AI & ML
Multi-step SWE: Can Coding Agents Keep Building on Their Own Code Over Long Horizons?
arXiv cs.SE0 views
arXiv:2611.07166v1 Announce Type: new Abstract: Developers rarely give a coding agent a single request: they ask it to build a component and then to extend, upgrade, and optimize it, each time on code the agent itself wrote. Most benchmarks, however, score one task at a time. We introduce Multi-step SWE, a long-horizon benchmark of 69 software engineering tasks, each a chain of 5-15 dependent steps on a single codebase. Every step is a complete, multi-hour engineering request that starts from the code the agent produced in the preceding steps, so early design decisions and errors carry forward. The tasks span four families of engineering work and nine languages, include both from-scratch builds and existing open-source codebases, and ground every step in an existing source of truth that defines both the instruction and its verifier. Across nine frontier models, the strongest model reaches a solve rate of only 18.5%, and 38 of the 69 tasks are not solved by any model. We release Multi-step SWE publicly at https://multistepswe.com.
Source:https://arxiv.org/abs/2611.07166PreviousAutomatic Assistance to Reduce Information Overload during Software Issue Report UnderstandingNextSeVerus: Context-Aware, Gamified Benchmarking for Rust Verification
Related posts
Your AI Can Treat the Patient Perfectly and Still Not Know What They Have
0dev.to Python
Come incapsulare Codex CLI in Python come fa osFoundry
0dev.to Python
Data Pipelines Optimize for Throughput. AI Training Needs Determinism
0dev.to DevOps

Chicago-based data analytics company Ocient raised a $100M Series C co-led by Boka Capital and OCA Ventures to grow its agentic AI analytics business (Paul Gillin/SiliconANGLE)
0Techmeme
Surprise Google Antigravity usage limit reset
0Hacker News New
Show HN: We compressed a 31B video+audio diffusion model to 14B, 6 steps, INT8
0Hacker News New