AI Patterns
The current patterns I'm using and hardening for delivering enterprise software with AI agents.
Guides
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Automated Code Review with AI Agents Reference Architecture - A hybrid approach combining deterministic rules-based tooling with context-aware AI agents to automate everything that can be automated about code review.
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Leading an Agentic Development Team - A playbook for leading AI agents as team members, covering mission setting, acceptance-test-driven development, building focused specialist agents, and validating outcomes over activity.
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CD Defect Detection and Remediation Cheat Sheet - A comprehensive catalog of where defects are created in the value stream, methods for automated detection, and systemic remediation strategies.
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Contract Testing Strategies - A comprehensive guide to different contract testing approaches based on your level of organizational control over the services you integrate with.
References
- Agentic Continuous Delivery (ACD) - Extends traditional CD practices to AI agent-generated code, providing frameworks and governance structures that hold agent changes to the same quality bar as human-generated changes.
Articles
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AI is a High Pass Filter for Software Delivery - Why AI amplifies your engineering discipline—teams with strong practices get dramatic improvements, while those without discipline struggle with generated garbage.
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Incorporating AI Without Crashing - A practical roadmap for integrating AI into existing teams, starting with foundational delivery challenges before jumping to code generation.
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Write-Only Code - An exploration of code that is difficult to read and understand, and strategies for writing code that remains maintainable.
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Why Spec-Driven Development Has Reached Its Limit - The article argues that traditional spec-driven development has reached its limit because it only automates software structure, proposing instead a Contract-Driven AI Development (C-DAD) framework that uses "living contracts" to encode human intent and ensure systems remain trustworthy as they evolve.
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AI Broke Your Code Review. Here's How to Fix It - Traditional code review is inadequate for AI-generated code production rates; replace manual bottlenecks with automated tooling and reserve human judgment for what only humans can evaluate.
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Tokenomics: How to Stop Wasting Money on Tokens - Developers building agentic AI systems must treat token consumption as a core architectural concern, managing input/output costs, context windows, and prompt caching to avoid wasteful spending.
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Clarity Was Always the Bottleneck - AI's speed merely exposes the long-standing problem that clarity in requirements has always been the real bottleneck in software delivery—not a reason to return to waterfall-style upfront documentation.
Example Skill libraries
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Paul Hammond's Skills - A focused collection of skills for frontend and test-driven development, covering TypeScript, React testing, mutation testing, functional patterns, refactoring, and TDD workflows.
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Robust Skills - Skills for DDD/hexagonal architecture, feature-sliced design, modern CSS and JavaScript, PostgreSQL with Drizzle ORM, Mermaid diagrams, and Slack app development.
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Quickstart: Agent-Augmented Development - A template for AI-augmented workflows built around a five-layer doctrine stack—guidelines, approaches, directives, tactics, and templates—giving agents consistent, inspectable, governance-layered behavior.
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nwave.ai - An AI-augmented development framework that standardizes team AI usage through a reviewable SDLC workflow combining specifications, tests, and code reviews for repeatable, auditable results.
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Holon: Agentic Coder - A blueprint for git-native, sandbox-isolated autonomous coding agents that decompose work recursively, generate competing plans, record decisions in an append-only ledger, and evolve toward proposing their own intents.