Episódios

  • Network Engineers and Using AI Development Tools with Ryan Booth

    Network Engineers and Using AI Development Tools with Ryan Booth

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    Dedicated to the memory of Nick Russo. Your star was bright my friend and I wish we had more time together.

    A conversation with Ryan Booth, Engineering Manager at Juniper on AI development practices and related development tools.

    Episode Description

    Ryan Booth discusses his recent experiment building a complete application using AI assistance without writing code directly. He shares insights on managing AI development workflows, context management, testing practices, and practical tips for network engineers working with AI tools.


    Key Topics Discussed

    Building applications using Claude 3.5 Sonnet through Cline (VS Code extension)Managing AI context and token limits in developmentTesting and validation strategiesFrontend vs backend development experiences with AITroubleshooting techniques when working with AI


    Tools & Technologies Mentioned

    Claude 3.5 SonnetCline (VS Code extension)OpenRouterOllamaDeepSeek CoderLangChainLlamaIndexAnsibleRedis


    Key Points

    Break down development into focused tasks rather than trying to handle everything at onceMaintain proper documentation and context files in directoriesValidate and test at each step rather than waiting until the endUse Git for granular version control of AI-generated code


    Notable Quotes

    "I learned very early on when getting into the coding stuff that you can't overload it with information. You really have to kind of start just like you would a normal project. You have to build from the foundation up.""It's network automation is managing software at the end of the day. You're writing code that you have to rely on, that you have to test, that you have to validate."

    Resources

    Cline VS Code Extension: https://github.com/cline/cline
    Claude AI: https://claude.ai
    Claude AI Computer Use: https://www.anthropic.com/news/3-5-models-and-computer-use
    OpenRouter: https://openrouter.ai


    Episode Credits

    Host: Kirk Byers
    Guest: Ryan Booth
    Recorded December 3, 2024

  • Amplification of your Abilities, AI and Networking with John Capobianco

    Amplification of your Abilities, AI and Networking with John Capobianco

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    Summary

    In this podcast, Kirk Byers and John Capobianco discuss the impact of AI on network automation and engineering. They explore the significance of ChatGPT, the challenges of inference, and the concept of Retrieval-Augmented Generation (RAG). John shares insights on using LangChain for building AI applications, and the role of AI agents. The conversation emphasizes the importance of adapting to AI technologies and the potential for enhancing productivity in network engineering.

    Takeaways

    ChatGPT marked a significant turning point in AI awareness.Retrieval-Augmented Generation (RAG) enhances AI capabilities.LangChain simplifies the integration of AI with network tools.AI agents can automate complex tasks in network management.Fine-tuning models can improve AI performance in specific domains.AI can significantly reduce the time needed for project development.

    Chapters

    00:00 - Introduction to AI and Network Automation

    01:42 - The Impact of ChatGPT

    05:50 - Understanding Hallucinations and Inference

    09:53 - Retrieval-Augmented Generation (RAG) Explained

    14:42 - Building with LangChain

    18:37 - Exploring Models and Local LLMs

    22:55 - Exploring Fine-Tuning and RAG Techniques

    25:34 - Integrating AI with Network Data

    29:34 - The Rise of AI Agents

    34:28 - Modernizing Code

    39:53 - Future Directions for Network Engineers

    Reference Materials
    Selector https://www.selector.ai/
    John Capobianco YouTube Video on "Multi Agent AI for Network Automation" https://www.youtube.com/watch?v=8GwSIRGae10
    LangChain https://www.langchain.com/
    LlamaIndex https://www.llamaindex.ai/
    Streamlit https://streamlit.io/

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