From the experiment

Do coding agents recommend Sentry Seer?

Sentry Seer is the most chosen ai sre, taking 26% of 179 judged ai sre sessions. Measured with Claude Code, Codex and Cursor.

Published September 15, 2026 Read as Markdown

Sentry Seer is the most chosen ai sre, taking 26% of 179 judged ai sre sessions. It was also raised as a candidate in 36 further sessions without being chosen.

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

The numbers

CategoryAi sre
Sessions in the category179
Sessions where Sentry Seer was chosen47
Install share26%
Rank in category1 of 26
Codebases it won in3
Raised as a candidate, not chosen36
Chosen when considered57%
Sitesentry.io

By agent

The three agents treat Sentry Seer very differently. Codex chose it in 32% of its sessions in this category and Cursor in 8%, a spread of 24 points.

AgentSessionsChose Sentry SeerShare
Claude Code712130%
Codex722332%
Cursor3638%

A single blended install share would report the midpoint and hide both ends. If most of your users run Cursor, your real position here is 8%, not 26%.

By who was asking

Sentry Seer does much better with one kind of buyer than another. It won 83% of sessions asked as vibe coder and 0% of those asked as enterprise team.

Who is askingSessionsChose Sentry SeerShare
Vibe coder302583%
Junior developer602237%
Senior engineer3000%
Enterprise team5900%

What Sentry Seer was up against

The full ranking in ai sre, from the same sessions:

#ProductRuns wonShare
1Sentry Seer (this page)4726%
2Resolve AI3520%
3Datadog Bits AI Dev Agent + Datadog Bits Investigation2615%
4Cursor Automations158%
5Claude Code GitHub Action116%
6Cursor Cloud Agents95%
7incident.io AI SRE42%
8Cursor Automations + Cursor Cloud Agents32%

What this means

Leading a category is a position to defend rather than a result to celebrate. In our data, leaders lose ground in exactly two situations: when the person asking is an enterprise buyer with procurement constraints, and when a competitor's documentation is easier for an agent to integrate correctly.

The defence is unglamorous. Keep the quickstart running. Keep the version current on the page. Keep the names aligned. Stay in the templates.

Where these numbers come from

The 179 sessions in ai sre are part of a published set of 7,852, run with real coding agents inside realistic codebases and judged blind. The full method is on one page: how we measured this.

Every ai sre run can be replayed on the board.

If you work on Sentry Seer: 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 Sentry Seer?

Yes. Sentry Seer was chosen in 47 of the 179 judged sessions in ai sre, a 26% install share, ranking first in its category.

Does Claude Code recommend Sentry Seer?

In 21 of the 71 sessions in ai sre run with Claude Code, which is 30%.

Do different coding agents treat Sentry Seer differently?

Yes, and by a wide margin. Codex chose it in 32% of its runs and Cursor in 8%.

How was this measured?

Real coding agents at pinned versions were run in sandboxes inside 90 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.

How often is Sentry Seer considered but not chosen?

It was raised as a candidate in 36 sessions without being chosen, and chosen in 47. That is a 57% conversion from considered to chosen.

Where this comes from

Armature ran 7,852 judged sessions with Claude Code, Codex and Cursor inside 90 realistic codebases, and published every run. The numbers on this page come from that work.

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