Build Your Own Jarvis: Turn Claude Code Into Your Personal Intelligence System

The exact system I use to manage 12,000+ songs, this website, and enterprise consulting.

TL;DR

Your Jarvis has three layers: Knowledge (CLAUDE.md context file with your projects, preferences, and decisions), Execution (MCP servers for file operations, deployment, email), and Intelligence (pattern recognition and continuous learning). Start by creating a CLAUDE.md in your project root. Add skills for repeated workflows. Update weekly with new learnings. In 30 days, you'll have a personal AI system that knows your work and executes complex workflows automatically. Free on GitHub.

Every creator, founder, and knowledge worker I talk to wants the same thing: "I want my own Jarvis."

Not another chat tool. Not another AI that forgets everything the moment you close the tab. A true intelligence partner that:

• Knows your projects intimately
• Remembers your preferences and decisions
• Executes complex workflows automatically
• Gets smarter with every interaction

Here's the truth most AI tutorials won't tell you: The technology to build this already exists. You just need to know how to wire it together.

This guide shows you exactly how.

Here's what your personal intelligence system will be capable of once configured.

Why Generic AI Tools Will Never Be Your Jarvis

The Problem

ChatGPT, Gemini, and other AI assistants are designed for everyone. That means they're optimized for no one.

Every conversation starts from zero. They don't know:

• Your current projects
• Your coding preferences
• Your brand voice
• Your past decisions
• Your goals

You spend 30% of every session just re-explaining context. That's not intelligence partnership—that's expensive rubber-ducking.

The Jarvis Difference

A true personal intelligence system:

The Architecture: How to Build Your Intelligence System

Your personal Jarvis has three layers:

Let's build each layer.

Layer 1: Knowledge (The Brain)

The foundation of your Jarvis is the CLAUDE.md file. This is where you teach the AI who you are.

Step 1: Create Your CLAUDE.md

# My Intelligence System

## Who I Am

- Creator building [your thing]
- Tech stack: [your preferences]
- Communication style: [how you write]

## Current Projects

### Project Alpha

- Goal: [what you're building]
- Status: [where you are]
- Key files: [important paths]

## My Preferences

- Always use TypeScript, never JavaScript
- Prefer functional components over class components
- Write in first person, conversational tone
- Dark mode everything

## Past Decisions

- 2024-01: Chose Next.js over Remix because [reason]
- 2024-02: Using Vercel KV for session storage
- [Document decisions as you make them]

Step 2: Add Skills

Skills are predefined capabilities your system can activate:

## Available Skills

### /publish

Full blog publishing pipeline:

1. Write content
2. Generate hero image
3. Optimize SEO
4. Deploy to production
5. Share on social

### /client-kickoff

New client onboarding:

1. Create CRM entry
2. Generate project brief
3. Set up repository
4. Send welcome email

Key Insight: The more context you add to CLAUDE.md, the smarter your system becomes. Update it regularly.

Layer 2: Execution (The Muscles)

Knowledge without action is just trivia. Your Jarvis needs to DO things.

MCP Servers: Local Superpowers

MCP (Model Context Protocol) servers give Claude Code access to tools that run on YOUR machine:

Example: Full Automation

When you say "publish this blog post", your Jarvis:

1. filesystem-mcp: Reads content, generates MDX
2. nano-banana: Creates hero image
3. website-mcp: Deploys to Vercel
4. email-mcp: Notifies your newsletter list
5. browser-mcp: Shares on social media

All from one command. That's the power of execution layers.

Workflow Commands

Create custom commands in .claude/commands/:

# /daily-ops

Run my daily operations workflow:

1. Check analytics dashboard
2. Review pending tasks
3. Summarize key metrics
4. Suggest priorities

Output: Brief daily intelligence report

Now just type /daily-ops and your Jarvis executes the entire workflow.

Layer 3: Intelligence (The Growth)

This is where your system becomes truly personal.

Pattern Recognition

Over time, your Jarvis learns:

• When you're most productive
• Common task sequences
• Your decision-making patterns
• Optimization opportunities

## Learned Patterns

### Writing Sessions

- Best time: 6-8 AM
- Typical length: 2 hours
- Prefers: Quiet, no meetings before

### Code Reviews

- Focus: Security, performance
- Pet peeves: Any/any types, console.logs

Continuous Improvement

After each major task, add learnings:

## Session: 2026-01-20

### What Worked

- Breaking down the task into smaller chunks
- Using the Task tool for parallel research

### What to Improve

- Need better error handling templates
- Should include tests in all code changes

### New Preference

- When writing APIs, always include rate limiting

Goal Alignment

Your Jarvis should know what you're working toward:

## Active Goals

### Q1 2026

- [ ] Publish 12 blog posts (4/12)
- [ ] Launch new product (research phase)
- [ ] Reach 5K newsletter subscribers (3.2K current)

### This Week

- [ ] Finish authentication refactor
- [ ] Write Claude Code tutorial
- [ ] Set up analytics dashboard

The 30-Day Build Plan

Week 1: Foundation

Day 1-2: Create your CLAUDE.md

• Write your context and preferences
• Document current projects
• List your tech stack

Day 3-5: Set up basic commands

• Create 3-5 workflow commands
• Test each one thoroughly
• Refine based on results

Day 6-7: Integration check

• Ensure all MCP servers working
• Test file operations
• Verify deployment pipeline

Week 2: Expansion

Day 8-10: Add more skills

• Document common workflows
• Create command shortcuts
• Build template library

Day 11-14: Automation

• Set up recurring tasks
• Create notification systems
• Build monitoring dashboards

Week 3: Intelligence

Day 15-17: Pattern documentation

• Record your work patterns
• Note optimization opportunities
• Track decision rationale

Day 18-21: Learning loops

• Add post-session reviews
• Update preferences based on feedback
• Refine command effectiveness

Week 4: Mastery

Day 22-25: Advanced workflows

• Multi-step orchestrations
• Parallel task execution
• Cross-project coordination

Day 26-30: Continuous improvement

• Review what's working
• Remove what isn't
• Plan next iteration

Real Examples From My System

Example 1: Publishing a Blog Post

Command: /publish "AI productivity tips"

What happens:

1. Research agent finds trending topics
2. Content agent writes draft
3. SEO agent optimizes
4. Design agent creates hero image
5. Dev agent deploys to production
6. Marketing agent shares on social

Time: 15 minutes vs 4+ hours manually

Example 2: Client Onboarding

Command: /onboard "Acme Corp"

What happens:

1. CRM entry created
2. Project folder structured
3. Welcome email sent
4. First meeting scheduled
5. Invoice template prepared

Time: 3 minutes vs 45+ minutes manually

Example 3: Weekly Operations

Command: /weekly

What happens:

1. Analytics pulled from all platforms
2. Content performance summarized
3. Revenue calculated
4. Priorities suggested
5. Calendar optimized

Time: 5 minutes vs 2+ hours manually

Common Mistakes to Avoid

1. Starting Too Complex

Don't try to automate everything at once. Start with ONE workflow and perfect it.

2. Not Updating Context

Your CLAUDE.md isn't "set and forget." Update it weekly with new projects, decisions, and learnings.

3. Generic Commands

/do-stuff tells your Jarvis nothing. Be specific: /deploy-staging, /review-pr, /write-newsletter.

4. Skipping the Learning Layer

If you're not documenting what works and what doesn't, your system can't improve. Take 2 minutes after each major task to add notes.

The Open Source Advantage

Everything I've described is free to build. Claude Code, MCP servers, and workflow commands are all open source or included in your Anthropic subscription.

But if you want a head start, I've packaged my entire system:

Agentic Creator OS

Free on GitHub:

• Complete MCP server suite
• 5 department configurations
• Workflow templates
• Skills library

Premium Support:

• Live setup sessions
• Custom configurations
• Priority support

Start Today

You don't need to wait. Here's what to do right now:

1. Create your CLAUDE.md - Take 30 minutes to document your context
2. Pick one workflow - Choose your most painful repeated task
3. Build the command - Create a .claude/commands/ file for it
4. Test and refine - Use it for a week, improve based on results

In 30 days, you'll have your own Jarvis—a personal intelligence system that knows your work, executes your workflows, and gets smarter every day.

The future of AI isn't better chat tools. It's personal intelligence systems that amplify what makes you unique.

Build yours.

Resources

• Agentic Creator OS on GitHub - Free open source system
• Claude Code Documentation - Official docs
• MCP Server Guide - How to set up local tools
• Creator Intelligence System - Premium implementation

FAQ

How much does it cost to build your own Jarvis?

Free with your Claude Pro subscription ($20/month). The Agentic Creator OS is open source on GitHub. MCP servers run locally on your machine. No additional costs unless you want premium support.

How long until I see results?

Most users report time savings in the first week after basic setup. The compound benefits—accumulated context, refined workflows, pattern learning—build over 30-90 days.

Do I need to know how to code?

Basic command line familiarity is enough (cd, npm install, git clone). You're configuring markdown files, not writing software. The system is designed for creators, not developers.

What if I use different AI tools?

The CLAUDE.md pattern works across AI tools. Your context is portable. MCP servers are Claude Code specific, but the workflow patterns transfer to any agentic AI system.

Is my data secure?

Everything runs locally. Your CLAUDE.md lives in your project folder. MCP servers execute on your machine. Nothing is sent to external servers except your Claude API calls (covered by Anthropic's privacy policy).

Related:

• Getting Started with Agentic Creator OS
• 5 Agentic Workflows That Save 10+ Hours Per Week
• What is Agentic AI?