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AI-native developer tooling — Claude Code · MCP · design tools

A 7-step path to using AI tools beyond chat — MCP, Skills, Subagents, workflows, and design-side tooling.

Difficulty
Beginner
Lessons
7

AI coding tools are not "copy-paste chatbots" anymore. Master context (MCP), automation (Skills/Subagents), and IDE integration — and the tools start running tools.

By the end:

  • Understand Claude Code's slash commands, memory, and extension model
  • Connect MCP servers, Context7, Figma
  • Build workflows with Skills + Subagents + Hooks
  • Compare with other AI CLIs / IDEs
  • Compare AI design tools (Stitch · v0 · Figma AI)

Flow

How AI tooling expands

Purpose and base tool

Separate repetitive work from judgment and learn the role of conversational development tools.

External context

Use MCP to design permission boundaries for documents, data, and service connections.

Reusable units

Split repeatable procedures and responsibilities into skills and supporting agents.

Workflow and design

Connect verifiable automation and visual collaboration tools to real delivery flows.

Steps 1–2 are start, 3–5 extend context (external tools, live docs), 6–7 are the automation and design payoff.

Prerequisite — getting-started + Claude Code (or compatible IDE) installed.

Lessons

  1. 1

    Step 1 — Why AI tools now

  2. 2

    Step 2 — Getting started with Claude Code

  3. 3

    Step 3 — MCP — concepts and clients

  4. 4

    Step 4 — Skills · Subagents · Hooks

  5. 5

    Step 5 — Context7 · Figma MCP

  6. 6

    Step 6 — Building workflows

  7. 7

    Step 7 — AI design tools (Stitch · v0 · Figma AI)

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