According to Lex Sokolin, crypto’s edge is enabling AI-to-AI commerce via frictionless micropayments and computational-speed value transfer, not replacing human transactions. Source: Lex Sokolin on X, Dec 3, 2025. For traders, this frames a thematic focus on low-fee, high-throughput payment rails and agent wallets where microtransaction volume and latency are key performance drivers. Source: Lex Sokolin on X, Dec 3, 2025. Actionable indicators to monitor include counts of sub-$1 transfers, median fees trending below 1 cent, stablecoin transfer frequency, and smart-wallet adoption supporting autonomous agents. Source: Lex Sokolin on X, Dec 3, 2025. If AI-to-AI commerce scales, networks minimizing confirmation time and payment friction could capture incremental transaction revenue and higher fee burn, favoring payment-centric infrastructure exposure. Source: Lex Sokolin on X, Dec 3, 2025. Near-term catalysts include live demos of agent-to-agent payments, integrations of agentic AI with crypto rails, and sustained increases in microtransaction throughput on public dashboards. Source: Lex Sokolin on X, Dec 3, 2025.

According to @LexSokolin, the catalyst that turns robot money into web3 is an AI agent earning its first dollar autonomously by holding its own keys and transacting without permission, rather than centralized API or “AI-friendly account” offerings. Source: Lex Sokolin on X, Nov 29, 2025. For traders, this prioritizes permissionless crypto rails and non-custodial machine wallets over fintech integrations when assessing the AI-crypto narrative and potential on-chain activity. Source: Lex Sokolin on X, Nov 29, 2025. The post signals proximity to this milestone, keeping market focus on infrastructure enabling agent-driven payments and self-custody on public blockchains. Source: Lex Sokolin on X, Nov 29, 2025.

According to @LexSokolin, robot money is coming and control of the payment rails will be decisive for the ecosystem (source: @LexSokolin on X, Nov 23, 2025). He states that current machine finance is being built on human-era infrastructure, likening it to running the internet on telegraph wires (source: @LexSokolin on X, Nov 23, 2025). He identifies four required components for machine-to-machine finance: native machine payment protocols, programmable money at the protocol layer, custody solutions for non-human actors, and legal frameworks for autonomous transactions (source: @LexSokolin on X, Nov 23, 2025). He adds that stablecoins serve as the bridge rather than the destination for this architecture (source: @LexSokolin on X, Nov 23, 2025).

According to Lex Sokolin, robot money will save Web3 because machines require programmable value transfer more than humans, highlighting a thesis that machine-to-machine payments and AI agents could be core demand drivers for on-chain finance and infrastructure, source: Lex Sokolin on X, Nov 22, 2025. For traders, this signals a thematic focus on protocols enabling autonomous, programmable payments and agentic commerce rather than immediate price action, as the post offers no data, token mentions, or timelines, source: Lex Sokolin on X, Nov 22, 2025.

According to @LexSokolin, crypto as robot money, robots as future GDP drivers, and Ethereum’s EVM stack together frame a convergence thesis that could shape ETH and EVM narrative momentum for traders. Source: https://twitter.com/LexSokolin/status/1967672223306838403 Traders can track ETH pairs, EVM network activity, and adoption of AI-focused applications on Ethereum as this thesis gains attention in market discourse. Source: https://twitter.com/LexSokolin/status/1967672223306838403