SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineering research paper summary (October 2026)

The SWE-agent paper shows that language model agents work better when they get tools designed for them, an agent-computer interface. Its open source implementation lets a model of your choice fix issues in real GitHub repositories autonomously.

The authors treat language model agents as a new kind of user and study how interface design affects their performance. SWE-agent gives the model commands to create and edit files, navigate repositories and run tests, and is evaluated on SWE-bench. The paper was published in May 2024 and revised in November 2024.

The repository is built and maintained by researchers from Princeton University and Stanford University. Its README notes that most current development has moved to mini-swe-agent, which the team now recommends. The repository is under the MIT license, had 20,433 stars and was updated on September 21, 2026.

• Explains how coding agents workThe paper describes which commands and feedback an agent needs to change code reliably. Engineering leads evaluating commercial coding agents can use it to ask better questions about how those tools see and edit a codebase.
• Fixes issues in repositoriesThe open source agent reads an issue, explores the repository, edits files and runs tests until it proposes a patch. Teams can try autonomous bug fixing on their own repositories with a model they already license.
• Benchmarks agent setupsSWE-agent ships batch mode for running on SWE-bench. Research and platform teams can compare models or prompts on the same tasks before choosing one for internal tooling.

• Introduced the term agent-computer interface for tools built for language model agents.
• Model-agnostic: works with the language model you choose.
• The team now recommends the simpler successor mini-swe-agent for new work.

The paper is freely available on arXiv, and the accompanying code runs on your own hardware in any country.

SWE-agent is research software. Running it sends your code to the model provider you configure, so check that provider's data terms. Agents execute commands, so run them in isolated environments and have people review every patch before merging.

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