Battle-tested best practices for building real products with Claude Code.
This guide distills 2 months of full-time AI-assisted development into actionable patterns. Every recommendation comes from shipping a production system — not theory. The project involved 34 backend domains, a Next.js frontend, Chrome extension, worker pipelines, and deployment automation — all built primarily through Claude Code conversations.
These practices are framework-agnostic. Whether you're building in Python, TypeScript, Rust, Go, or anything else — the workflows, debugging protocols, and quality gates apply universally.
- Beginners: Start with Foundation and Workflow — you'll immediately write better CLAUDE.md files and stop losing context between sessions
- Intermediate users: Jump to Agents and Debugging — learn to orchestrate multiple agents and debug systematically instead of randomly
- Team leads: Read Quality and Advanced — standardize your team's AI-assisted development process
- Structure beats talent. A mediocre prompt with great workflow beats a great prompt with no workflow.
- Evidence over claims. Never trust "should work" — run the tests, read the output, verify the claim.
- Atomic everything. One task, one commit. One agent, one job. Small, verifiable units compound into reliable systems.
- AI is a junior dev with perfect memory. Give it clear specs, review its work, and enforce process — don't just "let it code."
- The CLAUDE.md is your API contract. It's how you communicate your project's rules to every future Claude session.
Set up correctly from day one. These decisions compound.
- CLAUDE.md Architecture — The most important file in your project
- Memory System — Persistent learning across sessions
- Project Structure — Organizing your workspace for AI-assisted dev
The daily combat loop. These are your non-negotiable habits.
- Planning Before Coding — No placeholders, no "TBD"
- Test-Driven Development — The Iron Law: no code without a failing test
- Commit Discipline — One task = one commit, always
- Git Worktrees — Isolated workspaces for parallel features
- Verification Before Completion — Evidence > "should work"
Scale yourself by orchestrating specialized agents.
- Three-Layer Agent System — Planning + Process + Execution
- Agent Routing — Right agent for the right job
- Subagent-Driven Development — Fresh context per task, two-stage review
- Parallel Dispatch — Run independent work concurrently
Stop guessing. Start investigating.
- Systematic Debugging Protocol — 4 phases: Investigate, Analyze, Hypothesize, Implement
- Common Anti-Patterns — What NOT to do when things break
Gates that prevent shipping garbage.
- Code Review Gates — Spec compliance first, then code quality
- Refactoring Patterns — Breaking circular deps, extracting domains
- Deployment Safety — Health checks, scoped commands, backup discipline
Level up after you've mastered the basics.
- Knowledge Graphs — Map dependencies before you refactor
- Multi-Product Workspaces — Multiple projects, one AI workflow
- Extension & Build Versioning — Dual builds, snapshot rollback
- Templates — Copy-paste starters for CLAUDE.md, plans, stories, agents
- Examples — Sanitized real sessions showing patterns in action
- Cheatsheet — Everything on one page
Minimum viable setup (5 minutes):
- Copy templates/CLAUDE.md.template to your project root as
CLAUDE.md - Fill in: commands, architecture overview, testing instructions, key conventions
- Read Verification Before Completion — this alone will 10x your output quality
Full setup (30 minutes):
- Read Planning Before Coding and copy the plan template
- Set up the Memory System
- Read TDD with AI
Team adoption:
- Read Three-Layer Agent System for workflow architecture
- Customize Agent Routing for your tech stack
- Enforce Code Review Gates in your process
These practices were developed while building a production video generation platform with:
- 34 backend domain modules (Node.js, Prisma, PostgreSQL)
- Next.js 16 frontend with React 19
- Chrome extension with dual-build system
- BullMQ worker pipelines
- Python video assembly service
- Zero-downtime PM2 deployment
The entire system was built through Claude Code conversations over ~2 months. Every pattern in this guide was born from a real problem, not invented in a vacuum.
See CONTRIBUTING.md for guidelines.
The best contributions come from real experience — if you've discovered a pattern that made your AI-assisted development significantly better, we want to hear about it.