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Tag: implementation detail

  • Tomasz Tunguz: OpenAI Calls Codex a Senior Engineer

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    Kurt Seifried
    in

    Source URL: https://www.tomtunguz.com/openai-calls-codex-a-senior-engineer/ Source: Tomasz Tunguz Title: OpenAI Calls Codex a Senior Engineer Feedly Summary: For two years, Silicon Valley repeated the same mantra : AI agents are junior engineers. They need supervision. They handle routine tasks but struggle with complex problems. Then Thibault, OpenAI’s Codex team lead, delivered a line that broke the pattern…

  • Simon Willison’s Weblog: CompileBench: Can AI Compile 22-year-old Code?

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Sep/22/compilebench/ Source: Simon Willison’s Weblog Title: CompileBench: Can AI Compile 22-year-old Code? Feedly Summary: CompileBench: Can AI Compile 22-year-old Code? Interesting new LLM benchmark from Piotr Grabowski and Piotr Migdał: how well can different models handle compilation challenges such as cross-compiling gucr for ARM64 architecture? This is one of my favorite applications of…

  • Docker: How to Build Secure AI Coding Agents with Cerebras and Docker Compose

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    Kurt Seifried
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    Source URL: https://www.docker.com/blog/cerebras-docker-compose-secure-ai-coding-agents/ Source: Docker Title: How to Build Secure AI Coding Agents with Cerebras and Docker Compose Feedly Summary: In the recent article, Building Isolated AI Code Environments with Cerebras and Docker Compose, our friends at Cerebras showcased how one can build a coding agent to use worlds fastest Cerebras’ AI inference API, Docker…

  • Docker: Secure by Design: A Shift-Left Approach with Testcontainers, Docker Scout, and Hardened Images

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    Kurt Seifried
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    Source URL: https://www.docker.com/blog/a-shift-left-approach-with-docker/ Source: Docker Title: Secure by Design: A Shift-Left Approach with Testcontainers, Docker Scout, and Hardened Images Feedly Summary: In today’s fast-paced world of software development, product teams are expected to move quickly: building features, shipping updates, and reacting to user needs in real-time. But moving fast should never mean compromising on quality…

  • Simon Willison’s Weblog: llama.cpp guide: running gpt-oss with llama.cpp

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/19/gpt-oss-with-llama-cpp/ Source: Simon Willison’s Weblog Title: llama.cpp guide: running gpt-oss with llama.cpp Feedly Summary: llama.cpp guide: running gpt-oss with llama.cpp Really useful official guide to running the OpenAI gpt-oss models using llama-server from llama.cpp – which provides an OpenAI-compatible localhost API and a neat web interface for interacting with the models. TLDR version…

  • Cloud Blog: An efficient path to production AI: Kakao’s journey with JAX and Cloud TPUs

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/infrastructure-modernization/kakaos-journey-with-jax-and-cloud-tpus/ Source: Cloud Blog Title: An efficient path to production AI: Kakao’s journey with JAX and Cloud TPUs Feedly Summary: When your messaging platform serves 49 million people – 93% of South Korea’s population – every technical decision carries enormous weight. The engineering team at Kakao faced exactly this challenge when their existing…

  • Docker: Building AI agents made easy with Goose and Docker

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    Kurt Seifried
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    Source URL: https://www.docker.com/blog/building-ai-agents-with-goose-and-docker/ Source: Docker Title: Building AI agents made easy with Goose and Docker Feedly Summary: Building AI agents can be a complex task. But it also can be a fairly simple combination of answers to the following questions:  What is the AI backend that powers my intelligent fuzzy computation? What tools do you…