Editing Further Reading (section)

== By Pillar ==

=== Insight Synthesis ===
* '''[https://github.com/anthropics/prompt-eng-interactive-tutorial Anthropic's Prompt Engineering Interactive Tutorial]''' — Hands-on tutorial covering how to structure questions, use examples, and extract better information from AI. The question decomposition techniques directly improve research quality.
* '''[https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/claude-4-best-practices Prompting Best Practices (Anthropic Docs)]''' — The official reference for getting high-quality output from Claude, including techniques for extracting structured information from unstructured sources.
* '''[https://www.chelseagreen.com/product/thinking-in-systems/ Thinking in Systems] by Donella Meadows''' — Not about AI, but the best primer on synthesis thinking. Helps you see patterns, feedback loops, and leverage points in any information set.

=== Workflow Automation ===
* '''[https://docs.n8n.io/advanced-ai/ n8n Advanced AI Documentation]''' — Reference for building AI-powered automation workflows in n8n. Covers AI agents, LangChain integrations, and connecting AI to your existing tools.
* '''[https://docs.n8n.io/advanced-ai/intro-tutorial/ n8n AI Workflow Tutorial]''' — Step-by-step beginner tutorial for building your first AI-powered workflow. No code required.
* '''[https://atulgawande.com/book/the-checklist-manifesto/ The Checklist Manifesto] by Atul Gawande''' — Not about AI, but essential reading on why systematic processes beat ad-hoc approaches. Directly applicable to building reliable AI workflows.

=== Cross-Domain Reframing ===
* '''[https://global.oup.com/academic/product/how-breakthroughs-happen-9781578519040 How Breakthroughs Happen] by Andrew Hargadon''' — Research on how innovation comes from recombining ideas across domains, not from inventing from scratch.
* '''[https://davidepstein.com/range/ Range] by David Epstein''' — The case for generalists: why breadth of experience produces better problem-solving and more creative AI usage.
* '''[https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering/overview Prompt Engineering Overview (Anthropic)]''' — The official Anthropic prompt engineering guide includes techniques for adapting prompts across different use cases — a practical example of cross-domain thinking.

=== Agent Collaboration ===
* '''[https://anthropic.skilljar.com/ai-fluency-framework-foundations AI Fluency: Framework & Foundations (Anthropic)]''' — Free course built on the 4D framework (Delegation, Description, Discernment, Diligence) by Prof. Joseph Feller and Prof. Rick Dakan. The Delegation dimension maps directly to this pillar. CC BY-NC-SA 4.0.
* '''[https://modelcontextprotocol.io/ Model Context Protocol (MCP) Documentation]''' — The open standard for connecting AI to your tools and data sources. If you've completed the advanced agent exercises and want to implement what you designed, start here.
* '''[https://www.oreilly.com/library/view/the-managers-path/9781491973882/ The Manager's Path] by Camille Fournier''' — Not about AI, but excellent on delegation, handoffs, and role definition — the same skills you need to orchestrate AI agents effectively.

=== Ethical Prompting & Judgment ===
* '''[https://en.wikipedia.org/wiki/On_Bullshit On Bullshit] by Harry Frankfurt''' — Short philosophical essay on the difference between lying (knowing the truth and hiding it) and bullshitting (not caring whether it's true). Directly relevant to how AI generates confident but unverified content.
* '''[https://www.penguinrandomhouse.com/books/241363/weapons-of-math-destruction-by-cathy-oneil/ Weapons of Math Destruction] by Cathy O'Neil''' — How algorithmic systems can cause harm at scale when deployed without adequate verification. Provides the "why" behind the governance frameworks in the advanced exercises.
* '''[https://docs.anthropic.com/en/docs/about-claude/models Anthropic's Claude Model Card]''' — Understanding what the models you're using can and can't do is the foundation of ethical use. The official model documentation is the best source.