From the experiment

Do coding agents recommend Lemon Squeezy?

Coding agents raised Lemon Squeezy in 94 of 395 judged payments sessions and chose it in none of them. Measured with Claude Code, Codex and Cursor.

Published September 3, 2026 Read as Markdown

Coding agents raised Lemon Squeezy in 94 of 395 judged payments sessions and chose it in none of them.

This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in payments inside a realistic codebase. Not what a chat assistant says about Lemon Squeezy. What an agent actually installed.

The numbers

CategoryPayments
Sessions in the category395
Sessions where Lemon Squeezy was chosen0
Install share0%
Raised as a candidate, not chosen94
Chosen when considered0%
Sitelemonsqueezy.com

Which agents raised Lemon Squeezy

Every agent considered it and none adopted it. Cursor raised it most often, in 43% of its payments sessions.

AgentSessionsRaised Lemon SqueezyChose it
Claude Code13231 (23%)0
Codex1327 (5%)0
Cursor13156 (43%)0

Which buyers it came up for

It surfaced most for requests written as senior engineer, in 45% of those sessions. Knowing which buyer already has the product in mind tells you which pages to fix first.

Who is askingSessionsRaised it
Vibe coder7119 (27%)
Junior developer10825 (23%)
Senior engineer10849 (45%)
Enterprise team1081 (1%)

What Lemon Squeezy was up against

The full ranking in payments, from the same sessions:

#ProductRuns wonShare
1Stripe34988%
2Paddle144%
3Mollie133%
4GoCardless92%
5Adyen31%
6Bottomline PTX31%
7AccessPay21%
8Helcim10%

What this means

Raised 94 times and chosen none is a specific, diagnosable result, and a better starting position than being unknown. The agent has the product in mind. It reached the shortlist 94 times. Something then lost every one of those sessions.

In our data the causes, in the order they occur:

  • The quickstart does not run when pasted, so the agent abandoned it mid-integration.
  • The documentation describes an interface that changed, so the generated code failed.
  • The product name and the package name differ, so the install step went wrong.
  • The fit was genuinely wrong for the repository, which is fine and worth knowing.

All but the last are fixable in days, and the reason is written down in the session transcript.

Where these numbers come from

The 395 sessions in payments are part of a published set of 5,292, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.

Every payments run can be replayed on the board.

If you work on Lemon Squeezy: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts.

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Common questions

Do coding agents recommend Lemon Squeezy?

They raise it but do not choose it. Across 94 sessions where Lemon Squeezy came up as a candidate, agents chose something else every time.

Does Claude Code recommend Lemon Squeezy?

In 0 of the 132 sessions in payments run with Claude Code, which is 0%.

Do different coding agents treat Lemon Squeezy differently?

Not much. The three agents chose it at similar rates, between 0% and 0% of their runs.

How was this measured?

Real coding agents at pinned versions were run in sandboxes inside 51 realistic codebases and asked to solve real tasks. A simulated project owner approved or questioned each recommendation before any code was written, and a judge from a model family that builds none of the agents read every session blind.

Where this comes from

Armature ran 5,292 judged sessions with Claude Code, Codex and Cursor inside 51 realistic codebases, and published every run. The numbers on this page come from that work.

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