Thinking in Agents and AI-Native Systems: Designing, Building and Governing Agents on a Deterministic Core - Softcover

Book 5 of 6: Thinking in AI

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9798172228995: Thinking in Agents and AI-Native Systems: Designing, Building and Governing Agents on a Deterministic Core

Softcover

ISBN 13: 9798172228995

Publisher: Independently published, 2026

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An agent is a thing in code. Its autonomy level is the shape of that code. Its safety lives somewhere the model can never reach.

Thinking in Agents and AI-Native Systems is the engineer's book of the series: build four agents at autonomy levels 1 to 4 from scratch, run an offline simulated model so every listing runs on any laptop with no API key, write handoff contracts and a coordinator with step limits, put the never list into a deterministic core that refuses whoever proposes — agent or person — with no bypass, give every agent one identity and exactly its grants in one shared store, record every decision so it can be replayed for a regulator, and assemble a native process from five parts with a stop rule computed from the chain's own numbers.

Every listing is embedded from a tested code package (about 1,200 lines, nine tests, a reference architecture script) and every output printed in the book was produced at build time. The reference architecture is Cedar Bank's SME credit process: $310 to $95 a file, four days to four hours, 2.5x volume on the same forty analysts.

After this book you will be able to:

Write an agent specification as data and register agents that a runtime refuses without an owner
Build agents at every level and see the level as the shape of the code
Chain agents with handoff contracts, a coordinator, and controls for loops, conflicts and silent errors
Build a shared store with per-agent identities, exact grants and a write trail
Encode a never list as rule functions with owners, versioned and changed only by signature
Implement checkpoints, decision logs, replay, three numbers and per-agent indicators
Assemble a native process, migrate by cohort, and hand the board the numbers it asked for

26 chapters, 26 figures, 208 self-test questions with answer keys, the full code in Appendix A, templates and an 18-item architecture checklist in Appendix B. Book 5 of the Thinking in AI series.

In this series: 1 The Foundations � 2 Thinking in AI for Leaders � 3 Thinking in AI for Managers � 4 Thinking in AI at Work � 5 Thinking in Agents and AI-Native Systems � 6 The AI-Native Casebook.

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