Bito's AI Architect Boosts Claude Opus's task success rate by 35%
Bito's AI Architect has significantly improved the task success rate of the Claude Opus coding agent by 35%. The evaluation conducted on the SWE-Bench Pro benchmark demonstrated that incorporating deep system context enhances performance, especially in complex coding scenarios. This advancement allows for faster task completion and greater efficiency without increasing costs.
- ▪The task success rate for Claude Opus increased from 51.9% to 70.1% with the implementation of Bito's AI Architect.
- ▪Performance improvements are most notable in large codebases and multi-file changes, with success rates increasing by 3.8x and 4.5x respectively.
- ▪The average task duration decreased from 377 seconds to 300 seconds, and there were 25% fewer tool calls required per task.
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| Original publisher | Bito |
| Canonical URL | https://bito.ai/benchmarks/swe-bench-pro-evaluation/ |
| Publication time | Tue, 19 May 2026 10:02:03 +0000 |
| Retrieval time | 2026-05-19T10:04:57.575Z |
| Last seen | 2026-05-19T10:04:57.575Z |
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| Commercial reuse | May the content be reused commercially? | Not permitted |
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AI Architect tops SWE-Bench Pro A benchmark based evaluation of how deep codebase context improves coding agent success on large, complex, real world codebases. Evaluated on SWE-Bench Pro. Conducted by The Context Lab Start free See key results TASK SUCCESS RATE 51.9% Claude Opus 4.6 Without context 70.1% with system context LARGE CODEBASES 3.8x COMPLEX TASKS 4.5x Even advanced coding agents resolve fewer than 52% of tasks when changes span large codebases and require coordinated, multi-file updates. These long-horizon scenarios expose a gap in system-level reasoning that most coding agents lack today. This evaluation examines whether structured system context can close that gap.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Bito.
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