QED

Quod Erat Demonstrandum - “That Which Is Demonstrated”

AI Development Patterns: A Practitioner's Guide

A practical knowledge base for developers using AI coding assistants in client projects and production environments.

Overview

This guide provides battle-tested patterns for integrating AI tools like Claude Code into real-world development workflows, with focus on client work, security, and production considerations.

Navigate by Risk Level

🟢Low Risk Patterns

Safe starting points for AI adoption

🟡Managed Risk Patterns

Patterns requiring safeguards

🔴High Risk Patterns

Critical systems only

Navigate by Context

🚀Startup Patterns

High agility, low process

📈Mid-Market Patterns

Scaling approaches

🏢Enterprise Patterns

Governance-focused

🏛️Regulated Patterns

Compliance-first

Navigate by Domain

Architecture - System design and integration patterns

Implementation - Development workflows and frameworks

Operations - Deployment and maintenance patterns

Security - Access control and compliance

Team - Collaboration and process patterns

Quality - Validation and testing approaches

For Practitioners

Written for developers, consultants, and agencies using AI coding assistants, covering:

Client-focused best practices

Risk mitigation strategies

ROI optimization

Production deployment patterns

Free to read online • Licensed under CC BY 4.0

Documentation Philosophy

QED follows evidence-based knowledge management:

Tier 1: Research

docs/ Raw material collection

Tier 2: Analysis

src/analysis/ Professional evaluation

Tier 3: Practice

src/ Battle-tested guidance only

Decision Records

decisions/ QED application architecture only