I got addicted to AI. Now I use it to dub my YouTube videos into other languages automatically. Built a CLI that handles everything - upload, dubbing, translation, scheduling. Here's how I integrated ElevenLabs API into my workflow 🎬 https://youtu.be/_tvKc9kKrhA

AI agents are unpredictable by design. The LLM decides the path, chooses tools, loops as needed. You can't debug what you can't see. Good news: OpenTelemetry tracing works for AI agents too. New video explains how. https://youtu.be/Dh7jAYHcAlo

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I wrote a simple prompt. Port's MCP provided the context. Claude Code did the rest. Result? A fully configured developer portal with K8s integration, GitHub sync, and self-service actions. AI + the right context = 🔥 https://youtu.be/6r6ITHCYZ3c

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Most Dockerfiles in production are security nightmares: running as root, using :latest tags, copying secrets. Writing a good Dockerfile isn't hard, you just need to know the rules. Here's every best practice you need for production-ready containers 🐳 https://youtu.be/ueTe-VQaD7c

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Your API is a product. Who's using it? Are they abusing it? Should they even have access? New video on API Management: developer portals, analytics, versioning, monetization with Zuplo review 😤 https://youtu.be/mOy2mhKE2_8

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2025: AI agents went from experiment to reality. 2026: Time to take them seriously. Here are the tools that survived real-world use—from Claude Code to the BACK Stack. 🔧🤖 https://youtu.be/65o_j4E7_lk

"What's the status of my app?" should be a simple question. In Kubernetes, it means checking Deployments, Ingresses, databases, PVCs separately. 😤 I fixed this with a Solution CRD that shows unified status for logical resource groups. https://youtu.be/UEkhIMx6B6E

My team had everything: more money, more experience, control over the rules. But when AI entered the game, most refused to play. They sat on the bench yelling at those who tried. Sound familiar? ⚽🤖 Watch the full story: https://youtu.be/ZEB2pKs2R-Q

Your logs show everything succeeded. Your metrics are green. But requests are still slow. The problem? Each service only sees its own work. Distributed tracing connects the dots. 👇 https://youtu.be/Oa-zqv-EBpw

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Stop wasting hours chasing down information that should've been provided upfront. Learn how to transform a chaotic repository into a well-organized project with clear processes & automated workflows. https://youtu.be/gYl3moYa4iI

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See you all later today in this week's AMA session. YouTube (desktop): youtube.com/live/L4RZXAK... YouTube (mobile): youtube.com/live/mKvsQW6...

I wanted to love kagent for Kubernetes, but the UX is painful compared to Claude Code or Cursor 😬 Declarative agents = system prompts + tools + LLM. Nothing you couldn't build yourself in an hour. Full breakdown of what works (and what doesn't) 👇 https://youtu.be/3jkGJvmUMYE

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Stop trusting day-one AI reviews. I used Gemini 3 exclusively for a week on production code. Yes it's fast. Yes it's smart. But it ignores context, resists feedback, and declares victory while builds fail. https://youtu.be/AUoqr5r1pBY

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Stop debugging Kubernetes at 3 AM. I built an AI agent + K8s controller that: ✅ Detects issues via events ✅ Analyzes root cause (99% confidence) ✅ Suggests fixes ✅ Validates remediation Fully open source. https://youtu.be/UbPyEelCh-I

Here's what most devs get wrong about AI agents: The agent is the ONLY dumb actor in the system. It doesn't think or decide—it just executes. The LLM provides the brains, you provide intent. https://youtu.be/bfBOn2Ahj4c

Which AI model for DevOps work? I ran GPT-5, Claude, Gemini, Grok & more through real agent workflows. Pattern recognition, policy generation, troubleshooting. The winner beat models 20x more expensive. https://youtu.be/r84kQ5IMIQM

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Stop using AI for everything in Kubernetes. Use it where it actually helps: ❌ Alerting (events are better) ✅ Analysis (AI excels here) ⚖️ Remediation (only for unknowns) Smart automation beats expensive AI every time. https://youtu.be/rIdcJYLtCdo

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It's Thursday, and that means Ask Us Anything live session. youtube.com/live/--z0NqQ...

MCP servers are just servers. Deploy them like production services: Kubernetes for flexibility, cloud platforms for convenience, but never locally for teams. Full comparison of all methods 👇 https://youtu.be/MHf-M8qOogY

🔥 Your AI agent is (probably) USELESS for infrastructure management. Most orgs treat AI like a search engine instead of building it into their platform properly. Here's the 5-component blueprint that changes everything 👇 https://youtu.be/Ma3gKmuXahc Video sponsor: https://tuple.app

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🔥 Most people using Kubernetes don't actually understand how it works. They write YAML and run kubectl apply, but when things break, they're lost. The secret? Controllers are the beating heart of K8s. This video breaks down how they really work 👇 https://youtu.be/kss081c8EqY

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🤯 Just revealed my complete AI development workflow that takes projects from chaotic idea to production-ready code. No more context switching, forgotten requirements, or "what did we build last week?" Watch how PRDs + AI agents = systematic magic ✨ 🧵 https://youtu.be/LUFJuj1yIik

⚡ One workflow, two outputs: Extract policies from your brain → Generate embeddings for AI semantic search + Auto-create Kyverno enforcement rules. https://youtu.be/hLK9j2cn6c0

Why are all terminal coding agents except Claude Code so broken? I desperately want alternatives but every "GPT-5 compatible" agent I tested failed at table stakes features. Competition is good - when it actually works. https://youtu.be/MXOP4WELkCc

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Vector databases + embeddings = game changer for Kubernetes discovery! 🚀 Instead of memorizing 400+ resource names, just describe what you want in plain English. Semantic search finds the right resources even when keywords don't match perfectly. https://youtu.be/MSNstHj4rmk

Vector databases + embeddings = game changer for Kubernetes discovery! 🚀 Instead of memorizing 400+ resource names, just describe what you want in plain English. Semantic search finds the right resources even when keywords don't match perfectly. https://youtu.be/MSNstHj4rmk

The uncomfortable truth: Every day you don't implement vector databases + RAG is another day of manual work while complaining "AI isn't ready." The tools exist NOW. Proof of concept by tomorrow. Stop making excuses 💪 https://youtu.be/zqpJr1qZhTg

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We're back, after a short pause, with weekly AMA sessions. Looking forward to answering your questions later today. youtube.com/live/7_-PoHI...

Your team's collective AI knowledge shouldn't live on individual laptops. Learn how to package prompts into MCPs, distribute them like any other code, and stop reinventing the wheel every time someone needs AI help ⚡ https://youtu.be/XwWCFINXIoU