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This One Plugin Just 10x’d Claude Code

107.3K views· 2,739 likes· 15:14· Apr 12, 2026

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Full courses + unlimited support: https://www.skool.com/ai-automation-society-plus/about?el=superpowers All my FREE resources: https://www.skool.com/ai-automation-society/about?el=superpowers Apply for my YT podcast: https://podcast.nateherk.com/apply Work with me: https://uppitai.com/ My Tools💻 Voice to text: https://get.glaido.com/nate Code NATEHERK for 10% off VPS (annual plan): https://www.hostinger.com/vps/claude-code-hosting Superpowers GitHub: https://github.com/obra/superpowers There's one free plugin that's completely changed how I use Claude Code. It's called Superpowers, and it turns Claude Code into a disciplined developer that clarifies, designs, plans, codes, and verifies before shipping anything. In this video I walk through all 14 skills, show real brainstorming demos, and share the results from a 12-run experiment comparing token usage and code quality with and without the plugin installed. Sponsorship Inquiries: 📧 nate@smoothmedia.co TIMESTAMPS 0:00 Intro 1:22 How It Works & The 14 Skills 4:18 Live Brainstorming Demo 7:27 Building a Website with Superpowers 9:54 How to Install It 10:49 Token & Cost Comparison 14:53 Final Thoughts

About This Video

This video is all about the one free plugin that has genuinely 10x’d how I use Claude Code: Superpowers. It’s an open-source plugin by Jesse Vincent that installs a set of “agentic skills” so Claude Code stops acting like a coder that rushes straight into implementation and starts behaving like a disciplined developer. Instead of jumping into code, it moves through clarify → design → plan → code → verify, which is exactly what you want if you care about not burning tokens on the wrong thing. I walk you through how the dispatcher skill (“using superpowers”) automatically chooses from 14 skills depending on what you’re doing—brainstorming, hyper-detailed planning with file paths, executing plans with safety stops, spinning up sub-agents, parallelizing independent tasks, and adding quality gates like TDD, systematic debugging, and verification before completion. I also show live demos where it spins up a local dashboard to help you pick between options (layouts, UI vibes, approaches) so you can correct direction before it wastes a bunch of tokens. Then I share a 12-run experiment (6 with Superpowers, 6 without) using the same prompts/model (Opus 4.6), capped at $2/run, with zero human interaction. The results were directional, not “proof,” but interesting: ~9% cost savings, ~14% fewer tokens overall, tighter variance, and noticeably better code quality on medium/complex tasks—while simple tasks can see overhead you don’t really need.

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