Blockchain

Know Your Agent (KYA): AI Agent Identity, the Standards Race, and What Is Actually On-Chain

When you open a bank account you show an ID. When you sign up for an exchange you take a selfie. That procedure is KYC (Know Your Customer), and since the FATF was founded in 1989 it has been the standard way to keep illicit money out at the entry point of the financial system. Now the entity signing contracts, sending payments and swapping tokens on a DEX is increasingly not a person but an AI agent, and the same question comes back in a new form. The agent that just sent a payment request to my API: who is it, who built it, and what was it actually authorized to do? The trust layer that answers that question is being called KYA (Know Your Agent).

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The A2A (Agent-to-Agent) Protocol: How Agents Delegate to Each Other, and Where Payments Plug In

Every time this blog has covered x402, UCP and MPP or Know Your Agent, the term “A2A” showed up as an assumption. An agent hands work to another agent, pays for it, checks who the counterparty is. All of that sits on a lower layer: how do two agents talk in the first place? The attempt to standardize that layer is the Agent2Agent (A2A) protocol.

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Bitcoin, Ethereum, and the Quantum Computing Question

On March 30, 2026, a joint paper from Google Quantum AI, the Ethereum Foundation, and Stanford shook up the crypto community. It estimated that the physical qubit count needed to recover a private key on secp256k1 (the elliptic curve behind Bitcoin and Ethereum signatures) had dropped nearly 20x from the previous best estimate. A threat that used to sound like “millions of qubits, decades away” now reads as “under 500,000, maybe within this decade.”

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Apify x402 and Coinbase Wallets, in Depth: How Agents Buy Web Automation Tools Directly

Apify, the web scraping platform, announced x402 support: AI agents can now run more than 20,000 Apify Actors by paying with USDC on Base, with no Apify account and no API key. Apify frames the prior x402 ecosystem as roughly 2,000 endpoints, so by its own count this integration expanded the paid-tool surface by about 10x.

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AI Agent Commerce and Coordination: ERC-8183, ERC-8226, ERC-8001, ERC-8041

The ERC-8004/8126/8196 trust stack defines three layers: agent identity, security verification, and policy-constrained execution. It identifies an agent, scores its risk, and keeps it acting within the limits an owner has set. All of that answers one question: can I trust this agent to act on my behalf?

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Chainlink CCIP EVM Contracts: Architecture from Source Code

EVM chains are isolated by design. A contract on Arbitrum has no native way to call a contract on Base, and sending USDC from Ethereum Mainnet to Polygon is not a built-in operation. Cross-chain bridges filled that gap for years, but the category has seen repeated security incidents that highlight how wide the attack surface is.

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Circle CCTP V2 EVM Contracts: A Source-Code Walkthrough

Bridge designs for moving USDC between chains come down to two families. Lock-and-mint parks the original token in a contract on the source chain and issues a wrapped version on the destination. Burn-and-mint destroys the token on the source chain outright and issues the same amount fresh on the destination. Circle’s CCTP (Cross-Chain Transfer Protocol) is the second kind.

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ERC-8004 Agent Reputation: On-Chain Registration and Lookup

A prior post on this blog covered the ERC-8004/8126/8196 trust stack: three Ethereum registries that handle agent identity, reputation, and validation. If you want the conceptual overview first, start there. This post is about something narrower: how feedback actually gets written to the Reputation Registry, how to read it back, and what services are available today to browse and index that data.

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Agentic Payments in June 2026: x402, UCP, and MPP Implementation Progress

Agentic payments in June 2026 moved from “can an agent pay” toward “who authorized the payment, how is it verified, and how is it traced.” The major open protocols (x402, UCP, MPP/pay.sh, and ACP) each had meaningful implementation changes. All figures and commit details below come from GitHub API, PyPI, and npm registry checks.

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AI x Blockchain in 2026: Bittensor, DePIN, and Agent Finance

“AI plus blockchain” spent most of the early 2020s as a marketing phrase. By mid-2026, it has organized into four distinct layers, each with its own competitive dynamics. Which projects have staying power, and what are the actual evaluation criteria at this point?

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Figure: From HELOC Lender to Blockchain-Native Capital Markets

Two companies go by the name Figure. One is Figure AI, the humanoid robotics company. The other is Figure Technology Solutions, which is what this post is about. They are unrelated.

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Lighter: A ZK-SNARK Orderbook DEX on Ethereum

Decentralized exchanges come in two main forms. AMMs (Automated Market Makers) like Uniswap set prices algorithmically from pool ratios and work as permissionless swap venues. Orderbook DEXes match individual buy and sell orders by price and time priority, the same way centralized exchanges like Binance or Coinbase operate. Orderbooks enable limit orders, tighter spreads with active market-making, and more precise price discovery. AMMs do not.

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The AI Agent Trust Stack: ERC-8004, ERC-8126, and ERC-8196

When an AI agent acts on behalf of a user (spending funds, calling contracts, accessing paid APIs), the obvious question is: how do you know this agent is safe? The Ethereum community has three standards that address different layers of that question. They don’t solve the whole problem, but they’re building toward a coherent stack.

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Secret Voting Architecture with FHE, SP1, and Groth16

On-chain secret voting creates three tensions at once. Votes must stay hidden while still being tallied. Off-chain computation cannot be trusted without proof, yet results need to land on-chain. And the EVM cannot run heavy cryptographic operations natively, but it still needs to verify them. FHE (Fully Homomorphic Encryption), SP1 zkVM, and Groth16 each take on one of these.

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