# How to get picked for payments by coding agents > Stripe took 88% of 395 judged payments sessions. What the numbers say a vendor in this category should do. Source: https://armature.tech/library/payments-coding-agents-playbook Published: 2026-09-03 Publisher: Armature, Inc. (https://armature.tech) --- If you sell payment providers, this page is the part of the market no dashboard shows you: what a coding agent does when a developer asks for payments and never compares vendors. The numbers come from 395 judged sessions with Claude Code, Codex and Cursor, spread across 11 realistic codebases, with every session read by a judge. ## What coding agents choose for payments > Across 395 judged sessions, **Stripe** was chosen most often, in **88%** of runs. Paddle was second with 4%. | # | Product | Runs won | Share | | --- | --- | --- | --- | | 1 | Stripe | 349 | 88% | | 2 | Paddle | 14 | 4% | | 3 | Mollie | 13 | 3% | | 4 | GoCardless | 9 | 2% | | 5 | Adyen | 3 | 1% | | 6 | Bottomline PTX | 3 | 1% | | 7 | AccessPay | 2 | 1% | | 8 | Helcim | 1 | 0% | | 9 | Square | 1 | 0% | Full board, every run replayable: [the payments leaderboard](/leaderboards/payments). ## What the shape of this category means One product takes 88% of runs. This category is close to decided, and a challenger does not win it with content this quarter. Stripe is in the training data, in the templates and in the repositories. At 88% of 395 sessions an agent reaches for it without deliberating. No amount of writing changes that this quarter. What Paddle and the rest of the field can do is narrow: there are always requests the default fits badly, and those are winnable in full. What does work is narrowing. Find the requests where the leader is a bad fit and own those completely. Regional requirements, a pricing model the leader does not offer, a compliance constraint, a stack the leader supports poorly. Write those pages in the words the request uses. And check the persona split below. A category can be decided for one kind of buyer and open for another. ## The agents do not agree with each other In this category all three agents put Stripe first, which is less common than it sounds: across the eighteen categories we measured, Claude Code and Codex disagreed on the leader in nine of them. | Agent | Runs | Picked most often | | --- | --- | --- | | Claude Code | 132 | Stripe (126) | | Codex | 132 | Stripe (110) | | Cursor | 131 | Stripe (113) | Even where they agree, they get there differently. Codex ran a web search in 53% of decision runs and Claude Code in 1.6%, so what you publish reaches one of them in half its payments sessions and the other in almost none. ## Who is asking changes the answer Every request was written as a specific kind of person. In this category Stripe led for every persona, which is a sign of a strong default. | Who is asking | Runs | Picked most often | | --- | --- | --- | | Vibe coder | 71 | Stripe | | Junior developer | 108 | Stripe | | Senior engineer | 108 | Stripe | | Enterprise team | 108 | Stripe | ## What you are really competing against In this category agents never chose to build it themselves. Every session ended with a product. That is good news: you are in a straight vendor comparison, and the levers that work are the ones you control. ## Considered, and never chosen Because the judge records every product an agent raised and not only the one it picked, this board also shows who kept reaching the shortlist and losing. In payments the clearest case is PayPal: on the table in 139 sessions, chosen in none. | Product | Raised in | Chosen in | | --- | --- | --- | | [PayPal](/library/do-coding-agents-recommend-paypal) | 139 sessions | 0 | | [Lemon Squeezy](/library/do-coding-agents-recommend-lemon-squeezy) | 94 sessions | 0 | | [Braintree](/library/do-coding-agents-recommend-braintree) | 64 sessions | 0 | | Worldpay | 29 sessions | 0 | | Chargebee | 29 sessions | 0 | Being rejected is a better position than being unknown, and a cheaper one to fix. The product is already in the agent's head and on the list. Whatever ended those 355 sessions is recorded in each transcript, one reason at a time. ## What to do about it in payments 1. **Skip the build-versus-buy argument.** No payments session in this experiment ended with the agent writing its own implementation. Every one adopted a product, so the whole contest is against the other names in the table above. 2. **Do not attack Stripe head on.** At 88% it is the default an agent reaches for without deliberating. Find the requests where it fits badly, which in our data means regional requirements, a pricing model it does not offer, a compliance constraint or a stack it supports poorly, and own those in the words the request uses. The work that applies to every category rather than to this one is written up separately: [audit your documentation](/library/audit-your-docs-for-coding-agents), [write a quickstart an agent can follow](/library/write-a-quickstart-an-agent-can-follow), and [how to measure install share](/library/how-to-measure-install-share). ## Every payment provider on this board One page per product, with its install share, the per-agent split, and how often it was raised without being chosen. - [Do coding agents recommend Stripe?](/library/do-coding-agents-recommend-stripe) — chosen in 88% of sessions - [Do coding agents recommend Paddle?](/library/do-coding-agents-recommend-paddle) — chosen in 4% of sessions - [Do coding agents recommend Mollie?](/library/do-coding-agents-recommend-mollie) — chosen in 3% of sessions - [Do coding agents recommend GoCardless?](/library/do-coding-agents-recommend-gocardless) — chosen in 2% of sessions - [Do coding agents recommend PayPal?](/library/do-coding-agents-recommend-paypal) — raised in 139 sessions, chosen in none - [Do coding agents recommend Lemon Squeezy?](/library/do-coding-agents-recommend-lemon-squeezy) — raised in 94 sessions, chosen in none - [Do coding agents recommend Braintree?](/library/do-coding-agents-recommend-braintree) — raised in 64 sessions, chosen in none ## Where these numbers come from 395 judged sessions in payments across 11 codebases, part of a published set of 5,292. Real coding agents at pinned versions, in sandboxes, inside realistic codebases, with a simulated project owner in the loop and a blind judge on every session. The full method is on one page: [how we measured this](/library/how-we-measured-this). Every payments run can be replayed on [the board](/leaderboards/payments). ## Common questions ### How many codebases is this based on? 395 judged sessions across 11 realistic codebases. A category only runs on repositories where its seam is open, so coverage differs: some categories ran on more than ten codebases and some on two. ### What payment provider do coding agents choose? Across 395 judged sessions, Stripe was chosen most often, in 88% of runs. Paddle was second with 4%. The result changes by agent and by who is asking. ### Do Claude Code and Codex pick the same payment provider? Yes. All three agents we tested put Stripe first in this category, which is unusual: they disagree in half of the categories we measured. ### How often do agents build payments themselves instead of installing something? Never, in this category. Every one of the sessions ended with the agent adopting a product rather than writing the code itself. ### How can a vendor improve its position here? Make the quickstart run when pasted, state the current version on the documentation page, use one name across product, package and import, write pages for the symptoms users describe rather than only the category name, and get into the repository through templates and framework integrations. ### Which payment providers do agents consider but never choose? PayPal (raised in 139 sessions, chosen in none), Lemon Squeezy (raised in 94 sessions, chosen in none), Braintree (raised in 64 sessions, chosen in none), Worldpay (raised in 29 sessions, chosen in none), Chargebee (raised in 29 sessions, chosen in none). Being considered and not chosen is a different problem from being unknown, and it is usually fixable. ## Read next - [Agent discoverability: the complete guide](https://armature.tech/library/agent-discoverability) (Markdown: https://armature.tech/library/agent-discoverability.md) - [How coding agents choose tools](https://armature.tech/library/how-coding-agents-choose-tools) (Markdown: https://armature.tech/library/how-coding-agents-choose-tools.md) - [Do coding agents recommend Stripe?](https://armature.tech/library/do-coding-agents-recommend-stripe) (Markdown: https://armature.tech/library/do-coding-agents-recommend-stripe.md) - [Do coding agents recommend Paddle?](https://armature.tech/library/do-coding-agents-recommend-paddle) (Markdown: https://armature.tech/library/do-coding-agents-recommend-paddle.md) - [Do coding agents recommend Mollie?](https://armature.tech/library/do-coding-agents-recommend-mollie) (Markdown: https://armature.tech/library/do-coding-agents-recommend-mollie.md) --- Armature helps software products get discovered and used by coding agents. Service: https://armature.tech/discoverability · Results: https://armature.tech/leaderboards/sectors · Contact: contact@armature.tech