Walmart, Shopify, and Stripe are helping open a door for personal AI agents.
That door could decide which brands actually reach the customer.
Two Announcements, One Problem
1. Sierra announced the Personal Agent Protocol (PAP), which it’s developing with Meta and a first group of partners.
2. Decagon open-sourced its own PACT protocol the same day, and joined Sierra’s PAP working group instead of competing with it.
PAP’s approach is simple. The customer grants access. The business sets the limits. The agent can work through the website, the API, or the business’s own agent, with MCP as one likely route in.
PACT does the same job from the other side: a customer’s agent works with a business’s agent inside the customer’s own permissions, and the personal agent never touches the customer’s password. It’s not a from-scratch protocol either, Decagon built it on top of A2A 1.0 and OAuth 2.0, the same identity and authorization standards most of enterprise software already runs on. That’s a quiet but deliberate choice: it means PACT doesn’t ask a business to rebuild its auth stack, just to extend it.
Sierra names six partners already: Genesys, Instinct, Rocket, Shopify, Stripe, and Walmart. The v0.1 specification is planned for later this month. It’s early, but several serious companies are already building toward the same handshake.
Shopify’s own VP of Product put it plainly in Sierra’s announcement: the protocol is there to establish how agents and merchants work together at all, not just how fast they can. Stripe’s head of payments is quoted in the same post, which tells you the part of this stack everyone expects to matter most: not the handshake, the money that moves after it.
The Agent’s Answer Becomes the New Shelf
Consumer brands spent twenty years fighting for a place in Google search. Now an agent can stand between the buyer and the store, choosing which products to show and which to leave out.
The agent’s answer becomes the new shelf.
Without an interface for agents, MCP or something close to it, a business leaves that interaction to someone else. The agent works with whatever it can read off the website, and the brand loses its say in how its own products get described.
For me, “agentic-ready” comes down to one practical question: can an agent find your products, get accurate information, and complete a task inside the customer’s permissions?
I’d start with a simple test. Ask a personal agent about your own brand. See what it gets right, what it gets wrong, and whether you have any way to fix what it’s working from.
OpenAI Already Ran a Version of This
None of this is entirely new. OpenAI launched Instant Checkout inside ChatGPT back in September 2025, starting with a narrow, deliberate test: US users buying single items from Etsy sellers, with Shopify merchants and more regions promised to follow. Merchants paid a fee on completed purchases. Shopping through it was free for the user.
What’s worth watching is that OpenAI has since pulled back from running checkout itself, shifting toward a model where the merchant keeps the checkout and the agent just hands off to it. Owning the whole transaction inside someone else’s chat, payment, fulfillment, returns, support, turned out to be harder, or less wanted, than the original pitch made it sound. Processing a purchase is not the same job as being trusted with a return.
That’s the precedent PAP and PACT are walking into. A protocol can standardize permission. It says nothing yet about who ends up holding the money, or the customer, when something goes wrong after the sale.
A $20 Subscription Won’t Pay for a Personal Agent
The purchases it drives will.
I expect personal agents to earn a growing share of their revenue from the spending they send to merchants. Subscriptions can stay. Purchases open up another way to earn.
I expect agent platforms to build the payment layer underneath those purchases: card programs through issuing partners, a share of interchange fees, bulk discounts, a cut of whatever savings they generate. Revenue grows with the spending they handle, not just the seats they sell.
That gives every platform a reason to pool demand into one network instead of negotiating with every hotel, restaurant, and retailer one at a time. The network does that work once and hands the same terms to every agent connected to it.
For a brand, getting into the agent’s answer stops being a marketing question. Price, availability, and the cost of winning the order all sit on the table now, next to the permissions.
Can your business handle negotiated prices, track who actually brought the sale, and calculate what you owe them? Imagine a network offers to bring you 10,000 orders and asks for 10% of each one. You need to know your margin before you say yes.
My Forecast
The largest agent platforms end up as fintech businesses with real purchasing power, not just software companies with a chat window attached. Brands end up negotiating with networks that bring the customer, handle the payment, and ask for better terms in return.
Agents and fintech become one business. That’s agentic finance.
Where the Real Work Sits
Product data, pricing, orders, and commission tracking all have to connect, and the commercial agreement has to work inside the systems that already run the business, not next to them.
Picture the 10,000-order network deal going live. The agent network sends traffic, the orders land in the business’s own systems, and thirty days later an invoice shows up for 10% of gross, not net, with a different definition of “completed order” than the one the sales team uses internally. Nothing in PAP or PACT resolves that disagreement. The protocol governed the handshake. It had nothing to do with the invoice.
I’ve written before about the gap between what a model can do and what a company actually runs, and who gets paid to close it. This is the same gap, one layer further down. The protocol settles what an agent is allowed to do. It settles nothing about who checks that the numbers reconcile afterward, or who has standing to dispute them when they don’t.
That part shows up the first time a network claims a commission nobody budgeted for.
Watch the payment layer. The permission layer was never the hard part.