The book constellation
Ten books. Ten ways into the Agentic Systems Library. Choose a star, or follow the reading list below.
Ten books. A constellation of ideas.
Choose a star to discover a book.
English · Second Edition
The story of building a governed AI operating system: its boundaries, failures and human decisions. Start with one defined role, one bounded run and one careful revision.
By Danny Argudin
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English · Second Edition
The work continues. The context shouldn’t disappear. Keep goals, decisions and evidence connected across AI sessions, with illustrated cases and a seven-record field workbook.
By Danny Argudin
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English · Second Edition
When every component works, why does the system fail? Explore memory, attention and handoffs through neuroscience-inspired questions, worked diagnostics and practical exercises—with clear limits on the brain analogy.
By Danny Argudin
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English · Second Edition
The machine can answer. Who takes responsibility? Explore judgment, authorship and accountability in human–AI work, with three fictional cases and ten conceptual illustrations.
By Danny Argudin
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English · Second Edition
The demo works. This is for what comes after.
By Elias North
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English · Second Edition
You don't have to be a tech person. A sidekick works for you.
By Mira J. Lane
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English · Second Edition
Pack a pencil. The machines have habits worth observing. Meet nineteen imagined creatures that make AI easier to examine, with illustrated field notes and paper-based exercises for curious readers fourteen and up.
By Nova Wren
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English · Second Edition
Your system runs. What is it actually doing? Diagnose AI workflows through five bounded chemistry comparisons, with worked cases, diagrams and practical audit tools.
By Danny Argudin
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English · Second Edition
An infinite hotel. A very finite memory. Explore memory, handoffs and finite capacity through the hotel metaphor, with worked cases and practical exercises.
By Danny Argudin
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English · Second Edition
Begin with your phone. Follow the physics. Explore quantum ideas, then test what their analogies can—and cannot—tell us about AI, with worked examples, figures and practical exercises.
By Danny Argudin
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