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How AI agents & Claude skills work (Clearly Explained)

| 16 products mentioned
Ras Mic guest
Watch on YouTube ai agents prompt engineering workflow automation ai skills context management claude coding assistants

Ras Mic breaks down how AI agents and skills actually work in practice, countering common misconceptions about setup complexity. Rather than relying on large configuration files, the key to agent productivity is iteratively teaching the model your specific workflow, then codifying that into reusable skills — a methodology that yields dramatically better results than downloading pre-built solutions or over-engineering system prompts. [Claude Opus 4.5, GPT-4o, Claude Code]

Key takeaways
  • Skip agent.md and claude.md files for 95% of use cases; they waste tokens on every conversation and aren't necessary unless you have proprietary company information that must be referenced constantly.
  • Skills using progressive disclosure are superior to config files because only the skill name and description load in context; the full implementation only loads when the agent decides it needs that skill, saving thousands of tokens per conversation.
  • Build skills through iterative workflow teaching, not by creating them in isolation: work with the agent step-by-step on your actual task, identify failures together, ask the agent to fix errors and update the skill file accordingly—this recursive approach creates production-ready skills that work 100% of the time.
  • Modern LLMs are excellent token predictors but don't "think" the way humans do; you must treat agents like new employees and provide explicit step-by-step context, not assume they'll infer what you mean from a vague instruction.
  • Scale agent systems incrementally: start with one agent and real workflows, build skills that work, only add sub-agents when you have predefined, proven workflows to hand off—avoid the temptation to build 15 sub-agents and 30 skills from day one just because it looks impressive.
  • Keep context windows in the 20-70% range to maintain agent performance; filling context too close to the limit makes the model "get dumb," similar to how human cognition degrades when overwhelmed with information, which also wastes money on tokens.

Recommendations (11)

Claude Opus 4.5

"Opus 3.5 is amazing. I was using Opus."

Ras Mic · ▶ 0:51

GPT-4o
GPT-4o uses

"GPT-4o is amazing."

Ras Mic · ▶ 0:54

Claude Code

"Claude Code leaked recently and one of the cool things that especially as a developer I got to do is I got to read the system prompt."

Ras Mic · ▶ 1:43

React
React uses

"If I'm building like, let's say, a website with Claude Code and I'm telling Claude Code, this codebase uses React."

Ras Mic · ▶ 2:24

Notion
Notion uses

"Let's say you have a notion report skill, right? and you tell your agent, hey, I want you to create a notion report."

Ras Mic · ▶ 3:45

OpenClaw
OpenClaw uses

"I have an OpenClaw agent that has its own email, right? I forward that email to the agent."

Ras Mic · ▶ 7:35

Google Sheets

"We have a spreadsheet in Google Sheets. It'd be like no contact."

Ras Mic · ▶ 9:56

Trust Pilot

"Check their Twitter, check their YouTube, check their Trust Pilot, check if they've raised any money."

Ras Mic · ▶ 9:39

"It calls notion dub analytics YouTube analytics Twitter analytics pulls from my it pulls from like eight data sources."

Ras Mic · ▶ 22:17

"It calls notion dub analytics YouTube analytics Twitter analytics pulls from my it pulls from like eight data sources."

Ras Mic · ▶ 22:19

Paperclip uses

"Paperclip looks awesome. Cool. I used it. I loved it."

Ras Mic · ▶ 14:49

Mentioned (5)

Cursor
Cursor "There was a difference between the quality of output that cursor generated versus cloud code vers..." ▶ 27:11
Codex
Codex "There was a difference between the quality of output that cursor generated versus cloud code vers..." ▶ 27:16
Next.js
Next.js "I'm using Next.js and Superbase I'm using this and that." ▶ 19:46
Supabase
Supabase "I'm using Next.js and Superbase I'm using this and that." ▶ 19:48
Convex
Convex "I'm using react and you know convex." ▶ 19:43