We're excited to share that Gate US and @AlpacaHQ are aligning on a shared vision: bringing together AI infrastructure and trading infrastructure to power the next generation of agentic trading. Alpaca has built one of the most agent-friendly trading APIs in the market, and its community has been turning trading ideas into real, working projects — from research workflows to paper trading systems to fully agentic pipelines that connect market data, analysis, and execution logic. Gate AI is building the infrastructure layer for AI agents and developers — including GateRouter, a unified API that gives developers instant access to 25+ mainstream AI models with intelligent routing to optimize cost and performance. Putting these two pieces together points to a clear opportunity: developers building AI trading agents shouldn't have to choose between great execution infrastructure and great AI infrastructure — they should be able to have both, seamlessly. What this means going forward: ✅ Exploring how Gate AI's model routing and agent infrastructure can plug into trading workflows built on APIs like Alpaca's ✅ Supporting builders who want to combine market data + AI reasoning + trade execution into agentic systems ✅ Sharing knowledge and best practices between the Gate AI and Alpaca builder communities ✅ Continuing to lower the cost and complexity of building AI-native trading applications This is the start of a conversation, not the end of one. We'll be sharing more as the technical details take shape — and we'd love to hear from builders in both communities about what you'd want to see. If you're building agentic trading workflows and want to be part of shaping this, reach out — we'd love to hear from you. 👉 Learn more: #AI# #AgenticTrading# #Fintech# #GateAI# #Alpaca#

Last week in agentic finance: @TheFCA published the Mills Review, the first regulator-initiated review of its kind globally. It found that 11 million UK adults are likely to use AI that can act autonomously within pre-set financial goals. Its recommendations go beyond AI safety. They call for trusted agent frameworks covering identity, delegated authority, consent mandates, control, liability, audit and revocation. @bankofengland also put agentic payments and agentic trading under deeper examination, highlighting a fundamental tension: AI agents are probabilistic. Payment systems require deterministic and legally certain outcomes. Meanwhile, the infrastructure kept moving. @Mastercard completed Moldova’s first payments executed by an AI agent, using authenticated agents, verified intent and consumer-defined permissions. @brave unveiled browser-native support for #x402# and MPP, alongside BravePay for private, onchain stablecoin settlement. @SwiftCommunity made its blockchain ledger ready for initial use, with 17 banks preparing to pilot tokenized deposits for 24/7 cross-border payments. The direction is becoming clearer. Agentic finance is no longer only about giving agents access to money. It is about defining: Who the agent is. What authority it has. Which rules govern its actions. Who is liable when something goes wrong. And whether an action should execute at all. Identity proves which agent is acting. Payment rails move the money. But neither proves that the action still matches the user’s mandate at the moment of execution. That is the missing layer between agentic payments and agent-native banking. Vishwa is building the pre-execution verification layer for that gap. No proof. No execution.

Crypto is coming to agentic trading. Eligible US customers will soon be able to connect their AI agent to a dedicated Robinhood account to trade crypto on their behalf, with the same real-time P&L tracking and push notifications they already know from agentic trading. More soon.

Tokenized stocks and agentic trading are moving into real products. 🧠🔐 Robinhood Chain is live with 24/7 stock tokens, DeFi access and planned agentic accounts. HootArk's take: when agents can trigger trades, browsers need to check intent before wallets sign. #HootArk# #Web3#