# Do coding agents recommend Amazon SNS?

> Coding agents raised Amazon SNS in 91 of 288 judged message queues sessions and chose it in none of them. Measured with Claude Code, Codex and Cursor.

Source: https://armature.tech/library/do-coding-agents-recommend-amazon-sns
Published: 2026-09-15
Publisher: Armature, Inc. (https://armature.tech)

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> Coding agents raised Amazon SNS in 91 of 288 judged message queues 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 message queues inside a realistic codebase. Not what a chat assistant says about Amazon SNS. What an agent actually installed.

## The numbers

| | |
| --- | --- |
| Category | Message queues |
| Sessions in the category | 288 |
| Sessions where Amazon SNS was chosen | 0 |
| Install share | 0% |
| Raised as a candidate, not chosen | 91 |
| Chosen when considered | 0% |
| Site | aws.amazon.com |

## Which agents raised Amazon SNS

Every agent considered it and none adopted it. Cursor raised it most often, in 35% of its message queues sessions.

| Agent | Sessions | Raised Amazon SNS | Chose it |
| --- | --- | --- | --- |
| Claude Code | 96 | 25 (26%) | 0 |
| Codex | 96 | 32 (33%) | 0 |
| Cursor | 96 | 34 (35%) | 0 |

## Which buyers it came up for

It surfaced most for requests written as senior engineer, in 77% of those sessions. Knowing which buyer already has the product in mind tells you which pages to fix first.

| Who is asking | Sessions | Raised it |
| --- | --- | --- |
| Vibe coder | 48 | 6 (13%) |
| Junior developer | 120 | 21 (18%) |
| Senior engineer | 48 | 37 (77%) |
| Enterprise team | 72 | 27 (38%) |

## What Amazon SNS was up against

The full ranking in message queues, from the same sessions:

| # | Product | Runs won | Share |
| --- | --- | --- | --- |
| 1 | Built in-house (no product adopted) | 49 | 17% |
| 2 | Apache Kafka | 39 | 14% |
| 3 | Amazon SQS | 27 | 9% |
| 4 | Service Bus | 24 | 8% |
| 5 | Laravel Queues | 20 | 7% |
| 6 | Amazon Kinesis | 19 | 7% |
| 7 | Cloudflare Queues | 19 | 7% |
| 8 | Cloud Tasks | 15 | 5% |

## What this means

Raised 91 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 91 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 288 sessions in message queues 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](/library/how-we-measured-this).

Every message queues run can be replayed on [the board](/leaderboards/message-queues).

If you work on Amazon SNS: 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 Amazon SNS?

They raise it but do not choose it. Across 91 sessions where Amazon SNS came up as a candidate, agents chose something else every time.

### Does Claude Code recommend Amazon SNS?

In 0 of the 96 sessions in message queues run with Claude Code, which is 0%.

### Do different coding agents treat Amazon SNS 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 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.

## Read next

- [How to get picked for message queues by coding agents](https://armature.tech/library/message-queues-coding-agents-playbook) (Markdown: https://armature.tech/library/message-queues-coding-agents-playbook.md)
- [Do coding agents recommend Apache Kafka?](https://armature.tech/library/do-coding-agents-recommend-apache-kafka) (Markdown: https://armature.tech/library/do-coding-agents-recommend-apache-kafka.md)
- [Do coding agents recommend Amazon SQS?](https://armature.tech/library/do-coding-agents-recommend-amazon-sqs) (Markdown: https://armature.tech/library/do-coding-agents-recommend-amazon-sqs.md)
- [Do Claude Code, Codex and Cursor pick the same tools?](https://armature.tech/library/do-claude-code-and-codex-agree) (Markdown: https://armature.tech/library/do-claude-code-and-codex-agree.md)

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Service: https://armature.tech/discoverability · Results: https://armature.tech/leaderboards/sectors · Contact: contact@armature.tech
