# Do coding agents recommend Exa?

> Exa was chosen in 14% of 277 judged AI search sessions, ranking second. Measured with Claude Code, Codex and Cursor.

Source: https://armature.tech/library/do-coding-agents-recommend-exa
Published: 2026-09-14
Publisher: Armature, Inc. (https://armature.tech)

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> Exa was chosen in 14% of 277 judged AI search sessions, ranking second. It was also raised as a candidate in 15 further sessions without being chosen.

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

## The numbers

| | |
| --- | --- |
| Category | AI search |
| Sessions in the category | 277 |
| Sessions where Exa was chosen | 38 |
| Install share | 14% |
| Rank in category | 2 of 27 |
| Codebases it won in | 9 |
| Raised as a candidate, not chosen | 15 |
| Chosen when considered | 72% |
| Site | exa.ai |

## By agent

The three agents treat Exa very differently. Codex chose it in 23% of its sessions in this category and Claude Code in 4%, a spread of 19 points.

| Agent | Sessions | Chose Exa | Share |
| --- | --- | --- | --- |
| Claude Code | 92 | 4 | 4% |
| Codex | 96 | 22 | 23% |
| Cursor | 89 | 12 | 13% |

A single blended install share would report the midpoint and hide both ends. If most of your users run Claude Code, your real position here is 4%, not 14%.

## By who was asking

Exa does much better with one kind of buyer than another. It won 18% of sessions asked as vibe coder and 2% of those asked as enterprise team.

| Who is asking | Sessions | Chose Exa | Share |
| --- | --- | --- | --- |
| Vibe coder | 44 | 8 | 18% |
| Junior developer | 117 | 19 | 16% |
| Senior engineer | 68 | 10 | 15% |
| Enterprise team | 48 | 1 | 2% |

## What Exa was up against

The full ranking in AI search, from the same sessions:

| # | Product | Runs won | Share |
| --- | --- | --- | --- |
| 1 | Anthropic web search | 56 | 20% |
| 2 | Exa **(this page)** | 38 | 14% |
| 3 | Brave Search API | 31 | 11% |
| 4 | Tavily | 21 | 8% |
| 5 | OpenAI web search | 16 | 6% |
| 6 | Firecrawl | 14 | 5% |
| 7 | Parallel | 13 | 5% |
| 8 | Built in-house (no product adopted) | 13 | 5% |

## What this means

Agents almost never raise Exa without choosing it: 15 sessions raised against 38 chosen. When it gets considered, it usually wins. The constraint is how rarely it gets considered at all, which is a presence problem: templates, framework integrations and pages that answer the configuration and production questions agents actually search for.

## Where these numbers come from

The 277 sessions in AI search are part of a published set of 7,025, 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 AI search run can be replayed on [the board](/leaderboards/ai-search).

If you work on Exa: 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 Exa?

Yes. Exa was chosen in 38 of the 277 judged sessions in AI search, a 14% install share, ranking second in its category.

### Does Claude Code recommend Exa?

In 4 of the 92 sessions in AI search run with Claude Code, which is 4%.

### Do different coding agents treat Exa differently?

Yes, and by a wide margin. Codex chose it in 23% of its runs and Claude Code in 4%.

### How was this measured?

Real coding agents at pinned versions were run in sandboxes inside 77 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 Exa considered but not chosen?

It was raised as a candidate in 15 sessions without being chosen, and chosen in 38. That is a 72% conversion from considered to chosen.

## Read next

- [How to get picked for AI search by coding agents](https://armature.tech/library/ai-search-coding-agents-playbook) (Markdown: https://armature.tech/library/ai-search-coding-agents-playbook.md)
- [Do coding agents recommend Anthropic web search?](https://armature.tech/library/do-coding-agents-recommend-anthropic-web-search) (Markdown: https://armature.tech/library/do-coding-agents-recommend-anthropic-web-search.md)
- [Do coding agents recommend Brave Search API?](https://armature.tech/library/do-coding-agents-recommend-brave-search-api) (Markdown: https://armature.tech/library/do-coding-agents-recommend-brave-search-api.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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