Getting Started with AI Coding Agents in 2026

Why AI Coding Agents Matter

AI coding agents have evolved from simple autocomplete tools into full development partners. With the right configuration — skills, MCP servers, and structured workflows — they can handle complex multi-step tasks autonomously.

This guide walks you through setting up a production-ready AI agent workflow.

Step 1: Install Skills

Skills are structured workflows that turn your AI agent into a domain expert. Install the full AICoach library:

skillfish add johnefemer/skillfish --all

This gives you 170+ skills across engineering, marketing, product, and more.

Step 2: Connect MCP Servers

MCP (Model Context Protocol) servers extend your agent's capabilities with real-time data access. Browse 9,000+ servers in the AICoach MCP Registry.

Popular choices:

• GitHub MCP — Pull requests, issues, and code search
• Database MCP — Direct SQL access for debugging
• Slack MCP — Team communication from your agent

Step 3: Use Structured Workflows

Instead of ad-hoc prompts, use skills to invoke expert-level workflows:

/review src/auth.ts

This invokes the Code Review Coach skill, which follows a structured review process covering security, performance, and maintainability.

What's Next

• Browse the Skills Library to find skills for your domain
• Explore the MCP Registry for data integrations
• Read the API docs if you're building integrations
• Check out the Marketplace for AI tools and services

The AI coding agent ecosystem is growing fast. Start with a few skills, add MCP servers as needed, and iterate on your workflow.