Proud to be recognized in the 2026 Go Global AI 100 by Feifan Industrial Research! 🏆 As AI redefines commerce, we're evolving global payments into an intelligent engine. We are building the stablecoin-powered infrastructure to explore the future of programmable, Agentic Payments. 🚀 #PhotonPay# #GlobalPayments# #AI# #Stablecoin# #AgenticPayments#

Stripe building the agentic payment platform just said on A16z pod that "tokens are the new dollars" Jensen Huang building the GPUS for the AI factories just said in his X post "in the AI economy, compute is revenue" Together, that’s the AI economy: money → compute → intelligence → output. AI is breaking the old link between economic output and human time. The AI Macro Nexus Point where AI and crypto merge to form the new agentic speed economy is starting now.

"We have personally not deployed to an agentic focused company yet despite that being the hottest category." @AlexLWitt, General Partner at @VerdaVentures, shares what an agentic payments company has to show to get funded > A sustainable business already in place, rather than a company built around whatever is hottest that year > A reason why a company built purely around agentic payments keeps the value, instead of becoming a building block that anyone can plug into > An answer for the existing B2B stablecoin leaders, who can add agentic payment services themselves as a better way to capture the value "Our general approach has been distribution is king. So if you own the distribution with businesses and can layer on agentic payments, that's what's most interesting for us."

When we surveyed five leaders in the agentic payment space, we got a pretty clear consensus. Institutions are adopting this first, not consumers, and the reason has less to do with the technology and more to do with the fact that most people still don't want an AI agent touching their money. Jacquie (@jacqmelinek) and Alex (@ahbeaudry) spoke more on why this may be the case: "The idea of trust and that institutions are probably more willing to trust this because it's a technology that they could use to cut costs, cut intermediaries, whereas the consumer doesn't necessarily feel that way. And until consumers can actually trust this and realize like okay, this is more of a tool [that improves] my life." "On the institutional front, the transactions that they would be using agents for are a lot easier to trust an agent to do. So for a consumer, if I'm using it to buy shoes, that's a much more complicated task than having an agent handle my payroll or handle micro transactions. Those are a lot more programmable and easier to predict and to set up in advance."

❗@0xPolygon is for AI. Agentic payment volume has exploded, making the network one of the standout performers as AI-driven on-chain activity reaches new highs. The pace of growth over the past few months has been remarkable, highlighting how quickly this emerging sector is evolving. AI agents are no longer just a narrative, they're starting to generate measurable economic activity. And we believe that AI-native payments could become one of the defining blockchain use cases of this cycle, and Polygon is positioning itself as one of the key networks powering that future.

This was the week the control layer became the story. Agentic finance is no longer waiting for AI agents to become capable enough to transact. Payment rails are going live, banks are assigning agents real system access, and regulators are beginning to define who is responsible when autonomous software moves money. Here are seven developments that mattered: 1. The @x402 Foundation became fully operational under the Linux Foundation, completing Coinbase’s contribution of the protocol to open governance. This is more than ecosystem growth. Once a payment protocol is governed beyond a single vendor, it has a much stronger path toward becoming shared infrastructure for the agentic web. 2. @hmtreasury published its Financial Services AI Adoption Plan, identifying agentic payments as a near-term test case for broader autonomous finance. Its highest-priority recommendation calls for an agentic-payment trust framework built around three pillars: • clear legal liability • standardized Know Your Agent protocols • interoperable authentication and governance This is not regulation yet. But the conversation has moved from abstract AI risk to a much more practical question: when an agent transacts, who authorized it, what was it allowed to do, and who is accountable? 3. A joint @Visa and @artemis report divided agentic commerce into two categories: Macro-commerce: agents purchasing on behalf of people, where cards remain a natural fit. Micro-commerce: software paying software for APIs, data or compute, often in amounts too small for traditional card economics. Using adjusted onchain data through April 21, the report found that x402 had processed roughly 109.6 million transactions and $15 million in volume. Visa’s conclusion was not cards versus stablecoins, but a future in which both rails coexist. Two days later, Visa launched its Stablecoin Platform in beta, combining wallet infrastructure, minting and redemption with dual approvals, audit logs, passkeys and transfer allowlists. 4. A @KPMG survey cited by @Reuters found that 51% of banks are already piloting AI agents. @BNYglobal treats some agents as “digital employees,” giving them login credentials, assigned tasks and human managers. @UBS agents can prepare and execute trades or transfers after an adviser makes the decision. @MorganStanley is testing client-facing assistants while keeping portfolio decisions under human oversight. The emerging operating model is not simply human or machine. It is delegated access paired with named accountability. 5. @Entrust_Corp launched an Agentic AI Trust Accelerator focused on four production requirements: verifiable identity, real-time authorization, cryptographic assurance and proof of action. The program reflects a wider shift across enterprise AI. An agent cannot be trusted simply because its model is capable. Its identity, delegated authority and actions need to remain verifiable across systems and organizations. 6. @OpenAI introduced GPT-Red, an automated red-teaming model designed to find prompt-injection vulnerabilities. In one controlled exercise, GPT-Red compromised a live autonomous vending-machine agent, changed the price of expensive products to $0.50 and cancelled another customer’s order. Model-level defenses are improving. But once agents can access systems and move value, safety cannot depend entirely on the model correctly interpreting every instruction. External policies, execution controls and auditability still matter. 7. @Kimi_Moonshot released Kimi K3, a 2.8-trillion-parameter model built for long-horizon coding, knowledge work and tool use, with a one-million-token context window. One of its own disclosed limitations is “excessive proactiveness”: on ambiguous tasks, the model may make unexpected decisions on the user’s behalf. That may be the clearest description of the next infrastructure problem. Agents are becoming better at acting for longer periods with less supervision. The systems constraining those actions now need to advance just as quickly. The pattern across the week is clear: Models are getting better at deciding. Payment rails are getting better at settling. The open question is who controls the moment between the two. At Vishwa, that is the layer we are building for: turning an agent’s intent into an authorized, policy-bound and verifiable financial action-before money moves.

BlackRock's new report says AI and Crypto are complementary technologies. They share three zones of overlap: > Shared tokenization architecture: LLMs break language into tokens machines can understand. Blockchains break economic value into tokens machines can verify, transfer, and settle. > Agentic commerce needs machine rails: Cards, ACH, and bank accounts were built for humans clicking buttons. Agents need 24/7, programmable, high-frequency rails, which crypto-powered protocols like x402/MPP provide. Compute is becoming a digital asset market: Hyperscaler cloud revenue is projected to reach ~$1.1T by 2030. Standardized, tokenized claims on compute capacity could be financed, hedged, and settled onchain. Citing simulations by the Bitcoin Policy Institute, BlackRock further said that ~79% of models chose BTC for value storage, while 52% chose stablecoins for transactions, with bank money at under 9%. If the thesis plays out, crypto isn't just a side hobby for AI; it becomes the structural buyer of: > Settlement and blockspace > Stablecoin float and velocity > Programmable assets (tokenized cash, treasuries, RWAs) > Eventually even compute claims Coinbase and Solana are already leading in x402 agentic payment transaction volumes, while Stripe-backed Tempo is lining up agentic transactions with its MPP protocol. Data from Artemis already show agentic transactions going from virtually zero in Q4 2025 to ~262M till date. Circle-backed USDC is the workhorse asset for x402-style flows. Circle's recent launch of the ARC Network, with the intention of becoming the settlement layer for agentic transactions, proves they're already building products to lead this category. BTC, ETH and SOL are all big beneficiaries of the machine economy. BTC is the savings asset for AI. ETH's default settlement-layer vibes, combined with its lead in stablecoins and RWAs, mean more and more agents will use the network for identity, wallets, and transactions. SOL, on the other hand, is the best positioned for low-cost, high-volume transactions.