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Your laptop is powerful enough to run your own LLM. Here's why that matters While centralized AI tools help teams, they miss something critical: your personal knowledge. Meeting notes, tips, tricks, and context only you have. Kyle Fransham shows how running a local LLM changes the game. Index your own "master document of knowledge" and query it right in your dev environment. No cloud needed. The tools are accessible. The setup is simple. And the impact? Game-changing for how you work.

In this episode of Masters of Data, we dive into how AI learns, examining both how we teach it and what it derives from human performance, as well as why context plays a crucial role in AI interactions. We break down five key components of AI training and talk about why we should view AI as a tool under human control rather than an autonomous entity. We explore the challenge of maintaining context in AI—much like our own memory struggles—and discuss methods, such as retrieval-augmented generation, that can help AI retain context more effectively.

Introducing Kentik AI Advisor. AI with a comprehensive understanding of your network that thinks critically and advises how to design, operate, and protect infrastructure at scale. With the rise of hybrid cloud networks and the growing demands of AI infrastructure, network teams are under pressure to balance cost, performance, and security, often with limited resources that delay critical strategic initiatives.

In this preview of his AWS re:Invent session, Cortex CTO & Co-Founder Ganesh Datta breaks down how AI coding assistants are transforming software development, and what high-performing teams are doing to keep speed and reliability in balance. You’ll learn: If you care about AI, engineering velocity, or building sustainable systems, this is a must-watch. Full Session: December 3 at 2:30 PM Learn more about Cortex: go.cortex.io/reinvent.