DEV Community: Tom Wang

KFTC Builds Korea's AI Agent Payment Rail

Tom Wang — Thu, 07 May 2026 07:48:43 +0000

While most agentic commerce announcements this year have come from individual companies — Stripe, Visa, Alipay, Meta — Korea just made a different kind of move. On 3 May 2026, KFTC chairman Chae Byung-deuk used a press briefing on the sidelines of the Asian Development Bank annual meeting in Uzbekistan to unveil the Financial Sector AI Transformation Support Plan, anchored by a national AI agent payment platform. For any fintech developer UK, payment developer, or AI agent developer UK watching where state infrastructure goes next, this is the most consequential announcement of the week.

KFTC is not a private payments company. It is the entity that runs Korea's interbank network, ATM clearing, foreign exchange settlement, and the country's QR-payment scheme. When KFTC ships an AI agent payment rail, it ships at the same level as FedNow or Faster Payments — public infrastructure that every bank in the country plugs into.

What KFTC Is Actually Building

The plan has three layers, and the agent payment platform is the most visible one:

Finance-specialised AI corpus — distributed to banks for fine-tuning and grounding. This solves a problem private banks have been running into independently: their internal LLM tooling has no shared, regulator-blessed Korean-language financial training data.
AI agent work environment — internal-facing tooling KFTC is building for its own operations, including fraud detection and AML pipelines.
National AI agent payment platform — the public-facing piece. A user opens a conversation, the agent finds the product, the agent executes payment, the transaction settles. No app switching, no checkout redirect.

The PoC is already running. Initial scope is small-value transactions with explicit security prerequisites — a sensible launch envelope that mirrors how FedNow rolled out and how UK Faster Payments handled its early years.

The political framing matters as much as the technical scope: KFTC is positioning agentic payments as national infrastructure, not a vertical product. The "Financial Sector AX Alliance" KFTC is forming with banks and fintechs is the policy mechanism — every Korean financial institution is invited in, the way every UK bank is part of the open banking ecosystem.

Why a National Agent Rail Looks Different from a Stripe-Style One

Compare KFTC's announcement with Stripe Sessions 2026 from yesterday and the architectural divergence is sharp.

Stripe's stack is vendor-led: Link agent wallet, Checkout Studio, Stripe Console, all owned by one company, integrated by merchants who choose to opt in. KFTC's stack is rail-led: the platform sits at the clearing layer, every Korean bank connects through it, and the agent payment flow inherits the same systemic risk and compliance posture as a regular interbank transfer.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, an AI Developer & Fintech Developer — building AI agents, crypto payment infrastructure, and cross-border payout systems with Rust, Go, and TypeScript. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

Pay.sh Lets AI Agents Pay Google Cloud in USDC

Tom Wang — Wed, 06 May 2026 13:36:50 +0000

Pay.sh — a joint launch from the Solana Foundation and Google Cloud — went live this week, and it is the first time a hyperscaler has agreed to take stablecoin payments natively over x402. AI agents can now spend USDC on Solana to call Gemini, BigQuery, Vertex AI, plus 50+ third-party APIs including OpenAI's Codex, Anthropic's Claude Code, OpenClaw, Hermes, Helius, Alchemy, Dune Analytics, and Nansen. For any AI agent developer UK, crypto developer UK, or payment developer building on autonomous infrastructure, this is the most consequential x402 deployment to date.

Stripe, Meta, Alipay, and now Solana + Google Cloud — the production deployments are no longer trickling in. The agentic commerce stack is shipping at hyperscaler density.

What Pay.sh Actually Is

The architecture is deliberately thin. Pay.sh sits as an API proxy on Google Cloud Platform, in front of the existing Gemini, BigQuery, and Vertex AI endpoints. When an agent makes a request, the proxy can either let it through (free tier, authenticated user, etc.) or respond with an HTTP 402 Payment Required. The agent then settles on Solana — sub-cent USDC — and retries. The proxy verifies, releases the response, and bills the agent's wallet.

Two protocols do the heavy lifting:

x402 — Coinbase's HTTP-native payment standard, transferred to the Linux Foundation in April. Provides the 402 Payment Required flow, payment instructions header, and the receipt format.
MPP (Machine Payments Protocol) — Stripe and Tempo's spec for agent-to-agent payment intent. Pay.sh accepts both, which is significant: it normalises the "two competing protocols" narrative into "use whichever your agent runtime emits."

For the developer, the surface area is tiny. An MCP- or LangChain-style tool emits an HTTP request; the SDK handles the 402 dance underneath. A Solana wallet — from Privy, Phantom programmatic, or a custodial agent wallet — signs the transfer.

Why This Is the First Real x402 Production Story

x402 has had a handful of production endpoints since the protocol launched, but Pay.sh is the first time a top-three hyperscaler is on the receive side. The implications matter:

Catalogue scale. Gemini, BigQuery, and Vertex AI are some of the most-called APIs on the public internet. Pay.sh routes every one of those calls through an x402-aware proxy — instantly making Solana stablecoins a first-class payment rail for AI workloads.
Long tail attached. The 50+ community providers (Codex, Claude Code, OpenClaw, Hermes, Helius, Alchemy, Dune, Nansen) ride the same proxy. Adding new endpoints is now an SDK integration, not a billing-team negotiation.
Per-call economics. Agents pay fractions of a cent per call with no minimum spend. This kills the legacy SaaS metering model for the agentic use case — there is no enterprise contract, no monthly invoice, no procurement cycle. The agent expenses what it consumes.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, an AI Developer & Fintech Developer — building AI agents, crypto payment infrastructure, and cross-border payout systems with Rust, Go, and TypeScript. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

Stripe Sessions 2026: Agent Wallets and 160 Countries

Tom Wang — Tue, 05 May 2026 21:48:53 +0000

Stripe Sessions 2026 wrapped up on 30 April with the densest single-day product release the company has ever shipped. An agent wallet, an Agentic Commerce Suite co-built with Meta and Google, stablecoin payouts in 160 countries, four new chains in the settlement set, and an AI-native developer console. For any fintech developer UK, payment developer, or AI agent developer UK trying to figure out where the next two quarters of work concentrate, this is the most important release calendar entry of the year so far.

It also lines up neatly with yesterday's piece on Meta's USDC creator payouts — Stripe is the connective tissue underneath both stories, and that is not coincidence.

Link Agent Wallet — Credentials Stop Leaving the Vault

The headline product is Link agent wallet. The pitch is short: an LLM-driven agent can complete checkout on the user's behalf without ever seeing a card number, BIN, or token. The wallet sits between the agent and the merchant; the agent expresses intent ("buy this", "subscribe at this tier"), the wallet authorises within scope, and the credential stays inside Stripe.

Three engineering details make this consequential:

Scope-narrowed authorisation. The agent receives a single-use or short-lived authority to make a specific purchase. Compromise of the agent's runtime does not leak a payment instrument.
Multi-rail support out of the gate. Brazilian Pix, US stablecoins, with Indian UPI in the pipeline. This is not a US-only crypto experiment — it is built for the markets where local rails matter more than card networks.
Idempotency surfaced through the API. Every agent-initiated charge has an explicit idempotency key in the wallet's protocol. This is the single biggest piece of operational hygiene for non-deterministic callers, and it is finally first-class.

For a payment developer integrating an agent runtime today, Link removes the worst design decision — "do I let the agent see a token?" — by making it impossible.

Checkout Studio and the Configuration-as-Product Bet

Checkout Studio collapses what used to be a six-team checkout build (frontend, A/B platform, fraud, observability, data, finance) into a single configuration plane. Merchants edit checkout flows without code, ship them to web/native/in-store, and watch the analytics in the same surface.

The interesting thing for engineers is the escape hatch. Custom Objects (a separate launch) lets teams add domain-specific data models — subscription tiers, marketplace splits, dynamic pricing rules — that Studio can render and that Stripe's tax/fraud layers respect. The config UI is for the 80% case; the data model is open for the rest. This is the same architectural pattern Shopify uses to keep merchants in the platform without forcing every flow through a no-code editor.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, an AI Developer & Fintech Developer — building AI agents, crypto payment infrastructure, and cross-border payout systems with Rust, Go, and TypeScript. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

Meta Pays Creators in USDC on Polygon, Solana

Tom Wang — Thu, 30 Apr 2026 23:19:13 +0000

Six years after Libra was shelved under regulatory pressure, Meta is back in the payments game — quietly. On 29 April 2026 the company started paying selected creators in USDC on Polygon and Solana, with Stripe handling the on-ramp and tax reporting layer. The rollout is small (Colombia and the Philippines first, expanding to 160+ countries by year-end) but the architecture is the news. For any fintech developer UK, crypto developer UK, or payment developer building cross-border payouts in 2026, this is the reference design to study.

Meta's not alone in this week's stablecoin push. Visa expanded its settlement pilot to nine blockchains and disclosed a $7B run rate growing 50% quarter on quarter. The infrastructure is no longer experimental — it is shipping at scale.

What Meta Actually Built

The flow is deceptively simple. A creator opts into stablecoin payouts through Facebook's payout platform, supplies a third-party USDC wallet address on Solana or Polygon, and receives earnings denominated in USDC. Meta does not convert to local currency. The creator is responsible for off-ramping, custody, and any local tax obligations on top of the reporting Stripe provides.

That single sentence hides several deliberate engineering choices:

No internal custody. Meta does not hold creator funds in a wallet of its own. The creator brings the wallet; Meta sends the payout. This sidesteps the licensing burden that sank Libra and is the reason the architecture is shippable in 160+ countries without a bespoke regulatory regime in each.
Two chains, on purpose. Polygon offers low fees and broad EVM tooling; Solana offers high throughput and the tightest fee profile for micro-payouts. A two-chain design lets Meta route on cost and creator preference without committing to either ecosystem long-term.
Stripe at the compliance layer. Stripe's Issuing and Connect products already handle 1099/VAT/global tax reporting for traditional payouts. Extending that surface to crypto means the regulated reporting path is one Meta — and any developer building on Stripe — already trusts.

This is the first time a household-name internet platform has shipped a stablecoin payout product without trying to mint its own coin. The "boring" architecture is the point.

Why This Is the Blueprint for Cross-Border Payment Developers

For a payment developer UK building creator economy or marketplace payouts, the legacy stack is brutal: SWIFT for high-value transfers, local ACH/Faster Payments rails for domestic, a tangle of correspondent banks for everywhere else, FX desks taking 1–3% on conversion, and settlement times measured in days. Meta's architecture compresses that into something a small team can actually run:

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, an AI Developer & Fintech Developer — building AI agents, crypto payment infrastructure, and cross-border payout systems with Rust, Go, and TypeScript. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

Alipay's MCP Server Brings Payments to AI Agents

Tom Wang — Wed, 29 Apr 2026 21:06:22 +0000

Alipay went live yesterday with a business-facing AI payment processing product, and the more interesting half of the announcement is buried in the developer notes: a Payment MCP Server that lets AI agents call real money flows through natural language. For anyone working as an AI agent developer UK, fintech developer UK, or payment developer, this is the most consequential piece of agentic commerce infrastructure shipped this month — and it changes what a credible AI-payments stack looks like in 2026.

The announcement also reframed Alipay AI Pay's growth: 100 million users by February 2026, 120 million transactions in a single week, and 30+ million daily API calls from a single AI agent skill. Those are not pilot numbers. Agentic payments at scale are no longer a theoretical roadmap item.

What Alipay Actually Shipped

Two related products, one stack:

Alipay AI Pay (consumer, launched 2025) — voice- and chat-driven payments where an AI agent acts on a consumer's behalf to buy goods, top up subscriptions, or settle a tab.
AI Payment Processing Product (business, launched 28–29 April 2026) — the merchant-side counterpart. Small and medium businesses, including One Person Companies, can register their monetisable services and accept money each time an autonomous agent triggers a purchase.

Around those products sits a developer surface area that Alipay has been quietly assembling since late 2025:

Payment MCP Server — exposes payment primitives as tools an LLM can call via the Model Context Protocol. Developers describe what they need ("charge ¥5 for one search result", "subscribe this user for ¥30/month") and the server handles authorisation, settlement, idempotency, and refund handling.
Payment Integration Skill — a higher-level construct so agent platforms (Alipay Tbox, Hermes Agent, Qwen, OpenClaw, Rokid Lingzhu) can bind a paying user to a session.
AI Tipping and AI Subscription Payment — pre-built recurring and micro-transaction flows tuned for agent-initiated commerce.

The Bocha case study is the part to pay attention to: the bocha-web-search-a2m skill clears 30+ million API calls a day, each of which is a metered, paid invocation. That is what agentic monetisation looks like in production — not a thought experiment.

Why MCP Is the Right Layer for Payment Tooling

The Model Context Protocol started life as a way to plug LLMs into tools without building a bespoke adapter for every model and runtime. Payment infrastructure benefits from MCP for the same reason that any complex API benefits from MCP: well-typed tool descriptions, strong contracts, and a predictable surface that an agent can reason about.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, an AI Developer & Fintech Developer — building AI agents, crypto payment infrastructure, and cross-border payout systems with Rust, Go, and TypeScript. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

FedNow's Network API Launches for Payment Devs

Tom Wang — Tue, 28 Apr 2026 19:54:42 +0000

The Federal Reserve flipped the switch today on a long-anticipated upgrade to its instant payments rail. As of 28 April 2026, the FedNow Service rolls out its network intelligence API to early adopters — a development that quietly reshapes the daily workflow of every payment developer building on US real-time rails. For anyone working as a fintech developer UK or payment developer UK with cross-border ambitions, this matters: FedNow now exposes the kind of pre-payment intelligence that previously required years of in-house data engineering.

This is more than another endpoint. It is a structural admission that instant payments cannot be safely scaled without instant context.

What the FedNow Network Intelligence API Actually Does

Until today, a FedNow participant validated a transaction using whatever signals it had locally: device fingerprints, internal velocity rules, KYC history, and bespoke fraud models. The new API adds a second layer — receiver account-level data observed across the entire FedNow network. A bank can now ask the rail itself, in milliseconds, whether the destination account has been behaving in ways that correlate with authorised push-payment (APP) fraud, mule activity, or scam patterns elsewhere on the network.

The Federal Reserve's framing is careful: this is decision-support, not a kill switch. Participants combine the API's signals with their own internal data to decide whether to release a payment, hold it, or refer it for review. In practice, that means three new architectural patterns are about to become standard in production payment systems:

Pre-flight risk enrichment — a synchronous call from the originating bank's payment service to FedNow before the ISO 20022 pacs.008 is committed.
Asynchronous risk replays — feeding the API's signals into offline analytics pipelines for model retraining and post-hoc investigation.
Tiered hold logic — dynamic thresholds that route flagged transfers into human review rather than blanket blocking, preserving the instant-payment promise for the 99% of clean traffic.

For engineers who have spent the last decade building payment fraud systems on stale, batch-loaded data, this is a significant generational shift.

Why This Matters for Fintech Developers Building on Real-Time Rails

Real-time payments fail in a particular way. Once pacs.002 confirms settlement, the money is gone — there is no chargeback, no overnight reversal, no friendly clawback. The original FedNow design solved availability and speed; it did not solve the "is this counterparty actually who they claim to be" problem at the network layer. The new API is FedNow's first serious answer.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, an AI Developer & Fintech Developer — building AI agents, crypto payment infrastructure, and cross-border payout systems with Rust, Go, and TypeScript. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

DoorDash Pilots Stablecoin Payouts on Tempo

Tom Wang — Mon, 27 Apr 2026 22:02:58 +0000

DoorDash, the food delivery giant operating in over 40 countries with nearly $75 billion in merchant sales last year, announced on 21 April 2026 that it is piloting stablecoin payouts for global merchants and Dashers. The rails: Tempo, the payments-focused blockchain built by Stripe and Paradigm that went live in production last month.

This is the moment crypto payments stop being a niche merchant feature and start becoming the default settlement layer for global gig-economy platforms. For fintech developers and payment engineers, it is also a clear signal of where mainstream payment infrastructure is heading.

What DoorDash Is Actually Building

The architecture is deliberately invisible to the end user. Merchants and Dashers do not need to hold wallets, manage seed phrases, or even know that stablecoins are involved. Tempo sits between DoorDash's existing financial infrastructure and the recipient, converting platform-held balances into stablecoin-denominated payouts at the point of settlement.

The benefits stack up quickly:

Sub-second finality instead of 1-5+ business days for traditional cross-border payouts
Predictable, dollar-denominated fees instead of FX spreads and correspondent banking charges
Continuous settlement — no more waiting for banking hours, weekends, or holidays
Account abstraction built in — payouts can be batched and gas fees sponsored at the protocol level

For a platform processing payouts to merchants and gig workers across 40+ countries, the cash flow improvement alone is transformative. Cross-border operations that previously locked up working capital for days now settle in seconds.

Why Tempo, Not Ethereum or Solana

Tempo was engineered specifically for payment workloads, and the design choices reflect priorities you do not see in general-purpose chains:

Reserved blockspace for payments — payment transactions cannot be priced out by speculative activity or NFT mints
Private payment zones — sensitive transaction data is not broadcast publicly, addressing enterprise compliance concerns
Fixed fees in fiat terms — no exposure to gas price volatility, which makes accounting and pricing predictable
Built-in account abstraction — fee sponsorship, batching, and programmable authorisation are first-class features

The infrastructure partners list reads like a who's-who of payment incumbents: Mastercard, UBS, Klarna, Visa. DoorDash has been a Tempo design partner since September 2025, which means the chain's architecture has been shaped by real-world payout requirements from day one.

What This Means for Payment Developers

The DoorDash launch is not just another crypto integration story. It is a forcing function for a set of architectural decisions that payment developers will increasingly need to make.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, an AI Developer & Fintech Developer — building AI agents, crypto payment infrastructure, and cross-border payout systems with Rust, Go, and TypeScript. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

AI Agents Expose Crypto Wallet Security Gap

Tom Wang — Fri, 17 Apr 2026 15:22:28 +0000

The rise of AI agents in crypto payments has unlocked powerful automation — but it has also exposed a dangerous security gap. In 2026 alone, protocol-level weaknesses in AI agent infrastructure have triggered over $45 million in losses, forcing the industry to rethink how autonomous systems interact with wallets, oracles, and trading endpoints. For fintech developers and crypto developers in the UK and beyond, understanding these vulnerabilities is no longer optional — it is essential.

What Went Wrong: The $45M Wake-Up Call

The headline incident came from Step Finance, a Solana-based DeFi portfolio manager, where attackers compromised executive devices and exploited overly permissive AI agent protocols. The agents, designed to automate treasury operations, executed transfers of over 261,000 SOL tokens — approximately $40 million — because they lacked proper isolation and permission boundaries.

A separate wave of social engineering attacks, including AI-generated impersonations targeting Coinbase users, added another $5 million in losses. In both cases, the root cause was the same: AI agents were granted broad access to critical infrastructure with insufficient safeguards.

The Core Vulnerabilities Payment Developers Must Know

Research published in April 2026 identified several attack vectors that are particularly relevant to payment infrastructure:

Memory Poisoning

Attackers inject malicious instructions into an agent's long-term storage — typically vector databases used for context retrieval. These "sleeper" payloads remain dormant until triggered by specific market conditions, at which point they can corrupt up to 87% of an agent's decision-making within hours. For payment developers building AI-powered transaction systems, this means every data source feeding your agent's context window is a potential attack surface.

Indirect Prompt Injection

Hidden commands embedded in third-party data sources — market feeds, web pages, even email content — can rewrite transaction parameters mid-execution. This is especially dangerous for cross-border payment systems that aggregate data from multiple external APIs.

The Confused Deputy Problem

Agents with legitimate credentials get tricked into approving fraudulent actions. A striking 45.6% of teams surveyed relied on shared API keys for their agents, making it nearly impossible to trace or halt rogue actions once a compromise occurs.

LLM Router Exploits

Security researchers documented 26 LLM routers — services that sit between users and AI models — secretly injecting malicious tool calls. One incident drained $500,000 from a client's crypto wallet through compromised routing infrastructure.

Building Secure AI Agent Infrastructure

As a fintech developer building payment infrastructure at Radom and working extensively with Rust, Go, and Kubernetes, I see these vulnerabilities as fundamentally architectural problems. The solutions require the same rigour we apply to any production payment system:

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, a Founding Engineer at Radom building crypto payment infrastructure, Open Banking integrations, and cross-border payout systems with Rust and Go. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

Oracle Launches AI Agents for Corporate Banking

Tom Wang — Wed, 15 Apr 2026 12:51:50 +0000

Oracle just dropped embedded AI agents directly into its corporate banking platform — purpose-built for treasury, trade finance, credit, and lending. This is not another chatbot bolted onto a dashboard. These are autonomous agents that process loan contracts, cross-reference financial data, and flag anomalies for human review.

For fintech developers and payment developers building enterprise-grade systems, this marks a turning point. The AI agent is no longer a consumer-facing novelty. It is becoming core infrastructure in institutional finance.

What Oracle Actually Shipped

On 14 April 2026, Oracle Financial Services announced two production-ready agents as part of its Fusion Agentic Applications suite:

Loan Data Extraction Agent — Parses complex, customised corporate loan contracts to extract structured data from unstructured documents. Think multi-tranche syndicated facilities with bespoke covenants, not simple personal loans.
Loan Data Validation Agent — Cross-references extracted loan data against source documents, performs integrity checks, and surfaces anomalies for banker review. This replaces hours of manual reconciliation.

Both agents are designed with human-in-the-loop governance. Finance leaders retain checkpoints for material decisions — accounting entries, capital allocation, regulatory submissions. The agents handle the grunt work; humans handle the judgement calls.

Why This Matters for Payment Infrastructure

Corporate banking has been one of the last holdouts against automation. Consumer payments went digital years ago. Retail banking has chatbots and automated fraud detection. But corporate treasury and trade finance still run on spreadsheets, email chains, and manual document reviews.

The technical challenge is real. Corporate lending involves documents that vary wildly between institutions — bespoke legal language, jurisdiction-specific clauses, nested conditions. Traditional rules-based extraction fails because there are no standard templates.

AI agents change this equation. Large language models can parse unstructured legal text. Validation agents can cross-reference extracted fields against multiple source systems in real-time. The key insight is that these agents are not replacing bankers — they are eliminating the data entry and reconciliation work that consumes 60-70% of a corporate banker's time.

The Infrastructure Gap Fintech Developers Must Close

Oracle building these agents is significant, but it exposes a broader infrastructure problem. Current payment systems were not designed for autonomous software actors.

Consider the authentication challenge alone. When an AI agent initiates a transaction or modifies a loan record, the system needs to verify:

Agent identity — Is this a legitimate agent, not a malicious bot?
Delegated authority — Who authorised this agent, and what are its permission boundaries?
Action scope — Does this specific action fall within the agent's approved parameters?
Audit trail — Can every machine-initiated action be traced back to its authorising principal?

Read the full article on tomcn.uk →

I am Tom Wang, founder of Applr.ai. Based in London, UK.

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Stablecoins Hit 40M Retail Terminals

Tom Wang — Sat, 11 Apr 2026 03:36:59 +0000

Stablecoins are no longer confined to DeFi dashboards and crypto-native apps. In the span of a single quarter, two major partnerships have brought stablecoin payments to physical retail at global scale — and the infrastructure behind them is something every fintech developer and crypto developer in the UK should understand. Ingenico has launched native stablecoin checkout across its 40 million Android POS terminals via WalletConnect Pay, whilst Paysafe has integrated MoonPay's stablecoin rails into its $167 billion-a-year payment platform. For payment developers, the message is clear: stablecoin acceptance at the point of sale is now production infrastructure, not a pilot programme.

How Stablecoin Checkout Works at Physical POS

The Ingenico-WalletConnect integration is the first to bring native stablecoin payments to physical retail terminals without requiring new hardware. Here is how the flow works from a payment developer's perspective:

Customer initiates payment. At checkout, the customer selects stablecoin as their payment method. The Ingenico Android terminal displays a QR code or initiates a WalletConnect session.
Wallet connection. The customer scans the QR code with any of 700+ compatible wallets connected through the WalletConnect protocol — serving over half a billion crypto users globally.
Stablecoin transfer. The customer authorises the payment in their wallet. Supported stablecoins include USDC, EURC, and USDT across multiple blockchains.
Fiat conversion and settlement. WalletConnect Pay handles the conversion from stablecoin to fiat currency. The merchant receives settlement in their local currency through their existing acquirer — no crypto touches the merchant's balance sheet.

The critical architectural insight is that WalletConnect Pay operates as a "messaging layer that sits alongside settlement." It abstracts blockchain complexity entirely from the merchant. As WalletConnect Pay CEO Jess Houlgrave put it: "The payments company and the merchant shouldn't even need to know about any of this stuff. They should just be able to serve this as an offering."

For Ingenico, this means the Digital Currency Application runs on existing Android terminals — no hardware swap, no new integration for acquirers beyond enabling the app. The potential reach is staggering: 40 million POS units across 120 countries.

Paysafe and MoonPay: Stablecoin Rails Inside a $167B Platform

The second major development is Paysafe's integration of MoonPay's crypto payment infrastructure, announced on 8 April 2026. Paysafe processed $167 billion in transactions in 2025 — this is not a niche crypto processor, but a mainstream payment platform serving e-commerce, financial services, retail, and iGaming.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, a Founding Engineer at Radom building crypto payment infrastructure, Open Banking integrations, and cross-border payout systems with Rust and Go. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

AI Agents Now Have Credit Cards

Tom Wang — Thu, 09 Apr 2026 02:44:55 +0000

Today Nevermined announced the integration that many fintech developers and crypto developers have been waiting for: a unified commerce layer that gives AI agents both delegated Visa credit cards and stablecoin wallets through a single platform. By combining Visa Intelligent Commerce with Coinbase's x402 protocol, Nevermined has created the first production infrastructure where autonomous software can pay for goods and services — using either traditional card rails or crypto — without human intervention per transaction. For any payment developer or AI agent developer in the UK, this is the clearest signal yet that agentic commerce infrastructure is ready to build on.

How AI Agents Get Their Own Credit Cards

The core innovation is what Visa calls "agentic tokens" — a fourth token type purpose-built for AI agents, sitting alongside the familiar card-present, card-not-present, and device token categories.

Here is how the delegation flow works:

User enrolment: A cardholder registers their Visa card with Visa Intelligent Commerce and authorises a specific AI agent to spend on their behalf.
Token binding: Visa issues a cryptographically bound agentic token that ties to that specific agent. Unlike virtual cards, the token never exposes the card PAN to the agent runtime.
Guardrails: The user sets granular controls — per-transaction limits, daily/monthly budgets, merchant category restrictions, time-based validity windows, and pre-approved vendor lists.
Three-point validation: Every transaction is verified against three criteria: the credential request matches the user's instructions, the merchant authorisation aligns with the request, and the transaction data matches the original consumer intent.

The critical difference from virtual cards is visibility. Agentic tokens identify the agent to banks, merchants, and payment networks, creating a new "human-not-present" transaction category. This replaces the awkward workaround of disguising agent transactions as card-not-present human purchases — a practice that was already causing fraud detection headaches across the industry.

The x402 Protocol: Machine-Native Payments Over HTTP

On the crypto side, Nevermined integrates Coinbase's x402 protocol — the HTTP-native payment standard that revives the long-dormant HTTP 402 "Payment Required" status code.

The flow is elegantly simple for any payment developer who has worked with REST APIs:

An AI agent sends a standard HTTP request to a merchant's API endpoint.
The server responds with 402 Payment Required and a payment instruction in the response header — specifying the price, accepted currencies (USDC, RLUSD, etc.), and a wallet address.
The agent autonomously executes payment via its agentic wallet — holding stablecoins and making payments without direct human handling of private keys.
The merchant verifies payment and serves the requested resource.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, a Founding Engineer at Radom building crypto payment infrastructure, Open Banking integrations, and cross-border payout systems with Rust and Go. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

Portfolio | LinkedIn | GitHub | Email

Ant Group Launches Anvita for AI Agent Crypto

Tom Wang — Mon, 06 Apr 2026 16:25:57 +0000

Ant Digital Technologies, the blockchain arm of Alipay's parent company, has unveiled Anvita — a two-part platform that lets AI agents autonomously hold crypto assets, execute trades, and settle payments in real time using stablecoins. For any fintech developer or crypto developer building payment infrastructure in the UK, this marks the moment a major Asian fintech giant went all in on the agent-to-agent economy running on crypto rails.

Announced at the Real Up summit in Cannes on 5 April, Anvita sits at the exact intersection of agentic AI and crypto payment infrastructure — two domains converging faster than most payment developers anticipated.

What Anvita Means for Payment Developers

Anvita ships in two distinct modules, each targeting a different layer of the fintech stack:

Anvita TaaS (Tokenisation-as-a-Service)

This is an institutional-grade layer for real-world asset (RWA) tokenisation. It handles custody, treasury management, and the on-chain representation of traditional financial instruments. For payment developers working on cross-border settlement or asset-backed payment flows, TaaS provides the tokenisation primitives that sit beneath the agent layer.

Anvita Flow

Flow is the coordination layer where things get interesting for AI agent developers. It provides:

Agent registration and discovery — autonomous agents can find and negotiate with each other
Real-time settlement — agents settle payments in USDC without human approval
An Agent Store — pre-built modules for data collection, financial analysis, and gaming, plus developer-published custom agents
Framework compatibility — works with Claude Code, OpenClaw, and other agentic AI frameworks

The critical detail: Anvita Flow integrates the x402 protocol — the HTTP-native stablecoin micropayment standard developed by Coinbase and Cloudflare that recently joined the Linux Foundation. This means agents can complete sub-cent transactions instantly using USDC, embedded directly in HTTP request headers. No billing systems, no subscriptions, no human in the loop.

Why This Matters: The Agentic Payment Stack Is Filling In

Over the past week, we have tracked an extraordinary acceleration in the agentic payment space:

Stripe Tempo launched AI agent payment rails with card-based checkout
Visa released an AI Agent Developer SDK for trusted agent commerce
Google introduced AP2, an open protocol for agent-to-merchant negotiation
x402 moved to the Linux Foundation for vendor-neutral HTTP-native payments
Convera and Ripple partnered on stablecoin sandwich settlement for cross-border flows

Anvita is the first platform from a major Asian fintech to enter this space — and it chose crypto rails over card rails. That architectural decision is significant. While Visa and Stripe anchor their agent payment flows to existing card networks, Ant Group is betting that autonomous agents need native digital asset settlement. The reasoning is sound: agents operating at machine speed across borders cannot wait for T+1 card settlement or navigate the correspondent banking maze.

Read the full article on tomcn.uk →

About the Author

I'm Tom Wang, a Founding Engineer at Radom building crypto payment infrastructure, Open Banking integrations, and cross-border payout systems with Rust and Go. Based in London, UK.

Currently open to new opportunities in fintech, crypto payments, and AI agent engineering.

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