Supervision Does Not Scale @DevOpsToolkit

Uploaded May 2026 | Updated September 2026, 1 day ago

Supervision Does Not Scale
Watch the full video: youtu.be/7ME4R__IlLg

#Shorts

Ep16 - Ask Me Anything About DevOps, Cloud, Kubernetes, Platform Engineering,... w/Scott Rosenberg

DevOps Q&A: AI Job Impact, Mono vs Poly Repos, Crossplane, and Flux vs Argo

Specialized Templating - Feat. Porter, Werf, Radius, Score, PipeCD (You Choose!, Ch. 05, Ep. 05)

40 Years of Infrastructure as Code: Ansible → Terraform → Kubernetes → Crossplane → AI Agents

DevOps Q&A: Secure Images, GitOps vs CI/CD, and AI Agents

Ep21 - Ask Me Anything About Anything with Scott Rosenberg

Remote Environments with Dev Containers and Devpod: Are They Worth It?

How to Create Custom CLIs for Internal Developer Platforms with Nushell

$MCP vs CLI: I Tested Both and Heres What Won MCP (Model Context Protocol) promises standardized tool discovery for AI agents, but it comes with a hidden cost: every tool definition, name, description, and parameter schema gets loaded into your context window on every single turn. Connect to a bloated MCP server with 40 or 50 tools and youve burned tens of thousands of tokens before asking a single question. This video puts MCP to the test against a compelling alternative — using CLIs as the communication channel between your agent and remote servers. Through live demos with Claude Code and a Kubernetes cluster, the video walks through both approaches side by side: querying cluster health and component relationships through an MCP server, then accomplishing the same task using the `dot-ai` CLI with a handful of lightweight skill files. The core insight is that LLMs are already trained on widely-used CLIs like `kubectl`, `gh`, and `aws`, making them zero-cost to use. For custom or internal tools, small skill files can teach the LLM what it needs to know at a fraction of the context cost of MCP schemas. The verdict isnt that one approach always wins — well-designed MCP servers with a small number of high-level tools remain a strong choice for centralized, cross-agent deployments — but when context efficiency matters or youre working with tools the LLM already knows, CLIs are often the smarter path. ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ Sponsor: Auth0 🔗 http://a0.to/gav ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ #MCPProtocol #AIAgents #KubernetesCLI Consider joining the channel: https://www.youtube.com/c/devopstoolkit/join ▬▬▬▬▬▬ 🔗 Additional Info 🔗 ▬▬▬▬▬▬ ➡ Transcript and commands: https://devopstoolkit.live/ai/mcp-is-burning-your-tokens-before-you-ask-a-single-question 🔗 DevOps AI Toolkit: https://devopstoolkit.ai ▬▬▬▬▬▬ 💰 Sponsorships 💰 ▬▬▬▬▬▬ If you are interested in sponsoring this channel, please visit https://devopstoolkit.live/sponsor for more information. Alternatively, feel free to contact me over Twitter or LinkedIn (see below). ▬▬▬▬▬▬ 👋 Contact me 👋 ▬▬▬▬▬▬ ➡ BlueSky: https://vfarcic.bsky.social ➡ LinkedIn: https://www.linkedin.com/in/viktorfarcic/ ▬▬▬▬▬▬ 🚀 Other Channels 🚀 ▬▬▬▬▬▬ 🎤 Podcast: https://www.devopsparadox.com/ 💬 Live streams: https://www.youtube.com/c/DevOpsParadox ▬▬▬▬▬▬ ⏱ Timecodes ⏱ ▬▬▬▬▬▬ 00:00 MCP vs. CLI 01:10 Auth0 (sponsor) 02:50 MCP Protocol in Action 07:20 CLI Alternative to MCP 17:23 MCP vs CLI: Which One Wins?$

Kubernetes ownerReferences Explained: Why Your Apps Are a Mess