Alexio cassani (9 risultati)

- Brossura
Da: BargainBookStores, Grand Rapids, MI, U.S.A.BargainBookStores
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 38,96
Spedizione gratuitaSpedito in U.S.A.Quantità: 5 disponibili
Paperback or Softback. Condizione: New. Code Revealed: A practical guide to AI agents, workflows, and modern application practices. Book.

- Brossura
Da: California Books, Miami, FL, U.S.A.California Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 42,42
Spedizione gratuitaSpedito in U.S.A.Quantità: Più di 20 disponibili
Condizione: New.

- Brossura
Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 42,90
EUR 4,85 spedizioneSpedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

- Brossura
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 55,00
EUR 62,37 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Taschenbuch. Condizione: Neu. Neuware - This book shows how to move from experimental AI use to structured delivery. Learn to evaluate tools, assign autonomy, create traceable workflows, and build collaboration models that keep teams effective as AI takes on a larger role.

- Brossura
- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 44,83
Spedizione gratuitaSpedito in U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Bridge the gap between AI hype and software reality by learning how to evaluate agents, redesign team responsibilities, and introduce structured controls that improve delivery without sacrificing clarity, safety, or maintainability.Key FeaturesUse RACM to match AI capabilities to SDLC tasks… and supervision needsApply Execution Plans and Logbooks to make agent work visible and auditableSet autonomy limits, guardrails, and review practices for safer adoptionBook DescriptionCode Revealed is a practical guide for teams learning to work with AI agents in real delivery environments. Rather than treating AI as a coding shortcut, it shows how to introduce it as a managed capability across the software lifecycle.It explains how agents differ from assistants, why evaluation matters when selecting tools, and how development changes when intent, supervision, and validation become more important than manual implementation.You will learn how to use frameworks such as RACM to assess capability, Context Engineering to improve reliability, and PAIP to introduce repeatable integration patterns. The book also explains why Execution Plans and Logbooks matter when delegating work to agents, giving teams a way to align before action and review what happened afterward.Beyond process, the book examines team redesign, new specialist roles, and the shift from directing people alone to orchestrating human and artificial contributors together.It also addresses difficult issues often overlooked in AI adoption, including code churn, weak oversight, security exposure, opaque decisions, and the long-term cost of unmanaged speed. The result is a practical roadmap for adopting AI with discipline, transparency, and measurable intent.What you will learnDistinguish agents from simpler AI coding assistantsAssess tool fit using capability and autonomy criteriaStructure prompts through richer Context EngineeringUse plans and logs to supervise non-trivial AI tasksDesign workflows for prototyping, refactoring, and QAPrevent hidden risk from churn, bias, and hallucinationsReorganize teams around emerging AI-native rolesBuild skills for orchestration, review, and governanceWho this book is forThis book is for developers, tech leads, architects, and engineering managers who are actively building and delivering software while adapting to AI-driven change. It is especially valuable for mid-level and senior developers working across web, backend, and platform systems who want to stay relevant as their role shifts from writing code to guiding and validating AI-generated work. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

- Brossura
- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 61,49
EUR 7,58 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Condizione: New. Print on Demand.

- Brossura
- Print on Demand
Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 63,57
EUR 9,95 spedizioneSpedito da Germania a U.S.A.Quantità: 4 disponibili
Condizione: New. PRINT ON DEMAND.

- Brossura
- Print on Demand
Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 55,06
EUR 31,74 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Bridge the gap between AI hype and software reality by learning how to evaluate agents, redesign team responsibilities, and introduce structured controls that improve delivery without sacrificing clarity, safety, or maintainability.Key FeaturesUse RACM to match AI capabilities to SDLC tasks… and supervision needsApply Execution Plans and Logbooks to make agent work visible and auditableSet autonomy limits, guardrails, and review practices for safer adoptionBook DescriptionCode Revealed is a practical guide for teams learning to work with AI agents in real delivery environments. Rather than treating AI as a coding shortcut, it shows how to introduce it as a managed capability across the software lifecycle.It explains how agents differ from assistants, why evaluation matters when selecting tools, and how development changes when intent, supervision, and validation become more important than manual implementation.You will learn how to use frameworks such as RACM to assess capability, Context Engineering to improve reliability, and PAIP to introduce repeatable integration patterns. The book also explains why Execution Plans and Logbooks matter when delegating work to agents, giving teams a way to align before action and review what happened afterward.Beyond process, the book examines team redesign, new specialist roles, and the shift from directing people alone to orchestrating human and artificial contributors together.It also addresses difficult issues often overlooked in AI adoption, including code churn, weak oversight, security exposure, opaque decisions, and the long-term cost of unmanaged speed. The result is a practical roadmap for adopting AI with discipline, transparency, and measurable intent.What you will learnDistinguish agents from simpler AI coding assistantsAssess tool fit using capability and autonomy criteriaStructure prompts through richer Context EngineeringUse plans and logs to supervise non-trivial AI tasksDesign workflows for prototyping, refactoring, and QAPrevent hidden risk from churn, bias, and hallucinationsReorganize teams around emerging AI-native rolesBuild skills for orchestration, review, and governanceWho this book is forThis book is for developers, tech leads, architects, and engineering managers who are actively building and delivering software while adapting to AI-driven change. It is especially valuable for mid-level and senior developers working across web, backend, and platform systems who want to stay relevant as their role shifts from writing code to guiding and validating AI-generated work. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 47,44
EUR 43,16 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. Bridge the gap between AI hype and software reality by learning how to evaluate agents, redesign team responsibilities, and introduce structured controls that improve delivery without sacrificing clarity, safety, or maintainability.Key FeaturesUse RACM to match AI capabilities to SDLC tasks… and supervision needsApply Execution Plans and Logbooks to make agent work visible and auditableSet autonomy limits, guardrails, and review practices for safer adoptionBook DescriptionCode Revealed is a practical guide for teams learning to work with AI agents in real delivery environments. Rather than treating AI as a coding shortcut, it shows how to introduce it as a managed capability across the software lifecycle.It explains how agents differ from assistants, why evaluation matters when selecting tools, and how development changes when intent, supervision, and validation become more important than manual implementation.You will learn how to use frameworks such as RACM to assess capability, Context Engineering to improve reliability, and PAIP to introduce repeatable integration patterns. The book also explains why Execution Plans and Logbooks matter when delegating work to agents, giving teams a way to align before action and review what happened afterward.Beyond process, the book examines team redesign, new specialist roles, and the shift from directing people alone to orchestrating human and artificial contributors together.It also addresses difficult issues often overlooked in AI adoption, including code churn, weak oversight, security exposure, opaque decisions, and the long-term cost of unmanaged speed. The result is a practical roadmap for adopting AI with discipline, transparency, and measurable intent.What you will learnDistinguish agents from simpler AI coding assistantsAssess tool fit using capability and autonomy criteriaStructure prompts through richer Context EngineeringUse plans and logs to supervise non-trivial AI tasksDesign workflows for prototyping, refactoring, and QAPrevent hidden risk from churn, bias, and hallucinationsReorganize teams around emerging AI-native rolesBuild skills for orchestration, review, and governanceWho this book is forThis book is for developers, tech leads, architects, and engineering managers who are actively building and delivering software while adapting to AI-driven change. It is especially valuable for mid-level and senior developers working across web, backend, and platform systems who want to stay relevant as their role shifts from writing code to guiding and validating AI-generated work. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.