ISBN: 9798172228995 - thinking in agents and ai-native systems: designing, building and governing agents on a deterministic core (thinking in ai, band 5) (6 Ergebnisse)

Taschenbuch. Zustand: Neu. Neuware - 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 for26 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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Paperback. Zustand: new. Paperback. 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 ownerBuild agents at every level and see the level as the shape of the codeChain agents with handoff contracts, a coordinator, and controls for loops, conflicts and silent errorsBuild a shared store with per-agent identities, exact grants and a write trailEncode a never list as rule functions with owners, versioned and changed only by signatureImplement checkpoints, decision logs, replay, three numbers and per-agent indicatorsAssemble a native process, migrate by cohort, and hand the board the numbers it asked for26 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

PAP. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Zustand: new. Paperback. 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 ownerBuild agents at every level and see the level as the shape of the codeChain agents with handoff contracts, a coordinator, and controls for loops, conflicts and silent errorsBuild a shared store with per-agent identities, exact grants and a write trailEncode a never list as rule functions with owners, versioned and changed only by signatureImplement checkpoints, decision logs, replay, three numbers and per-agent indicatorsAssemble a native process, migrate by cohort, and hand the board the numbers it asked for26 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…