Learning Systems Thinking
Montalion, Diana
Shameless self promotion
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Zen and the Art of Motorcycle Maintenance
Pirsig, Robert
This is the philosophical root of Knowledge Flow. Pirsig names the core problem: we keep rebuilding the same factories because we never interrogate the rationality that produced them.
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Thinking in Systems
Meadows, Donella
Meadows gives readers the grammar of systems thinking: stocks, flows, feedback loops, leverage points. This is the first time many people realize they’ve been solving the wrong problems.
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The Fifth Discipline
Senge, Peter
This book connects individual learning to organizational learning. It introduces mental models, shared vision, and team learning as system properties—not HR initiatives.
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The New Economics
Deming, W Edwards
Deming teaches that most failure is systemic, not individual—and that optimizing parts destroys wholes. His System of Profound Knowledge maps directly onto modern software, AI, and sociotechnical systems.
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Cynefin Weaving Sense-Making
Cynefin reframes decision-making as context-sensitive. It explains why best practices fail in complex domains—and why knowledge must be probed, not prescribed.
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Deep Work
Newport, Cal
Knowledge Flow requires protecting time, energy, and attention. Newport shows why deep cognitive work is becoming rarer—and more valuable—inside distracted systems.
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The Social Life of Information
This book explains why formal systems fail without informal practices. Knowledge flows through communities, stories, and relationships—not just tools
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Thinking Fast and Slow
Kahneman reveals why rational systems routinely make irrational decisions. Cognitive bias, heuristics, and illusion of understanding are not bugs—they’re features you must design around.
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Team Topologies
This is Knowledge Flow applied to software teams. It shows how organizational structure shapes communication, cognition, and delivery—and why architecture follows interaction patterns.
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Working Knowledge
This book dismantles the myth that knowledge can be “captured and delivered.” Knowledge is relational, contextual, and socially constructed—long before “knowledge graphs” made this fashionable.
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