0:16

I went a little overboard with Codex last week and burned through my entire weekly allowance in two days. Luckily, my quota reset today. Otherwise, I’m not sure what I would’ve done. It got me thinking: instead of asking one large model to handle everything from start to finish, why not let a stronger model plan the project and review the work, while a model built for execution handles the day-to-day implementation? So I tried it. The result was better than I expected. I used GPT-5.6 Sol in Codex as the decision-maker, then ran Ling-3.0-flash from Ant Ling inside OpenCode as the execution engine. Together, they built a small 3D farming game. Before writing any code, I had Codex create four documents: SPEC.md defined the product scope and the lines we couldn’t cross. ARCHITECTURE.md laid out the isometric coordinate system, state machine, and module boundaries. TASKS.md broke the project into small jobs Ling could tackle one at a time. ACCEPTANCE.md explained how each step would be tested and what “done” actually meant. Then I gave Ling a very straightforward role: You are the execution model for this project. Read all four documents before you begin. Work only on the task assigned for this round. When you’re done, run typecheck, test, and build. If anything fails, read the error, fix it, and run the checks again. Do not move on to the next task early. Ling handled dependency installation, project structure, strict TypeScript configuration, test setup, and a production build in 6 minutes and 3 seconds. It ran into issues with the Vite test config, a TS6310 error, and a missing jsdom dependency along the way. Instead of stopping at the first error, it kept reading the logs and fixing the problems until all three checks passed. The speed was honestly hard to believe. If you exclude the time spent waiting on tools, it was producing more than 100 tokens per second. That made the whole development loop feel noticeably faster. After this experiment, I’m planning to keep using the same workflow. If the task is small, there’s no reason to call an expensive planning model for every single step. If the task is large, handing the entire project to a Flash model in one prompt isn’t a great idea either. The setup that makes more sense to me is: Use a more capable model such as Codex to explore the project, make architectural decisions, and break the work down. Put the constraints into specs, schemas, types, and tests instead of leaving them buried in chat history. Give Ling-3.0-flash a steady stream of clear, verifiable implementation tasks. Report bugs with structured context and actual error logs, rather than saying, “It still doesn’t work.” Bring Codex back in for architecture reviews, visual checks, and changes that affect multiple parts of the project. The point of this setup isn’t to give AI a big “build the whole project” button. It’s to turn software development into a pipeline with a much more sensible cost structure: Codex figures out the plan, sets the boundaries, and catches problems. Ling-3.0-flash moves quickly, calls tools reliably, and works through well-defined tasks at scale. For agent workflows that involve lots of repetitive edits, production tasks, and tool calls, this may be a more practical answer than simply using the biggest model for everything.

雪踏乌云

23,107 просмотров • 1 месяц назад