Stablecoins are the fuel for AI agents. AI won't stop at generating text and images — it will pay, execute, and coordinate. All of that requires a currency system that can settle autonomously on-chain. Dollar-backed stablecoins might become the first currency massively adopted by AI. The next big narrative: Stablecoin x Autonomous Agents.

Bitcoin just hit a new all-time high — congratulations to all holders.Meanwhile, $ASI is also showing strong momentum. The AI narrative is heating up. https://t.co/BvSVeW2G8t

Good morning

AI agents are evolving fast — from simple task runners to autonomous decision-makers. In crypto, they’re already watching wallets, claiming airdrops, sniping mints, and automating entire growth loops. This isn’t theory. It’s happening. Those who build or adopt early will win.

ChatGPT’s revolutionary shopping feature is live! Smarter recommendations, stunning visuals, transparent pricing, authentic reviews, and direct purchase links—powered by independent algorithms and 100% ad-free. AI is changing the way we shop. Now imagine this experience supercharged by Web3: Seamless crypto payments, decentralized marketplaces, and blockchain-powered trust are redefining the future of e-commerce. The future is here—and it’s open, smart, and decentralized.

🚀🚀🚀

NEAR is a legend.

TOP WEEKLY CRYPTO GAINERS 🔹 Core +29.05% $CORE 🔹 Bittensor +24.18% $TAO 🔹 ASI Alliance +18.80% $FET 🔹 Hyperliquid +12.78% $HYPE 🔹 Render +11.43% $RENDER 🔹 Immutable +10.90% $IMX 🔹 Raydium +10.51% $RAY 🔹 Decentraland +7.37% $MANA

User-owned AI = User success & outcome > maximizing corporate revenue and profit. Good one!

Orchestrated AI isn’t a future vision: it’s a present imperative 🧠 As the complexity of our systems accelerates, intelligence can no longer live in isolation. To stay relevant, it must be modular, adaptable, and able to coordinate fluidly across diverse environments. That’s why Axone and ASI are converging. We’re not just building infrastructure; we’re crafting the foundation for a new kind of intelligence: one that’s networked, verifiable, and rooted in human and planetary values 🌍 At the core of what we’re building: · We provide cognition — hybrid architectures that combine logic and pattern recognition · We enable orchestration — decentralized coordination across agents, chains, and services · We prioritize trust — reasoning and verifiability are built-in, not bolted on This isn’t about bigger models or faster chips. It’s about designing systems that evolve, collaborate, and self-govern—without centralized choke points or black-box control 🛠️ We’re not building AI that just responds—we’re building AI that participates. Systems that explain themselves, coordinate seamlessly, and adapt in real time—while staying transparent and autonomous. Axone x ASI is a programmable substrate for agentic, decentralized intelligence. Where agents aren’t just code—they’re actors in living, modular ecosystems 🧬 If you believe the future of AI should be open, auditable, and collective—this is your stack. 🧰 Let’s build it together: https://t.co/Uq8pE2UR1n

AI Agents aren't just your new employees—they're your future DAO contributors. Imagine an AI that: • Joins your DAO • Completes on-chain tasks • Earns tokens • Builds reputation Web3 gives AI agents a passport, a wallet, and a reason to work. This is just the beginning.

Good morning

Huge milestone for NEAR! Global contract code is a game changer — making common contract deployment 100x cheaper is massive. This unlocks real scalability for devs. And 600ms block time? UX just leveled up.

🚀 What if we build a crypto-native https://t.co/pnmdEi4Ucj? Check these user cases: 1⃣ DeFi Farmer Bot Auto-optimize yield strategies across 10+ protocols 💸 2⃣ Contract Guardian Real-time audit & vulnerability alerts for smart contracts 🛡 3⃣ Cross-Chain Conductor One-click asset routing (ETH↔SOL↔BTC) 🌉 Which use case excites you most?

The team has recently explored many new AI products and directions. Three thoughts on how to judge the value of AI products in the crypto field: 1. Does the product create value for users? (e.g., asset issuance or trading) 2. Can the product generate revenue? (Will users pay for it?) 3. Can the tokenomics capture the above two values? If these three conditions are not met, then deeper thinking and research are needed.

🚀

🚀 The evolution of LLM architecture will inevitably lead to MCP (Modularized-Composable-Parameters). Current limitations demand Web3-native solutions: 1. Outdated Knowledge: Massive training cycles trap models in the past. Web3 needs decentralized, real-time knowledge updates (think on-chain data streams). [4] 2. Overparameterization: Bloated models ≠ better UX. Modular design could enable task-specific parameter clusters (e.g. deploy only code-gen modules locally). [1] 3. Toxic Data Crawling: 74% of web content could become AI-hostile by 2026. Web3 needs: - Tokenized creator incentives - Verified data marketplaces - Anti-spam consensus mechanisms 4. Functional Limitations: Static APIs ≠ dynamic real-world ops. Imagine: - DAO-curated plugin registry - On-chain version control for APIs - Community-verified execution proofs The future lies in decomposing monolithic LLMs into interoperable modules with blockchain-based coordination. True progress isn't bigger models - it's creating incentive-aligned systems where humans and AI co-evolve.

🚀 Web3 AI Agents aren't just about multi-agent coordination & tokenomics. Real innovation lies in blockchain-native solutions: 1/ Decentralized Identity (DID) System → Agent-specific addresses for permanent state tracking (like smart contract addresses) 2/ AI-Optimized Oracle Network → Multi-layer architecture for trusted off-chain data + on-chain verification → Combines data collection, consensus, & execution layers 3/ Storage DA Layer → Records LLM knowledge states & reasoning paths → Cost-effective data availability proofs for validation 4/ ZK-Powered Privacy Layer → Hybrid approach with TEE/FHE integration → Enables medical/financial data usage while preserving privacy 5/ Cross-Chain Interoperability → Agent-specific relay networks → Syncs complex states (prompts/memories) across chains Key challenge: Aligning AI workflows with blockchain's trust architecture. The real battleground isn't replicating Web2 models - it's building new verification primitives that make decentralized AI agents truly trustless and composable.

Congrats to the winners 😀

Anthropic's Model Context Protocol (MCP) is simplifying how AI interacts with blockchains. Here’s why it matters:Universal Bridge: Lets AI tools connect to any blockchain/data source through a single interface (no custom coding)Auto-Pilot for DeFi: Set up rules like "Sell ETH if BTC drops 10% in 24h" using plain EnglishLiving NFTs: Your digital art can now update itself based on real-world events (e.g. weather/token price changes)DAO 2.0: AI assistants draft proposals, analyze voter patterns, and even execute approved actionsThis isn’t just another protocol – it’s the missing layer for an AI-native Web3 ecosystem.#Web3 #AI #Blockchain