From the experiment

Do coding agents recommend CARTO?

Coding agents raised CARTO in 70 of 701 judged maps sessions and chose it in none of them.

Published September 24, 2026 Read as Markdown

Coding agents raised CARTO in 70 of 701 judged maps sessions and chose it in none of them.

This page reports what happened when Claude Code, Codex, Cursor, Grok Build CLI and Muse Code had to solve a problem in maps inside a realistic codebase. Not what a chat assistant says about CARTO. What an agent actually installed.

The numbers

CategoryMaps
Sessions in the category701
Sessions where CARTO was chosen0
Install share0%
Raised as a candidate, not chosen70
Chosen when considered0%
Sitecarto.com

Which agents raised CARTO

Claude Code, Codex, Cursor and Muse Code considered it and none adopted it. Cursor raised it most often, in 21% of its maps sessions.

AgentSessionsRaised CARTOChose it
Claude Code16410 (6%)0
Codex1691 (1%)0
Cursor15433 (21%)0
Grok Build CLI370 (0%)0
Muse Code17726 (15%)0

Which buyers it came up for

It surfaced most for requests written as enterprise team, in 14% of those sessions. Knowing which buyer already has the product in mind tells you which pages to fix first.

Who is askingSessionsRaised it
Vibe coder15010 (7%)
Junior developer23419 (8%)
Senior engineer15018 (12%)
Enterprise team16723 (14%)

What CARTO was up against

The full ranking in maps, from the same sessions:

#ProductRuns wonShare
1Google Maps11917%
2Leaflet11917%
3Apple Maps (MapKit)9714%
4MapLibre588%
5Built in-house (no product adopted)436%
6Mapbox426%
7react-native-maps355%
8OpenStreetMap355%

What this means

Raised 70 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 70 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 701 sessions in maps are part of a published set of 13,497, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.

Every maps run can be replayed on the board.

If you work on CARTO: 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 CARTO?

They raise it but do not choose it. Across 70 sessions where CARTO came up as a candidate, agents chose something else every time.

Does Claude Code recommend CARTO?

In 0 of the 164 sessions in maps run with Claude Code, which is 0%.

Do different coding agents treat CARTO differently?

Not much. Claude Code, Codex, Cursor, Grok Build CLI and Muse Code 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 91 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 13,497 judged sessions with Claude Code, Codex, Cursor, Grok Build CLI and Muse Code inside 91 realistic codebases, and published every run. The numbers on this page come from that work.

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