The Private AI Lab

Johan van Amersfoort

The Private AI Lab is a monthly podcast where we explore the future of Artificial Intelligence behind the firewall. Hosted by Johan from Johan.ml, each episode invites industry experts, innovators, and thought leaders to discuss how Private AI is reshaping enterprises, technology, and society. From data sovereignty to air-gapped deployments, from GPUs to governance — this podcast uncovers the real-world experiments, failures, and breakthroughs that define the era of Private AI. 🎙️ New episode every month. 🌐 More at Johan.ml

Episodes

  1. Vibe Coding: Productivity Hack or Production Nightmare?

    3 DAYS AGO

    Vibe Coding: Productivity Hack or Production Nightmare?

    Is vibe coding the ultimate productivity accelerator — or a fast track to 4AM production outages? In this episode of The Private AI Lab, Johan speaks with Andrew Morgan about the real state of vibe coding in 2026. They unpack the difference between vibe coding and vibe learning, explore the risks of blindly trusting AI-generated code, and debate whether this new wave of AI-native development is democratizing software engineering — or quietly lowering the bar. The conversation covers rogue agents, context window limits, guardrails, on-prem AI strategies, enterprise accountability, and why thinking might become the most important engineering skill of the next decade. This episode is for developers, platform engineers, architects, and anyone navigating AI-assisted software development. 00:00 – Welcome to The Private AI Lab 01:40 – Andrew’s biggest AI fail 03:00 – The sunken cost fallacy of prompting 04:45 – Rogue agents & expensive mistakes 06:30 – Skynet jokes (but not really) 07:20 – What is vibe coding? 09:00 – Trust, guardrails & blast radius 10:15 – The current tooling landscape 12:00 – Vibe coding inside teams 14:40 – Stack Overflow vs vibe coding 17:00 – Code completion on steroids 18:30 – Who’s using it most aggressively? 20:45 – Democratization or dilution? 23:00 – Accountability at 4AM 25:00 – Lazy engineers vs lazy vibecoders 27:00 – Debugging AI-generated code 30:00 – Crab dragons & technical debt 32:30 – DevOps knowledge & production readiness 35:00 – Human vs AI code reviews 37:30 – Private AI & vibe coding 40:00 – On-prem vs cloud agents 42:30 – Context windows & hallucinations 44:00 – The next 18 months 47:30 – Strong engineers vs weak engineers 49:30 – Security risks & red teaming 52:00 – Is thinking the new bottleneck? 54:00 – Final lab report & takeaways

    1h 7m
  2. #007 - From Zero to Agentic AI — All Before Your Coffee Gets Cold (with Tasha Drew)

    5 FEB

    #007 - From Zero to Agentic AI — All Before Your Coffee Gets Cold (with Tasha Drew)

    What if deploying private, enterprise-grade AI didn’t take months—but only as long as it takes your coffee to cool? In this episode of The Private AI Lab, Johan van Amersfoort sits down with Tasha Drew to unpack how Private AI Services on VMware Cloud Foundation are changing the way enterprises build and consume AI. They discuss why AI needs a platform layer, how Broadcom integrates open source responsibly, what MCP means for enterprise AI, and how agentic AI workloads can be deployed securely, governed properly, and operated at scale—inside the private cloud. If you like to follow Tasha, you can do that on linkedin:https://www.linkedin.com/in/tashy/ Topics covered Why “training” is the most misused AI term From zero to RAG and agentic AI in minutes Private AI Services and the VCF strategy Model runtime, API gateways, and GPU efficiency Data indexing & retrieval for enterprise RAG Open source trade-offs: speed vs flexibility MCP, tool usage, and governance How Broadcom uses its own AI platform internally The future of agents: specialists over monoliths If you like to follow Tasha, you can do that on linkedin:https://www.linkedin.com/in/tashy/

    57 min
  3. #006 - The Subtle Art of Inference with Adam Grzywaczewski

    22 JAN

    #006 - The Subtle Art of Inference with Adam Grzywaczewski

    In this episode of The Private AI Lab, Johan van Amersfoort speaks with Adam Grzywaczewski, a senior Deep Learning Data Scientist at NVIDIA, about the rapidly evolving world of AI inference. They explore how inference has shifted from simple, single-GPU execution to highly distributed, latency-sensitive systems powering today’s large language models. Adam explains the real bottlenecks teams face, why software optimization and hardware innovation must move together, and how NVIDIA’s inference stack—from TensorRT-LLM to Dynamo—enables scalable, cost-efficient deployments. The conversation also covers quantization, pruning, mixture-of-experts models, AI factories, and why inference optimization is becoming one of the most critical skills in modern AI engineering. Topics covered Why inference is now harder than training Autoregressive models and KV-cache challenges Mixture-of-experts architectures NVIDIA Dynamo and TensorRT-LLM Hardware vs software optimization Quantization, pruning, and distillation Latency vs throughput trade-offs The rise of AI factories and DGX systems What’s next for AI inference

    53 min
  4. #005 - The Why, What, and How of MCP with Maxime Colomès

    8 JAN

    #005 - The Why, What, and How of MCP with Maxime Colomès

    In this episode of The Private AI Lab, Johan van Amersfoort talks with Maxime Colomès about the Model Context Protocol (MCP)—one of the most important emerging standards in AI today. MCP is often described as the USB-C of AI: a universal way for AI models to connect to tools, data sources, and real-world systems. Maxime explains what MCP is, how it works, and why its recent donation to the Linux Foundation is such a major milestone for the AI ecosystem. They explore real-world enterprise use cases, MCP security considerations, private AI architectures, and how MCP integrates with platforms like OpenShift AI. The conversation also touches on developer productivity, AI agents that can take action, and the future of personal, privacy-preserving AI assistants. Key topics What the Model Context Protocol (MCP) is and why it matters MCP vs traditional APIs and plugin systems Enterprise MCP architectures and gateways MCP and private AI / data sovereignty OpenShift AI and MLOps workflows Security risks and best practices with MCP Community MCP servers and registries Future MCP use cases and predictions

    1h 3m
  5. #004 - The Past, Present, and Future of VMware Private AI Services with Frank Denneman

    23/12/2025

    #004 - The Past, Present, and Future of VMware Private AI Services with Frank Denneman

    In this episode of The Private AI Lab, Johan sits down with Frank Denneman to explore the past, present, and future of VMware’s Private AI portfolio. This conversation goes beyond AI buzzwords and marketing fluff. Together, Johan and Frank dive deep into the real infrastructure and resource management challenges that emerge when AI workloads enter enterprise environments. GPUs, scheduling, isolation, and platform design all take center stage—viewed through the lens of real-world VMware deployments. If you are an infrastructure architect, platform engineer, or IT decision-maker designing AI behind the firewall, this episode provides grounded insights into what actually matters. 🔍 What you’ll learn in this episode How VMware’s Private AI strategy has evolved over time Why AI workloads fundamentally change infrastructure assumptions The importance of resource management for GPU-backed workloads Key architectural trade-offs when running AI on-prem How to think about the future of enterprise AI platforms 🎧 Listen & Subscribe For more experiments, insights, and behind-the-firewall AI discussions, visit johan.ml. Experiment complete. Until the next one — stay curious.

    1h 1m
  6. #003 - OpenShift AI, DGX Spark & the Future of Private AI — with Robbie Jerrom (Red Hat)

    11/12/2025

    #003 - OpenShift AI, DGX Spark & the Future of Private AI — with Robbie Jerrom (Red Hat)

    This episode of The Private AI Lab features Robbie Jerrom, Principal Technologist AI at Red Hat, for a deep dive into Private AI, from the DGX Spark to OpenShift AI and the future of agentic systems. Topics we cover: How Robbie uses the DGX Spark for home-lab AI Why developers are moving from cloud GPUs to local devices OpenShift AI as a consistent platform from experiment to production The best open-source components for modern AI stacks Why 79% of POCs never reach production — and how to avoid that The next wave: agentic AI and enterprise automation Watch on YouTube: https://www.youtube.com/watch?v=jjyB8w_cpb0 More episodes & articles at johan.ml

    1h 3m
  7. #002 - DGX Spark Review — With Andrew Foe (Iodis & HyperAI)

    27/11/2025

    #002 - DGX Spark Review — With Andrew Foe (Iodis & HyperAI)

    In this episode of The Private AI Lab, Johan is joined by Andrew Foe, CEO of Iodis and HyperAI, to explore the NVIDIA DGX Spark from a real-world perspective. We cover: Unboxing & first impressions Bring-up and setup tips Everyday usability What customers love The most common misconceptions Why preorder demand exploded in the BeNeLux region A must-listen for anyone exploring Private AI hardware or considering the DGX Spark. 🎧 Watch on YouTube: https://www.youtube.com/watch?v=jENCTgcAWsI 💡 More experiments: https://johan.ml

    1h 1m
  8. #001 - Fast, Sovereign, and Local: What SUSE AI Taught Me in 40 Minutes

    13/11/2025

    #001 - Fast, Sovereign, and Local: What SUSE AI Taught Me in 40 Minutes

    In the premiere of The Private AI Lab, Johan van Amersfoort is joined by SUSE AI Specialist Eric Lajoie to talk about sovereign AI, deploying chatbots in under an hour, and the unexpected hazards of robotic dogs.Timestamps: 00:00 – Intro & guest welcome 01:04 – How to pronounce “Lajoie”? 02:00 – What Eric actually does at SUSE 05:14 – Eric’s AI fail: a very personal RAG demo 10:06 – What Private AI means to Eric 11:30 – How SUSE AI works (chatbots, Kubernetes, Rancher, and more) 21:30 – RAG architecture explained 26:00 – 40-minute SUSE AI deployment?! 31:00 – Real-world use cases (GPUaaS, observability, MCP) 39:00 – AI sovereignty in Europe 43:00 – Wrap-up & key takeaways 54:00 – Eric’s prediction for the next 12 months in AI 57:40 – Johan’s robot dog fail 60:00 – Outro + where to follow Eric 🔗 Links & Mentions • Learn more about SUSE AI: https://suse.com Follow Eric: https://www.linkedin.com/in/elajoie/ or lajoie.de Check out the companion post at https://johan.ml/ Related episode: When Shit Hits The Fan ft. Eric – https://open.spotify.com/episode/2IeLq8WT7eqMJPVkcUMg3G?si=eaf7a529a75e4078

    58 min

  9. 07/10/2025

    The Private AI Lab

    Welcome to The Private AI Lab — the podcast where we experiment, explore, and debate the future of Artificial Intelligence behind the firewall. I’m your host, Johan, and every month I invite a guest into the lab to break down real-world use cases, challenges, and innovations shaping Private AI. Brought to you by Johan.ml Be the first to know when a new episode drops, by subscribing to the podcast!

    1 min

Trailer

About

The Private AI Lab is a monthly podcast where we explore the future of Artificial Intelligence behind the firewall. Hosted by Johan from Johan.ml, each episode invites industry experts, innovators, and thought leaders to discuss how Private AI is reshaping enterprises, technology, and society. From data sovereignty to air-gapped deployments, from GPUs to governance — this podcast uncovers the real-world experiments, failures, and breakthroughs that define the era of Private AI. 🎙️ New episode every month. 🌐 More at Johan.ml

Information

  • Creator
    Johan van Amersfoort
  • Years Active
    2025 - 2026
  • Episodes
    9
  • Rating
    Explicit
  • Copyright
    © Johan van Amersfoort
  • Show Website
    The Private AI Lab