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Thinking in Agents and AI-Native Systems: Designing, Building and Governing Agents on a Deterministic Core - Brossura
Libro 5 di 6: Thinking in AI
Sinossi
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
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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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Thinking in Agents and AI-Native Systems: Designing, Building and Governing Agents on a Deterministic Core
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Thinking in Agents and AI-Native Systems (Paperback)
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Paperback. Condizione: 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. Codice articolo 9798172228995
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Thinking in Agents and AI-Native Systems : Designing, Building and Governing Agents on a Deterministic Core
Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: 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. Codice articolo 9798172228995
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Thinking in Agents and AI-Native Systems (Paperback)
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Paperback. Condizione: 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. Codice articolo 9798172228995
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