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# Enterprise AI benchmarks are broken

**[The New Stack](https://daily.dev/sources/newstack)** · 9 min read · 0 upvotes · 0 comments

## Summary

DevRev has open-sourced an Enterprise AI Agent Benchmark that tests AI agents on messy, permission-controlled data at scale rather than exotic reasoning tasks. The benchmark uses a scale-invariant dataset modeled on a mid-size software company at four sizes (1x to 64x), scoring agents on precision, efficiency, and safety. DevRev's own agent, Computer, outperformed Claude Code by 22–35 accuracy points and used 3.4x fewer tokens on identical tasks using the same Opus model family — attributing the gap to data-retrieval architecture rather than model capability. The benchmark follows an L1–L4 autonomy framework borrowed from self-driving levels, with only L1 and L2 currently released. Critics may note that DevRev designed the benchmark around the exact problem its own architecture solves, though the dataset, harness, and traces are fully open-sourced for independent verification.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://thenewstack.io/enterprise-ai-benchmarks-are-broken>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#ai-agents](https://daily.dev/tags/ai-agents), [#mcp](https://daily.dev/tags/mcp)

[View this post on daily.dev](https://daily.dev/posts/enterprise-ai-benchmarks-are-broken-os7hvrdov)

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