# Identity Articoli collegati

Il Centro Notizie HTX fornisce gli articoli più recenti e le analisi più approfondite su "Identity", coprendo tendenze di mercato, aggiornamenti sui progetti, sviluppi tecnologici e politiche normative nel settore crypto.

AI Agents Are Starting to Register Email Accounts Themselves: This YC-Backed Company Raised $6 Million to Do Just One Thing

AI agents are now autonomously registering email accounts through AgentMail, a San Francisco-based startup that recently secured $6 million in seed funding. The company, backed by General Catalyst, Y Combinator, and prominent angels, is building email infrastructure specifically designed for AI agents—not humans. Unlike traditional email services, AgentMail provides API-first access, allowing AI agents to programmatically create accounts, send/receive emails, manage threads, and handle authentication without human intervention. This addresses a critical gap: while AI agents can perform complex tasks, they lack the identity layer (email) required to interact with most internet services. Key capabilities enabled by AgentMail include third-party authentication, bidirectional communication, automated audit trails, and multi-threaded conversations. The platform already serves thousands of human users and hundreds of thousands of AI agents, with use cases spanning supply chain coordination, customer support, loan collection, and procurement negotiations. Notably, AI agents are proactively seeking out and registering for AgentMail themselves—a sign of growing autonomy. This shift underscores a broader trend: AI agents are evolving from tools into active internet participants, necessitating new infrastructure tailored to their needs. As Box CEO Aaron Levie predicts, AI agents will soon become the primary users of software, vastly outnumbering human users in enterprises. AgentMail’s vision positions email as the foundational identity layer for this agent-centric future.

marsbit03/13 07:06

AI Agents Are Starting to Register Email Accounts Themselves: This YC-Backed Company Raised $6 Million to Do Just One Thing

marsbit03/13 07:06

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

Interview with FinAI: Pioneering Order in the Age of Agent Economy AI is rapidly evolving from "tool-based intelligence" to "autonomous intelligence." While tools like ChatGPT amazed us just two years ago, agents like OpenClaw can now independently perform complex real-world tasks. As AI transitions from a "human assistant" to an "autonomous participant" in economic activities, a new challenge arises: how to establish economic rules among AI agents. FinAI, a startup founded by veterans from top tech firms, is addressing this by building financial infrastructure for AI agents based on Web3 technologies like x402 and ERC-8004. Their solution focuses on three core pillars: - **Payment Capability**: Enabling microsecond-level payments between agents via the x402 protocol to complete economic transactions autonomously. - **Identity System**: Introducing KYA (Know Your Agent), a verifiable identity framework similar to KYC, to ensure compliance and security. - **Credit System**: Establishing a trust-based reputation system using historical data like transaction quality and refund records. FinAI aims to offer these capabilities via APIs/Skills for both Web2 agent developers (via subscriptions) and Web3 users (through链上 integrations). The platform prioritizes Agent-friendly design, optimizing interfaces for seamless integration. With its first autonomous payment already processed in 2026, FinAI expects profitability within the year. By leveraging blockchain’s efficiency (e.g., near-instant settlements at 1/300 the cost of traditional systems) and addressing合规 concerns through KYA and quantum加密 wallets, FinAI positions itself as a first-mover in shaping the future of agent-to-agent economies.

marsbit03/12 11:45

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

marsbit03/12 11:45

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

Interview with FinAI: Pioneering Order in the Agent Economy Era AI is rapidly evolving from "tool-based intelligence" to "autonomous intelligence." While tools like ChatGPT impressed with dialogue just two years ago, agents like "Lobster" OpenClaw can now independently execute complex real-world tasks. This shift means AI's role in the economy is transitioning from a "human assistant" to an "autonomous participant." We will soon commonly see assistant agents handling chores, research agents finding financial opportunities, and commercial agents comparing global supplier quotes and placing orders—often transacting with other agents. A critical question emerges: How is economic order established among AI agents? FinAI, an AI startup with a team from major tech firms, argues that for an autonomous AI economy to function, agents need core infrastructural capabilities: payment ability, an identity system, and a credit system. Currently, most agents lack independent payment functionality; they can perform tasks but not finalize transactions. FinAI is building financial infrastructure for AI agents using Web3 technology stacks like x402 and ERC-8004. Their solution is threefold: 1. **Payment:** Utilizing the x402 protocol to enable microsecond-level payments between agents, creating a complete economic闭环 (closed loop). 2. **Identity:** Introducing a KYA (Know Your Agent) concept, akin to KYC, using ERC-8004 to provide agents with verifiable, compliant identities. 3. **Credit:** Establishing a reputation system based on agents' transaction history and task performance to serve as a trust foundation for future AI经济活动 (economic activities). These capabilities will be packaged into APIs/Skills for agents to调用 (call). FinAI's primary customers are Web2 agent application developers, who will pay via API subscriptions, and Web3 users, for whom agent skills will be integrated into various on-chain financial scenarios. The company plans to take a very low, friendly transaction fee on agent-to-agent tasks but does not intend to profit heavily from end-users, aiming instead to incubate a mature agent marketplace. FinAI chose Web3 infrastructure out of practical necessity. Traditional payment systems are too slow and expensive for the micro-payment demands of agent economies. Stablecoin-based settlements on-chain can complete transactions in seconds at a fraction of the cost (approximately 1/300th of traditional systems). While traditional clients have compliance and security concerns, FinAI addresses these with its full-stack capabilities, including identity gateways, payment systems, quantum-encrypted wallets, and its KYA framework. Founded in August 2025, FinAI has progressed rapidly, completing its first autonomous payment order in 2026 and expecting to be profitable within the year. Rechard, the founder, believes the key competitive advantage in this nascent field is being the first to establish a complete, operational system. Furthermore, FinAI is designing its services to be "Agent-friendly"—optimizing its APIs and interfaces for agents, the primary decision-makers who will automatically seek the most cost-effective and easiest-to-integrate services. Just as e-commerce spurred third-party payment and mobile internet spurred digital wallets, the rise of AI agents may催生 (give rise to) a new economic system. FinAI aims to be the pioneer building the foundational order for this new Agent-to-Agent economy.

Odaily星球日报03/12 11:32

Exclusive Interview with FinAI: Pioneering Order in the Era of Agent Economy

Odaily星球日报03/12 11:32

a16z: After AI Grants Humans Superpowers, Where Do We Go From Here?

A new paper titled "The Minimal Economics of AGI" explores the economic implications of AI automation, particularly as AI agents evolve from tools into collaborative partners capable of long-horizon tasks. The authors, Christian Catalini and Eddy Lazzarin, argue that the core economic divide will be between automation (tasks that can be measured and automated) and verification (tasks requiring human oversight, judgment, and contextual understanding). Key themes include: - The "coder’s curse": top experts training AI systems may inadvertently automate their own roles over time. - Three future human roles: directors (setting intent), verifiers (domain experts ensuring quality), and meaning-makers (creating cultural and social value). - Cryptocurrency and blockchain are positioned as critical for identity, provenance, and trust in a world flooded with AI-generated content. - Two potential economic outcomes: a "hollow economy" with systemic risk from under-verification, or an "augmented economy" where AI amplifies human potential and reduces costs for education, healthcare, and innovation. - The importance of small, agile teams leveraging AI for outsized impact, with crypto infrastructure enabling coordination at scale. The authors emphasize that AI acts as a force multiplier, granting individuals "superpowers," and urge a focus on verification, adaptability, and ambitious experimentation.

marsbit03/09 11:31

a16z: After AI Grants Humans Superpowers, Where Do We Go From Here?

marsbit03/09 11:31

Your AI Agent is Quietly Changing the Rules of the Internet

AI Agents are rapidly transforming the internet landscape, evolving from experimental tools to essential components in daily operations—managing emails, scheduling meetings, and handling support tickets. By 2025, automated traffic is projected to surpass human activity, accounting for 51% of all web traffic, with AI-driven visits to US retail sites surging by 4,700% year-over-year. However, confidence in fully autonomous agents has declined due to security concerns, as infrastructure struggles to keep pace with their expansion. Key challenges include discoverability—agents must efficiently find machine-readable services amidst web pages designed for humans, prompting a shift from SEO to Agent-Oriented Discoverability (AEO). Identity is critical: agents require cryptographic authentication, delegated authority, and real-world accountability to transact securely, leading to emerging standards like ERC-8004 and protocols such as Visa’s Trusted Agent Protocol. Finally, reputation systems are essential to verify agent performance through methods like trusted execution environments (TEEs), zero-knowledge machine learning (ZKML), and economic security models, enabling portable, auditable records of reliability. Together, discoverability, identity, and reputation form the foundational infrastructure for an agent-driven economy, ensuring agents can operate at scale with trust and autonomy.

比推03/05 19:13

Your AI Agent is Quietly Changing the Rules of the Internet

比推03/05 19:13

Building Trustless AI Agents: ERC-8004 Security Audit Guide

ERC-8004, the Trustless Agents standard deployed on Ethereum, introduces a verifiable and trust-minimized framework for AI Agent identity and reputation management through three core registries: Identity, Reputation, and Validation. The **Identity Registry** (ERC-721 based) mints a unique AgentID (an NFT) for each agent, with a `tokenURI` pointing to an off-chain registration file. This file contains the agent's basic info, service endpoints, and capabilities. A critical security feature is domain verification, requiring agents to host a signed file at a specific path on their domain to prove ownership and prevent spoofing. Key audit points include access controls for URI updates, use of immutable storage, proper cryptographic signature validation (EIP-712), and prevention of signature replay attacks. The **Reputation Registry** provides a standard interface for submitting and aggregating feedback. It uses a "Payment-Proof Linking" mechanism, where feedback submissions must include a proof of a payment (e.g., an x402 transaction hash), making Sybil attacks economically costly. Audit focuses include enforcing payment proof validity, constraining score ranges, and ensuring robust, manipulation-resistant off-chain aggregation algorithms. The **Validation Registry** allows agents to submit their work for independent verification, crucial for high-stakes tasks. It supports two models: 1. **Cryptoeconomic Validation:** Agents stake funds, which can be slashed via a fraud-proof system if malfeasance is proven. Audits must check proof submission windows, decentralized adjudication logic, and sufficient stake levels. 2. **Cryptographic Validation:** This uses Trusted Execution Environments (TEEs) or Zero-Knowledge Machine Learning (zkML). For TEEs, audits must verify proof timeliness and content. For zkML, audits must ensure the use of audited verifier libraries and prevent model-swapping attacks. Overall, a comprehensive security audit of an ERC-8004 implementation must scrutinize all three registries, their interactions, and standard smart contract vulnerabilities to uphold its promise of a decentralized, trustless agent ecosystem.

marsbit03/05 09:10

Building Trustless AI Agents: ERC-8004 Security Audit Guide

marsbit03/05 09:10

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