Resources
Curated insights for human-AI collaboration
A carefully curated collection of resources, frameworks, and content that have shaped my understanding of human systems, AI technology, and their intersection. Each resource includes my unique perspective on why it matters for human-AI collaboration.
Essential Resources
Key insights across human systems, AI technology, and collaboration
Deep explorations of human personality systems, attachment theory, and personal development through the lens of complex adaptive systems.
My Take:
Priebe's work on personality as emergent patterns perfectly parallels how I think about AI system architectures - both are complex adaptive systems with emergent behaviors that can't be fully predicted from their components.
Research on training AI systems to be helpful, harmless, and honest through constitutional methods and human feedback.
My Take:
The constitutional approach to AI alignment mirrors human moral development - both require iterative refinement of principles through experience and feedback, not just rule-following.
Comprehensive guide to functional programming patterns in TypeScript, focusing on composable, type-safe effect management.
My Take:
Effect-TS isn't just a library - it's a paradigm for thinking about program composition that directly translates to designing robust human-AI workflows. The same patterns that make code predictable make AI systems trustworthy.
Declarative way to compose LangChain components into complex AI workflows and pipelines.
My Take:
LCEL demonstrates how declarative composition can make AI systems more transparent and debuggable - crucial for human-AI collaboration where humans need to understand and trust the AI's process.
Decision-making framework for understanding the complexity and context of different types of problems and situations.
My Take:
The Cynefin framework is essential for human-AI collaboration because it helps determine when to rely on AI (complicated/complex domains) versus human judgment (chaotic/disorder domains). Most AI failures happen when we apply AI to the wrong complexity domain.
More Resources Coming Soon
I'm continuously discovering and curating new resources that illuminate the intersection of human systems and AI. Future additions will include interactive demos, research papers, and community-contributed insights.
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