# Do coding agents recommend Inspect AI? > Inspect AI was chosen in 4% of 288 judged evals sessions, ranking fifth. Measured with Claude Code, Codex and Cursor. Source: https://armature.tech/library/do-coding-agents-recommend-inspect-ai Published: 2026-09-03 Publisher: Armature, Inc. (https://armature.tech) --- > Inspect AI was chosen in 4% of 288 judged evals sessions, ranking fifth. It was also raised as a candidate in 30 further sessions without being chosen. This page reports what happened when Claude Code, Codex and Cursor had to solve a problem in evals inside a realistic codebase. Not what a chat assistant says about Inspect AI. What an agent actually installed. One thing to read first: every one of those wins came from a **single codebase**. That is a result about one repository rather than about evals in general, and the splits below cannot separate the two. Treat them as a description of that repository. ## The numbers | | | | --- | --- | | Category | Evals | | Sessions in the category | 288 | | Sessions where Inspect AI was chosen | 12 | | Install share | 4% | | Rank in category | 5 of 9 | | Codebases it won in | 1 | | Raised as a candidate, not chosen | 30 | | Chosen when considered | 29% | | Site | inspect.aisi.org.uk | ## By agent With 12 wins spread across three agents, the rates below are small numbers and a difference between them is not yet a finding. They are here because the direction is worth knowing, not because the gap is established. | Agent | Sessions | Chose Inspect AI | Share | | --- | --- | --- | --- | | Claude Code | 96 | 3 | 3% | | Codex | 96 | 0 | 0% | | Cursor | 96 | 9 | 9% | ## By who was asking Inspect AI performs similarly across the four kinds of buyer, from 0% to 8%. That is unusual: the category leader changed with the persona in 14 of the 18 categories we measured. | Who is asking | Sessions | Chose Inspect AI | Share | | --- | --- | --- | --- | | Junior developer | 145 | 0 | 0% | | Senior engineer | 143 | 12 | 8% | ## What Inspect AI was up against The full ranking in evals, from the same sessions: | # | Product | Runs won | Share | | --- | --- | --- | --- | | 1 | Langfuse | 97 | 34% | | 2 | Built in-house (no product adopted) | 84 | 29% | | 3 | Promptfoo | 38 | 13% | | 4 | Arize Phoenix | 23 | 8% | | 5 | Braintrust | 18 | 6% | | 6 | Inspect AI **(this page)** | 12 | 4% | | 7 | LangSmith | 8 | 3% | | 8 | Helicone | 6 | 2% | ## What this means Inspect AI was raised in 30 sessions and chosen in 12. That ratio is balanced enough that the ceiling is presence rather than integration: the product converts reasonably when it is on the table, and it is not on the table often enough. ## Where these numbers come from The 288 sessions in evals 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](/library/how-we-measured-this). Every evals run can be replayed on [the board](/leaderboards/evals). If you work on Inspect AI: the judge recorded a reason for every session where it was raised and passed over. Those reasons are in the transcripts. ## Common questions ### Do coding agents recommend Inspect AI? Yes. Inspect AI was chosen in 12 of the 288 judged sessions in evals, a 4% install share, ranking fifth in its category. ### Does Claude Code recommend Inspect AI? In 3 of the 96 sessions in evals run with Claude Code, which is 3%. ### Do different coding agents treat Inspect AI differently? Not much. The three agents chose it at similar rates, between 0% and 9% 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. ### How often is Inspect AI considered but not chosen? It was raised as a candidate in 30 sessions without being chosen, and chosen in 12. That is a 29% conversion from considered to chosen. ## Read next - [How to get picked for evals by coding agents](https://armature.tech/library/evals-coding-agents-playbook) (Markdown: https://armature.tech/library/evals-coding-agents-playbook.md) - [Do coding agents recommend Langfuse?](https://armature.tech/library/do-coding-agents-recommend-langfuse) (Markdown: https://armature.tech/library/do-coding-agents-recommend-langfuse.md) - [Do coding agents recommend Promptfoo?](https://armature.tech/library/do-coding-agents-recommend-promptfoo) (Markdown: https://armature.tech/library/do-coding-agents-recommend-promptfoo.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) --- Armature helps software products get discovered and used by coding agents. 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