Claude Code Setup for AI Implementation Experts

    The real CLAUDE.md powering Iwo Szapar's workflow — running a SaaS product, ISG advisory work, content system, and client delivery pipeline from a single AI brain. Advanced hooks, agent teams, and full MCP orchestration included.

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    CLAUDE.md

    CLAUDE.mdpaste in your project root
    # CLAUDE.md — AI Implementation Expert & Second Brain Architect
    > Version: 2026-03 | Difficulty: advanced | This is a real setup powering a live product
    
    ## What Your AI Can Now Do
    - Ship production features autonomously with `/yalla` — 4-agent planning team with adversarial red-team review before a single line of code is written
    - Auto-track every outreach touchpoint (WhatsApp, email, LinkedIn) to CRM via hooks — zero manual logging
    - Generate personalized Second Brain repositories for clients, fully automated from questionnaire to GitHub delivery
    - Get a morning intelligence briefing combining sales pipeline, inbox, and task priorities with one `/overview` command
    - Draft, evaluate, and publish LinkedIn posts with a single `/content-generation` command — voice consistency scored against 1,000+ real posts
    - Run parallel agent teams: 1 lead + 3 specialists working simultaneously on different layers of the same feature
    
    ---
    
    ## Quick Start
    1. `/begin [task]` before ANY code change — hooks enforce session branch discipline automatically
    2. `/yalla` for complex features — plans with a 4-agent team, then builds and reviews before shipping
    3. `/overview` every morning — real data from CRM, tasks, and calendar combined
    4. `/respond-second-brain` for multi-channel outreach (WhatsApp + Gmail + LinkedIn in one command)
    5. `/grow` weekly — brain health score, patterns learned, time savings metrics
    
    ---
    
    ## About This Setup
    I run a multi-product business (SaaS, coaching, open-source MCP) while doing enterprise innovation advisory. My AI handles product development, CRM automation, content production, and client delivery simultaneously. The goal: think once, let the system run.
    
    **What I'm optimizing for:**
    - Zero context-switching between tools — everything surfaces in Claude
    - Every decision leaves a trace (memory, task, commit)
    - Automation that degrades gracefully — manual fallback for every automated step
    
    ---
    
    ## Pre-Built Commands
    
    | Command | What It Does |
    |---------|-------------|
    | `/yalla` | Full autonomous pipeline: plan → build → test → review → ship |
    | `/begin [desc]` | Start tracked session with branch + GitHub issue auto-created |
    | `/end` | Close session with PR, merge, branch cleanup |
    | `/overview` | Morning briefing: pipeline status + tasks + comms digest |
    | `/respond-second-brain` | Multi-channel outreach: WhatsApp + Gmail + LinkedIn |
    | `/content-generation` | Generate, evaluate, and queue LinkedIn/newsletter content |
    | `/publish-blog` | Full pipeline: write → evaluate → fix AI slop → SEO → publish |
    | `/add-prospect` | Add to CRM with auto-LinkedIn enrichment |
    | `/grow` | Brain health score and learning metrics |
    
    ---
    
    ## How Claude Connects to Your Tools
    
    | Tool | Why You Need It |
    |------|----------------|
    | Supabase MCP | Primary database: CRM, blog posts, product data |
    | Resend MCP | Transactional email: purchase confirmations, drip sequences |
    | Stripe MCP | Payment history, customer lookup, subscription management |
    | Gmail (gog CLI) | Email outreach, inbox triage, reply drafting |
    | LinkedIn (AnySite MCP) | Prospect research, profile enrichment, post engagement |
    | Google Analytics MCP | Traffic analysis, content performance |
    | Claude in Chrome MCP | LinkedIn automation, browser-based flows |
    | Memory MCP | Persistent knowledge graph — context survives between sessions |
    | GitHub MCP / gh CLI | Issues, PRs, file access without browser |
    
    ---
    
    ## Rules
    
    - **MUST:** Run `/begin` before any code change — hooks block edits on main branch, no exceptions
    - **MUST:** Use `mcp__supabase__execute_sql` for all DB queries
    - **MUST:** Include `.js` extensions in all API imports (production build requirement)
    - **MUST:** Add new routes BEFORE the catch-all `*` route
    - **MUST:** Confirm before destructive actions (force push, hard reset, table drops)
    - **SHOULD:** Use `Write` (not sequential `Edit` calls) for files over 500 lines — 80% fewer token failures
    - **SHOULD:** Run `npm run check:types && npm run test:unit` before every push
    
    ---
    
    ## Project Structure
    ```
    src/pages/          # React pages
    api/                # Vercel serverless functions
    lib/                # Shared utilities
    .claude/hooks/      # Lifecycle automation (branch-guard, CRM sync)
    .claude/docs/       # Architecture, patterns, gotchas
    memory/             # Semantic patterns, personal profile, episodic sessions
    product/            # Vision docs, specs, context engineering
    ```
    
    ---
    
    ## Automation (Hooks)
    
    | Trigger | What Happens |
    |---------|-------------|
    | Any edit on `main` | `branch-guard.sh` blocks it — must be on session branch |
    | Session start | Auto-switches to `main`, prevents branch reuse |
    | WhatsApp send | Auto-syncs to CRM with timestamp and message summary |
    | `git push` | Runs `check:types + test:unit` automatically |
    
    ---
    
    ## Gotchas
    - **Missing `.js` in API imports** → Build fails in production
    - **Route after catch-all `*`** → 404 forever, route never matches
    - **Code after `res.json()`** → Vercel terminates function — use `waitUntil()` for background work
    - **Large files (500+ lines) + many small Edits** → Use `Write` instead — saves 80% of tokens
    - **Agent Teams on main branch** → Run `/begin` first — hooks apply to teammates too
    
    ---
    
    ## Memory & Learning
    Claude builds context over time using the Memory MCP:
    - Architectural decisions and why they were made
    - Client patterns and buying signal recognition
    - Content voice calibration (1,000+ LinkedIn comments analyzed)
    - Recurring bugs and their root causes
    - Patterns learned across sessions stored in `memory/semantic/patterns/`
    
    Save anything: just say "remember that [fact]" in conversation.
    Review: `/grow` shows health score + patterns learned this week.
    Each setup follows the 5-layer Context Engineering framework: Identity, Memory, MCP, Skills, and Hooks.
    Learn the framework

    Pre-Built Skills

    Ready-to-use skills included in this setup. Each runs a specialized workflow for your role.

    🚀/yalla

    Full autonomous feature pipeline with agent teams

    🌅/overview

    Morning briefing: pipeline + tasks + comms

    📤/respond-second-brain

    Multi-channel outreach in one command

    ✍️/content-generation

    Generate and queue LinkedIn/newsletter content

    🧠/grow

    Brain health score and weekly learning metrics

    🔒branch-guard hook

    Blocks all edits on main — session discipline enforced

    Recommended MCP Servers

    Supabase MCP

    CRM, blog posts, product data — primary database for everything

    Gmail via gog CLI

    Email outreach, inbox management, reply drafting

    AnySite MCP

    LinkedIn prospect research and profile enrichment

    Memory MCP

    Persistent knowledge graph that survives between sessions

    Google Analytics MCP

    Content performance and traffic analysis

    Stripe MCP

    Payment history and customer management

    Claude in Chrome MCP

    Browser automation for LinkedIn and testing flows

    GitHub MCP / gh CLI

    Issues, PRs, file access without leaving the terminal

    Workflow Templates

    Full Feature Ship

    /yalla

    Autonomous plan → build → test → review → ship pipeline with agent teams

    Morning Briefing

    /overview

    Sales pipeline, tasks, and comms digest in one view

    Multi-Channel Outreach

    /respond-second-brain

    WhatsApp + Gmail + LinkedIn outreach from a single command

    Content Pipeline

    /content-generation

    Generate, evaluate, and queue content across platforms

    This Is a Starter Config

    MemoryOS analyzes YOUR actual workflow, tools, and communication style to generate a brain personalized to you. Fully automated — you decide what to share, it does the rest.

    Based on patterns from 100+ professionals. No technical knowledge required.

    Get Your Personalized Setup