Dagger
@dagger_io
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Dagger is an open-source runtime for composable workflows, ideal for AI agents and CI/CD.
Joined February 2021
Dagger 0.19 is out, with a LOT of improvements: - Better performance (more on the way!) - Run Dagger without Docker - Local container export - First-class support for codegen workflows - Build-an-agent! Run tiny coding agents directly in your workflows, with perfect context 🧵
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A Folding Chair Made for Simple, Round Dining Tables Keeping only the chairs you need around a round dining table makes the room feel open and uncluttered. When guests arrive, you can simply unfold additional chairs that have been stored away — quick, easy, and seamless. By
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Docker is overkill for running AI agents in parallel. @Dagger_io’s new Container Use is a much simpler, agent-first alternative: → No Dockerfile needed → Git-native isolation → Full logs & real‑time visibility + easy one-liner commands to do it all! 🙌 Let’s compare 🧵↓
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@mayfer Look into @dagger_io! I just played around with it a little bit but its amazing what you get for free when you just base things from containers
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How to run multiple isolated coding agents locally. Featuring the open source Container Use by @dagger_io.
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Here's a live demo. Dagger and @jfrog , working together to secure your software supply chain💪 https://t.co/N0Jv2Bd8Ce
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Dagger is a proud launch partner for this fresh take on Evidence Collection by @jfrog . If you used Dagger to integrate your artifacts, JFrog will automatically include a complete Dagger trace as evidence. Every detail of your build and test execution, available for audit.
SDLC audits are a manual headache. That's why we’re thrilled to announce a major evolution to our Evidence Collection solution, partnering with industry-leading vendors to automate the collection of attestations. Streamline your audit trail and simplify #DevGovOps. Learn more:
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7 KEY QUESTIONS FOR 2026 Let’s look at 7 themes that could define 2026. 1️⃣ CapEx spend by the Big Four: CapEx at $AMZN, $MSFT, $GOOGL, $META has tripled from 2020 to 2025 and is nearing $0.5T annually. How much positive surprise is left in 2026?
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@CloudNativeFdn A really simplified difference between a normal chat vs agentic chat by @solomonstre #KCDBayArea
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This is pretty much dagger 101 ; so i feel a bit bashful @dagger_io 's wonderful Miranda Carter turned this tweet into a case study. Hoping more people get to have this "aha" moment.. case study: https://t.co/AX4r46U97h
I used @dagger_io for the first time to build binaries for Windows AMD64, macOS ARM64, Linux AMD64, and Linux ARM64— and wow, what a delight. Being able to run and iterate on each platform build locally is a huge improvement over the usual "push to GitHub and wait for CI" loop.
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CI/CD shouldn’t feel like running through quicksand. 🐌 Andy cut pipeline feedback from 30 minutes to seconds with Dagger, and now ships cross-platform builds faster than ever. 🚀 🎥 Watch his story: https://t.co/gOpqRV11Ma
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Lowest price for USA-made 100% organic cotton shorts @ATGUSAMade I hope these inspire someone out there to build closer to home, wherever that is.
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CI/CD but faster ⚡ At our August meetup, 🔹 Jason @dagger_io → pipelines as code 🔹 Harsh @localstack → AWS emulation inside pipelines Get hands-on with Dagger + LocalStack (Cloud Pods, Ephemeral Instances). Ship faster. Break less. 📅 RSVP: https://t.co/6YqfjdszlO
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Catch @solomonstre at #GopherCon NYC! Talk: Demystifying AI Agents ✔️ What’s real vs hype ✔️ Cross-language opportunities ✔️ Live coding demo Walk away thinking: “I can build this too!” 🚀 🗓 9:35–10:00 AM EDT | August 27th
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Building full-stack apps with LLMs? 🤖⚡ In this demo, Igor Rekun from https://t.co/TWz8f3HFhn (built by @neondatabase/@databricks) shows how they use Dagger to: ✅ Run agent completions in parallel ✅ Sandbox & cache experiments locally ✅ Validate results with built-in checks
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arrancando el 2do Neurona 🇦🇷: @marcosnils muestra container-use de @dagger_io que es? un MCP server que le da a tus coding background agents el entendimiento de “distintos entornos”
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