Podcast
vBrownBag
Hosted by vBrownBag · EN
vBrownBag.com is a community of people who believe in helping other people. Specifically we work in IT infrastructure and we help other people in the IT industry to better their careers through education. Most frequent activity is producing the vBrownBag podcast. vBrownBag also attends global conferences to produce TechTalks and theater sessions.
18episodes
Episodes
Newest firstAll episodes
Claude / Codex / Gemini / Open-model Gen AI from Zero with Andrew Brown
2w ago00:59:54Tap to summarizeAndrew Brown (ExamPro) joins the vBrownBag crew to talk Gen AI skills, bootcamps, and whether vibe coding has made "learning to code" irrelevant. 🤖 Spoiler: it hasn't. Andrew walks through his upcoming Cloud Code Camp, demos agentic workflows he's built using Claude Desktop and Claude Code, and breaks down how to actually think about coordinator patterns, MCPs, and token-efficient development. 💡 The crew also gets into the "coders are obsolete" debate, AI-assisted JRPG game development, and whether AI certifications are worth your time in 2026. 🎮 Chapters: 00:00:01 - Andrew Brown, Classified Backstories, and Gen AI Fatigue 00:08:45 - Cloud Code Camp: Who It's For and What You'll Actually Build 00:15:38 - Building MCPs and Agentic Workflows with Claude Desktop and Claude Code 00:32:22 - Vibe Coding, Junior Devs, and Why Technical Skills Still Matter 00:54:03 - Are AI Certifications Worth It in 2026? #GenAI #CloudComputing #AIAgents #ExamPro #vBrownBag
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Survive & Thrive: Skills for Techs in 2026 with Stephen Sennett
2w ago01:01:33Tap to summarizeAWS Hero Stephen Sennett joins the vBrownBag crew to argue that foundational knowledge matters more now, not less. 🧠 They dig into why communication skills have become a functional technical requirement, 💬 how to build a T-shaped career that AI can't commoditize, and where LLMs still fall completely flat. 🤖 There's a live car wash prompt test 🚗, an honest AGI reality check, and a look at how junior and senior expectations are shifting in the cloud careers era. ☁️ Worth the watch for anyone mapping out their tech skills strategy for 2026. Chapters: 00:01:35 - Why Foundational Knowledge Is Your Advantage in the AI Era 00:12:50 - Communication Is Now a Technical Requirement (AI Proves It) 00:20:07 - T-Shaped Skills, Learning in Public, and Standing Out in Cloud Careers 00:34:46 - What AI Still Can't Do: The AGI Reality Check and Car Wash Test 00:49:20 - How AI Is Reshaping Junior, Mid, and Senior Dev Expectations #CloudComputing #AWS #TechCareers #AISkills #vBrownBag
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Getting Started with Local AI
Apr 2101:17:47Tap to summarizeJoin us for Part 1 of a 3-part series as Du'An Lightfoot (Senior AI Engineer at Akamai) breaks down everything you need to know to get started running AI models locally on your own hardware. Du'An walks through the fundamentals of local AI - from understanding why you'd want to run models privately (data ownership, air-gapped environments, IP protection) to the hardware concepts that make it possible. You'll learn how inference actually works under the hood, why GPUs matter for AI workloads, how to choose and quantize models for your hardware, and how to get up and running with tools like Ollama. This is Part 1 of a 3-part series - future episodes cover serving models via API and distributing inference at the edge with Kubernetes. Timestamps 0:00 Cold Open: Why Local AI? 0:26 Welcome & Introduction 1:30 Following Up on the Frontier Models Episode 2:25 Du'An's Background & AI Inference at Akamai 3:49 What If You Wanted to Own Your Data? 5:00 Local AI vs Cloud AI: A Different Layer of the Stack 5:47 Why GPUs Matter: The Nvidia Story 7:03 CPU vs GPU: Serial vs Parallel Processing 8:28 Model Weights & Quantization Explained 12:45 Choosing the Right Model for Your Hardware 18:22 Getting Started with Ollama 24:16 Live Demo: Running Your First Local Model 30:41 Hardware Recommendations & Requirements 36:52 Hugging Face & Finding Models 42:18 Performance Tips & Benchmarking 48:35 Use Cases: When to Go Local vs Cloud 1:01:30 Live Demo: Claude Put-in-Work Repo 1:11:17 Bonus: Building a Deck with Co-work Live 1:16:36 Preview: Episodes 2 & 3 1:17:17 Wrap-up How to find Du'An: https://www.duanlightfoot.com/ https://github.com/labeveryday/ Links from the show: https://ollama.com/ https://apxml.com/ https://localllm.in/ https://huggingface.co/ https://github.com/labeveryday/claude-put-in-work https://claude.ai/
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AI for Good
Apr 2000:37:52Tap to summarizeJoin us as Kira Intrator (MIT-trained urban planner, systems thinker, and social impact technologist based in Geneva) makes the case that AI for Good isn't failing because of models - it's failing because of systems. Kira walks through why so many AI pilots never reach deployment, drawing on her experience building tools scaled across 9,000 users, three ministries, and six countries in Central Asia. You'll learn the five factors that kill AI projects in the development sector, why 80% of clinical AI models are trained on data that can't be deployed outside Western contexts, and what the $2.6 trillion opportunity in developing markets actually requires to unlock. This episode is equal parts systems thinking masterclass and call to action - a rare perspective from someone who has moved AI from prototype to production in places most tech professionals never consider. Timestamps 0:00 Welcome & Introduction 2:47 Kira's Background: MIT, Geneva, Central Asia 3:54 The Core Thesis: It's About Systems, Not Models 5:20 AI is Our Generation's Revolution 6:35 The $2.6 Trillion Opportunity 7:17 The 80% Western Data Problem 8:20 Why AI Projects Fail in Development: 5 Factors 9:28 Systems Mismatch & Low-Bandwidth Environments 9:52 Built for Pilot vs. Built for Deployment 10:29 Ownership, Economics & Sustainability 18:22 Real-World Case Studies 24:16 What Actually Works: Levers for Scale 30:41 The Role of Tech Companies & Foundations 33:39 Crystal Ball: Merging the Two Universes 35:01 A Call to Action 38:48 Wrap-up How to find Kira: https://www.linkedin.com/in/kiraintrator/ Links from the show: Infrastructure & Platforms Anthropic Beneficial Deployments: https://www.anthropic.com/ Google Research Global South Labs: https://research.google/ Lelapa AI: https://lelapa.ai/ Microsoft AI for Good: https://www.microsoft.com/en-us/ai/ai-for-good OpenAI Foundation: https://openai.com/ Research & Innovation Hubs Data Science Africa: https://www.datascienceafrica.org/ Masakhane: https://www.masakhane.io/ Stanford HAI: https://hai.stanford.edu/ Wadhwani AI: https://www.wadhwaniai.org/ Global Governance & Policy OECD AI Observatory: https://oecd.ai/ UNICEF Office of Innovation: https://www.unicef.org/innovation/ World Health Organization AI: https://www.who.int/ Funders & Philanthropies Gates Foundation: https://www.gatesfoundation.org/ Patrick J. McGovern Foundation: https://www.mcgovern.org/ Conferences AI for Good Global Summit (July 7-10, 2026 - Geneva): https://aiforgood.itu.int/ Data Science Africa 2026 (July 20-24 - Kampala, Uganda): https://www.datascienceafrica.org/ Deep Learning Indaba 2026 (August 2-7 - Lagos, Nigeria): https://deeplearningindaba.com/
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700,000 Learners Later: AWS Education Community and What's Changed
Apr 1800:44:51Tap to summarizeJoin us as Hiroko Nishimura (AWS Hero, LinkedIn Learning Instructor, and author of AWS for Non-Engineers) reflects on seven years of teaching cloud to 700,000 learners - what she's learned about learning, and how AWS education has changed. Hiroko walks through the evolution of AWS certification content, what changed when the Cloud Practitioner exam shifted focus, and her honest take on the industry's move away from non-engineer focused learning. You'll hear her best advice for anyone wanting to build a career in tech through content creation, why you only need to be 1-2 steps ahead to start teaching others, and how community has shaped her entire journey. This episode is equal parts AWS education deep dive and career inspiration - whether you're studying for your first cert or wondering how to break into the cloud community, Hiroko's 700,000-learner perspective is exactly what you need to hear. Timestamps 0:00 Welcome & Introduction 1:42 How We Get to 700,000 Learners 3:37 The 22 Courses Explained 6:15 How AWS Cloud Practitioner Has Changed 7:31 The Shift Away from Non-Engineer Focus 12:45 What Actually Changed in the Exam Content 18:22 Hiroko's Teaching Philosophy 24:16 How AI Has Changed the Learning Landscape 30:41 Community Building & AWS Heroes 35:00 Content Creation as a Career Strategy 39:02 Key Takeaways: You Only Need to Be 1-2 Steps Ahead 41:08 The Origin Story: 700,000 Learners from One Study Blog 44:02 Wrap-up & Where to Find Hiroko How to find Hiroko: https://www.linkedin.com/in/hirokonishimura/ https://hirokonishimura.com/ https://hiroko.io/ Links from the show:
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Uncovering the Hard Truth of Vendor Neutrality in OTEL
Apr 700:50:10Tap to summarizeJoin us as Josh and Adriana call BS on the oversimplified vendor neutrality narrative - because switching observability vendors isn't magic, even with OpenTelemetry. Josh and Adriana walk through the hard truths about OTel vendor neutrality using their favorite analogy: switching from iOS to Android because vCard exists. Sure, your contacts will move, but what about everything else? You'll learn what vendor neutrality actually means in production, why vendor-neutral instrumentation still matters (your code artifacts survive tool changes), the real challenges and pitfalls of switching vendors, and best practices to make the process as pain-free as possible. This episode cuts through the hype with honest talk about what works, what doesn't, and why OpenTelemetry is still valuable even when it's not a magic wand. Timestamps 0:00 Welcome & Introduction 3:32 Getting Into the Talk 4:28 Origin Story: From LinkedIn Post to Full Presentation 5:35 Standards We Love: USB-C, Stop Signs, McDonald's 8:00 The No Name Brand Analogy 12:45 What Vendor Neutrality Actually Means 18:22 The iOS to Android / vCard Comparison 24:16 What You Lose When Switching Vendors 30:41 Why Vendor-Neutral Instrumentation Matters 36:52 Real Challenges & Pitfalls 42:18 Best Practices for Switching 46:17 Shameless Self-Promotion & Resources 49:03 Wrap-up How to find Josh & Adriana: https://www.linkedin.com/in/joshuamlee/ https://www.linkedin.com/in/adrianavillela/ Links from the show: https://opentelemetry.io/
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Troubleshooting AWS Hallucinations from Vector Store DBs
Mar 500:48:04Tap to summarizeJoin us as Amelia shares the debugging story nobody tells you about - how her vector store DB couldn't surface specific data until she tested it with simplified data from ChatGPT. Amelia walks through her journey from throwing JIRA tickets into a large language model without understanding pipelines or data cleaning, to discovering why her production vector store was failing. You'll learn about the gap between chatting with data and getting accurate connections, how to validate vector similarity search results, the difference between production and synthetic test data, and practical troubleshooting workflows for AWS vector stores. This episode reveals the messy reality of RAG systems - when everything seems fine but the outputs are subtly wrong, and how testing with simplified data can expose what production complexity hides. Timestamps 0:00 Cold Open 1:03 Welcome & Introduction 2:06 Amelia's Background & DeepRacer Trophy 4:49 The JIRA Ticket Use Case Origin Story 5:53 Getting Into the Presentation 6:03 Accessing & Cleaning Data Sets 8:12 Losing Production Data & Recreating with ChatGPT 12:45 Understanding Vector Databases 18:22 How Embeddings Work 24:16 The Hallucination Discovery 30:41 Testing Strategies for Vector Stores 36:52 Debugging Vector Similarity Search 42:18 Real-World Troubleshooting Workflows 44:26 Where to Find Amelia & Wrap-up How to find Amelia: https://www.linkedin.com/in/ameliahoughross/
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AI Agents Made Simple: Everything You Need to Know
Feb 2701:09:21Tap to summarizeJoin us as Du'An breaks down AI agents in a way that actually makes sense - what they are, how to use them, and how to get started today. Du'An walks through the fundamentals of AI agents with live demos and practical code examples you can use immediately. You'll learn about agent frameworks, when to use agents versus simple LLM calls, building your first agent, and real-world applications from bookmark management to automated workflows. This episode cuts through the hype with realistic expectations about what agents can and can't do, while showing you concrete examples including MCP servers, Strands Pack, and Du'An's personal second brain system. Timestamps 0:00 Welcome & Introduction 1:39 Du'An's Background & Previous Episode Success 3:06 Segueing from Last Week's Episode 4:03 CEOs Vibe Coding Discussion 6:49 Real Estate Developer Building Apps Story 8:23 Getting Started with the Presentation 12:45 What Are AI Agents? 18:22 Agent Frameworks Overview 24:16 When to Use Agents vs Simple LLM Calls 30:41 Building Your First Agent 36:52 Live Demo: Strands Pack 42:18 MCP Servers Explained 47:35 WriteStats MCP Demo 52:14 Real-World Applications 58:33 Du'An's Second Brain System 1:04:01 Bookmark Manager Walkthrough 1:07:17 Organizing Cloud Storage & Email 1:09:06 Wrap-up & Next Episode Teaser How to find Du'An: https://www.duanlightfoot.com/ https://github.com/labeveryday/ Links from the show: https://github.com/labeveryday/strands-pack https://github.com/labeveryday/writestat-mcp https://github.com/labeveryday/bookmark-manager-site https://bookmarks.duanlightfoot.com/ https://github.com/openai/whisper https://openai.com/index/whisper/
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This is Fine: Tech Employment in the AI Era
Feb 20Tap to summarizeJoin us as Chris gets brutally honest about tech employment in the AI era: what's dying, what's thriving, and how to position yourself to survive the chaos. Chris walks through the current state of tech layoffs hitting record numbers while companies post record profits, the disappearance of entry-level roles, and practical strategies for navigating this unprecedented moment. You'll learn about skill development in the AI era, why fundamentals still matter more than hype, how to build resilience through community, and what hiring managers are actually looking for right now. This episode doesn't sugarcoat the challenges from hollowed-out expertise at major companies to early-career professionals wondering if their degree still matters, but it also provides actionable guidance on positioning yourself and why humor and human connection remain irreplaceable in an AI-driven world. Timestamps 0:00 Welcome & Setting the Tone 3:09 Chris Miller's Background & Journey 7:30 The Current State of Tech Employment 12:45 Layoffs vs Record Profits Discussion 18:22 Entry-Level Roles Disappearing 24:16 What Skills Actually Matter Now 30:41 Building Career Resilience 36:52 The Fundamentals Still Win 42:18 Community & Support Networks 47:35 Practical Job Search Strategies 52:14 What AI Can't Replace (Yet) 55:06 Things We're Thankful For 59:00 Wrap-up & Resources How to find Chris: https://www.linkedin.com/in/chris-t-miller/ https://www.chrismiller.com/ Links from the show: https://roadmap.sh
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AI Governance for Virtualized Infrastructure: What vSphere Admins Need to Know
Feb 1600:59:22Tap to summarizeJoin us as Marian explains what AI governance means for vSphere administrators and why it matters now. Marian walks through practical governance frameworks that vSphere admins need to understand, from IEEE 7000 series standards to mapping governance controls onto infrastructure you already manage. You'll learn what your CISO will ask for, how to respond using your existing VMware stack, and why governance isn't about slowing innovation - it's about enabling it safely. This episode covers real-world scenarios from data lineage and model transparency to integrating governance tools with existing infrastructure, and addresses the gap between compliance requirements and practical implementation for virtualized environments. Timestamps 0:00 Welcome & Introduction 5:16 Marian's Background in Tech & Governance 6:37 What is Governance? 12:45 IEEE 7000 Series Standards Overview 18:22 AI Governance for vSphere Admins 24:16 Data Lineage & Model Transparency 30:41 Risk Assessment Frameworks 36:52 Practical Implementation Strategies 42:18 Integration with Existing Tools 47:35 Common Governance Challenges 51:12 Vendor Landscape Discussion 54:27 Missing Innovation in the Space 58:09 Wrap-up & Resources How to find Marian: https://www.linkedin.com/in/mariannewsome/ Links from the show: https://ethicaltechmatters.com/
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