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SWE-Agent is an open-source software engineering agent with a 12.3% resolve rate on SWE-Bench! Check out SWE-agent in action at Repo:

carlos

1,348 subscribers

138,703 görüntüleme • 2 yıl önce •via X (Twitter)

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carlos2 yıl önce

The SWE-agent open-source repository provides a framework for turning general LMs into software engineering agents. SWE-agent lets LMs like GPT-4 interact with their own Docker container using an Agent Computer Interface (ACI) - allowing it to browse, search, edit, and run code.

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carlos2 yıl önce

It’s been amazing to work on this with such a great team: @jyangballin*, @_carlosejimenez*, @_awettig, @ShunyuYao12, @karthik_r_n, and @OfirPress Keep an eye out for the paper coming out April 10th!

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MindBranches2 yıl önce

Here is a overview of the new open source Software Engineering Agent (SWE-Agent):

Elman Mansimov profil fotoğrafı

Elman Mansimov2 yıl önce

@OfirPress Very cool!

Eddie Forson profil fotoğrafı

Eddie Forson2 yıl önce

Nice work! Already starred the repo. Will take a look at the code in the next few days 👌🏿

Harry Tormey 🇮🇪 | 🇺🇸| 🇺🇦 profil fotoğrafı

Harry Tormey 🇮🇪 | 🇺🇸| 🇺🇦2 yıl önce

Amazing work with SWE-Bench and now this! Thanks for publishing your research and the source to this!.

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Konisberg Heinrich2 yıl önce

Incredible!

Gopinathan A profil fotoğrafı

Gopinathan A2 yıl önce

Nice work!!

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Hadi2 yıl önce

Does it just work with anthropic and openai models right now?

Owen Campbell-Moore ✪ profil fotoğrafı

Owen Campbell-Moore ✪2 yıl önce

(OpenAI PM here!) Super cool! I'm curious, what changes to our models or APIs would have made this easier to build or would make it work better? 🤔

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"You'll see this in a big way with the software engineering agent." He points to SWE agents, where 50¢ of compute can yield "$500 / $5,000 of work." The SWE agent will be the first major impact that will make people think about the economy with shock.

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In <4 months, Ridges used an open, incentivized tournament to produce the top open-source coding agent. • It outperforms all open-source agentic systems on SWE-Bench • Beats closed models from billion-dollar labs • Was done with $0 VC funding

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🚀New Amazon Q Developer agent for software development is available to customers: This agent is based on a new agent architecture that has exciting results coming from the SWE-bench scores (on the full and verified benchmarks) representing AI models’ ability to resolve real-world coding problems. Interesting aspect of Q Agent is that with these newest updates, Q drove nearly 50% more successful coding tasks completed. What makes Q Dev Agent remarkable? The agent architecture is not just about using the best LLMs (which we do), but also giving the agent the ability to constantly explore multiple paths to find the best way to resolve a particular problem (and back tracking when it has reached dead end like a developer would do). Needless to say, we are just getting started on the developer agent and we are constantly pushing to advance our AI capabilities while maintaining quality, security, privacy, and reliability to keep Amazon Q Developer an innovative and trusted option available to our customers using agents for software development. We highlighted the results of our first SWE-bench submission of Amazon Q Developer back in June blog post; with these updates, our new agent resolves 51% more coding tasks than its previous iteration on the SWE-bench verified dataset, and 43% more on the full dataset. That’s the difference a few months make, and I can’t wait to share what our teams will deliver at re:Invent this December. Here's a quick demo showcasing our new Agent in action:

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28,946 görüntüleme • 1 yıl önce

Wave 9 is here: a frontier model built for software engineering. Introducing our new family of models: SWE-1, SWE-1-lite, and SWE-1-mini. Based on internal evals, it has performance nearing that of frontier models from the foundation labs. Available now, only in Windsurf!

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BREAKING 🚨: Github Copilot got an agent mode on VSCode, and the SWE agent integrated straight into github 👀 There you can assign an issue to Copilot, review PR and profit! 🤯

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How did we build & scale Replit Agent? Find out from a Replit AI engineer (and a good friend), James Austin ⠕ We chat about building Replit Agent, what makes a great SWE, and James' journey to becoming an AI engineer

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$I'm delighted to say that Genie, our fully automated SWE agent is finally GA. It achieves a new SOTA score on the SWE-Lancer benchmark earning $88k with a 49% resolution rate – significantly out-earning any frontier reasoning model, for a fraction of the cost. Genie can work with you, or fully autonomously, and integrates with all of the tools developers love to use. Go give it a try on I'd love to hear any feedback!$

I'm delighted to say that Genie, our fully automated SWE agent is finally GA. It achieves a new SOTA score on the SWE-Lancer benchmark earning $88k with a 49% resolution rate – significantly out-earning any frontier reasoning model, for a fraction of the cost. Genie can work with you, or fully autonomously, and integrates with all of the tools developers love to use. Go give it a try on I'd love to hear any feedback!

Alistair

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Introducing Fast Deep Coder by NinjaTech AI - a coding agent with its own cloud VM ‣ Sonnet-level capability (69.6% SWE-bench) ‣ 5–10x faster using Qwen3 Coder on Cerebras ‣ Runs in a persistent cloud VM, freeing up your laptop ‣ Native GitHub integration Try it here:

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I'm excited to share that we've built the world's most capable AI software engineer, achieving 30.08% on SWE-Bench – ahead of Amazon and Cognition. This model is so much more than a benchmark score: it was trained from the start to think and behave like a human SWE.

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Cursor, Windsurf … all cool. But @AugmentCode just dropped `Augment Agent` 200K context. Persistent memory. Deep tool integrations. ... and it just hit #1 on SWE-bench Verified (65.4% on real tasks). It’s kind of a big deal. Let me show you 🧵 ↓

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CFO Sarah Friar revealed that OpenAI is working on: "Agentic Software Engineer — (A-SWE)" unlike current tools like Copilot, which only boost developers. A-SWE can build apps, handle pull requests, conduct QA, fix bugs, and write documentation.

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Haider.

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📣 Introducing SWE-PolyBench: A new open-source multilingual benchmark for evaluating #AI coding agents SWE-PolyBench is the first benchmark to evaluate AI coding agents' ability to understand complex codebases, helping advance AI performance in the real world. Learn more. 👉

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