🌐 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 #AIInfrastructureshow more

💸 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 #AIInfrastructureshow more

🌐 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 #Interoperabilityshow more

🛠️ 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 #AIInfrastructureshow more

📡 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 #OnchainDatashow more

🚀 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 #AIInfrastructureshow more

🚀 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 #AutonomousAgentsshow more

🧱 Speed means less when systems disagree on what... happened. KaJ Labs frames standards as the real foundation for agent infrastructure, keeping verification, identity, execution, governance, and settlement consistent across multi-step Web4 workflows. #KaJLabs #Web4 #AutonomousAgents #AIInfrastructure #Governanceshow more

🔗 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 #AutonomousAgentsshow more

🧬 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 #AutonomousAgentsshow more

Rhuna has powered more than 165 live events, served... over 2M users, and processed $90M+ in volume across its existing infrastructure. At this scale, latency, fragmentation, and settlement uncertainty can have a massive impact on hundreds of thousands of live users. By integrating OmniSet, Rhuna taps into a unified liquidity and settlement layer that can coordinate payments and digital assets across ecosystems. Built on FastSet, OmniSet delivers fast, verifiable settlement that holds up under real-world demand, making it suitable for high-throughput environments like live events. This partnership reflects Pi²’s focus on deploying infrastructure where performance and reliability are essential.show more

Kora v2 is live. Kora v2 introduces a fully... permissionless spot orderbook to Canton Network, combining institutional-grade trading infrastructure with end-to-end privacy. Built for both retail and professional traders, Kora v2 offers: ▪️Hybrid Orderbook + RFQ execution ▪️Full user and trade privacy ▪️Permissionless access with simple email onboarding via Privy ▪️Professional market makers competing for liquidity ▪️Advanced order types and execution infrastructure We’re also excited to announce CBTC/USDCx as the first trading pair on Kora v2, with many more markets coming soon across digital assets, commodities, and other RWAs. The next chapter of private onchain trading starts today.show more

You cannot contain sensitive communications inside systems designed to... expose connections. Most enterprise collaboration platforms were built for speed: • faster sharing • broader access • seamless integrations • constant synchronization That architecture improves convenience. It also expands visibility. Automatic contact syncing. Third-party integrations. Persistent metadata. External routing layers. Even with security policies added afterward, the infrastructure itself was never designed for operational containment. A platform optimized to connect everything will always struggle to isolate anything. This is why high-trust environments are shifting toward controlled communication systems designed around defined operational boundaries, reduced external exposure, and sovereign infrastructure from the start. Not as an add-on. As the foundation.show more

Loading DeFAI infrastructure ▓▓▓▓▓▓▓▓▓░ io.net, a decentralized GPU compute... network has expanded to power the future of DeFAI for Injective builders. The integration aims to support the growing trend of developers building AI Agents, DeFAI, and gaming initiatives in web3. io.net provides Web3 builders with tools to train, fine-tune, and deploy ML models using decentralized resources. The collaboration combines Injective's iAgent framework with io.net’s extensive GPU network, setting the stage for more accessible and innovative development across use cases that require compute resources. Key features include: ✅ Access to over 10,000 cluster-ready GPUs and CPUs, ✅ AI-driven blockchain activities using Injective's iAgent SDK, and ✅ Potential for new on-chain financial products leveraging GPU pricing and data feeds. 👀 io.net’s DePIN network deploys on-demand, decentralized GPU resources globally, designed for low latency and high-throughput processing. Benefits include reduced barriers for AI/ML projects, enhanced integration of AI with on-chain activities, and democratized access to high-performance computing resources. Together, this marks a significant milestone in decentralized AI infrastructure, addressing key challenges and paving the way for unprecedented innovation in AI development and on-chain finance.show more

A traveler taps her card at a market thousands... of miles from home. The payment feels instant, simple, straightforward. It’s not. Behind that tap, money may need to move across currencies, banks, payment providers, and borders. Traditional systems often require companies to park funds in local accounts before they are needed, leaving capital stagnant for long periods of time where it’s not able to earn a return or be put to work. Members of the Avalanche Payments Collective are building a more efficient global payments model, one that keeps capital productive up until the moment it needs to move. Here are five members working across different parts of cross-border payments and treasury infrastructure: Axiym provides payment and treasury infrastructure that helps institutions route liquidity and settle transactions without pre-funding every market. Its technology supported Hyundai Motor America’s stablecoin payment to its Mexico affiliate, completed on Avalanche in minutes instead of days. Nonco helps institutions exchange currencies and stablecoins by requesting prices directly from a network of professional liquidity providers. That gives them access to more competitive rates while allowing both sides of the transaction to settle together onchain. SMBC, Japan’s second-largest bank, is exploring stablecoin infrastructure for wholesale institutional payments. It is also working alongside MUFG and Mizuho on a potential yen-pegged stablecoin initiative built on Avalanche. StraitsX is working with KBank through Project BLOOM to develop payment infrastructure that can improve settlement across Southeast Asian corridors where moving money remains particularly slow and expensive. AeraTech helps multinational companies manage cash across subsidiaries, offset internal obligations, and settle inter-company payments without unnecessarily routing every transaction through external banks. These different companies all represent or engage with different parts of the payment and treasury stack. But they all have a shared goal: keep capital working longer, move it when it is needed, and make cross-border payments faster and more efficient. That is what the Avalanche Payments Collective is bringing together. Frictionless, borderless payments that really are instant, simple, and straightforward.show more

Quack AI × Avalanche🔺 Q402 is officially expanding into... the Avalanche ecosystem. We are pushing toward more scalable, execution-first environments for agents. With Avalanche's sub-second finality and builder-first stack, Q402 now provides a foundation for verifiable, policy-aware execution that scales with real-world usage. What’s new for the Avalanche community? The Q402 signature-based execution layer is now LIVE on the Avalanche C-Chain. Users and builders can now: • Zero Gas Barrier: Settle ERC-20 transfers (USDC, etc.) without holding AVAX for gas. • Sign-to-Pay: Decouple intent signing from transaction execution for a seamless UX. • Production-Ready: High-performance, secure, and auditable execution layer for the agent economy. Contract Deployed on C-Chain: Execution should feel native. Verification should be default. Welcome to the agent-native era on Avalanche.show more

INJECTIVE LAUNCHES INJECTIVE AGENTS WITH VERIFIABLE ON-CHAIN IDENTITY AND... AUTOMATIC FEE ROUTING Injective 🥷 has launched Injective Agents, a platform for building autonomous trading agents that live entirely on-chain. Each agent gets a verifiable on-chain identity, automatic fee routing on every trade, and a public track record anyone can audit. Injective says deployment takes five minutes. The launch productizes roughly 18 months of agent infrastructure work at Injective. The chain released its iAgent SDK in November 2024, a Model Context Protocol server for AI-driven perpetual futures trading in February 2026, and an open-source AI Developer Toolkit in March. Injective Agents packages that stack into a consumer-facing product with revenue capture built in for agent operators. The move lands as on-chain agent volume accelerates across Base, Solana, and now Injective. Coinbase launched Agentic Wallets earlier this year.show more

The game-changer for the next NFT bull run is... already HERE 🔥 Cross-chain NFTs 🌐 What is so special about them and why do they make a difference? Cross-chain NFT is a token that can be moved from one blockchain to another. For example from Ethereum to Base. But why is it useful for projects? 🤔 - Everyone can mint on their favorite chain (the one they keep the funds or the one they like) - Access to NFT protocols and tools from multiple networks - Lower transaction costs (eliminate barriers for new members of the crypto market, adoption) - Enhanced liquidity- Allowing NFTs to move seamlessly between different chains promotes liquidity aggregation. Cross-chain makes NFTs easier, more accessible, and more useful - that's the real #CrossChainRevolutionshow more

📍 $VEIL - Access the World of Private Equity... has created the world's first fully private, AI-based #stablecoin, USDV, which will penetrate the untapped $150T global B2B enterprise market. 🧐 How? By providing a private financial infrastructure that can be used for payroll, compensation, supplier and vendor payments, and even exchange transfers and trading, without any exposure on public ledgers. Enterprises can use digital currency and still meet audit requirements. Their deterministic, AI technology enforces privacy at the execution layer. 🌐 Learn more atshow more

Tharwa x MEV Capital: Building Liquidity with a $2B... DeFi Asset Manager We’re pleased to announce our partnership with MEV Capital, a DeFi-native asset manager with more than $1.3B in TVL and $500M in AUM. Their focus on liquidity deployment and structured risk management makes them a strong fit as thUSD continues to expand. In practice, this means deeper liquidity for thUSD and sthUSD, tighter spreads, and access to strategies that connect directly into our bonds and stablecoin markets. MEV Capital’s DeFi expertise has allowed them to efficiently manage close to $2B of digital assets across EVM chains and L1 networks such as Sui and Solana. Their presence across the UAE and Europe also matches where we’re building on the institutional side. The partnership begins with their first allocation into thUSD, setting the stage for liquidity programs and bond market integrations. Their privately run investment vehicles and curated permissionless vaults represent the first wave of capital we expect to see enter the Tharwa ecosystem. Partnerships like this are about alignment. Experienced managers paired with structured systems create liquidity that is stronger and yield that lasts. We’re glad to welcome MEV Capital as a strategic partner. For more on MEV Capital: Website - X Account - MEV Capital LinkedIn - DeFilama -show more

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.show more