ISBN: 9798175815444 - ai tool-use engineering: function calling, tool routing, permission boundaries, execution control, and verification (6 risultati)

Taschenbuch. Condizione: Neu. Neuware - AI Tool-Use Engineering is a guide to the interface between a language model's reasoning and the systems it can actually affect: function calling, tool routing, permission boundaries, execution control, and verification. This is the layer where a model's decision to act becomes a real action with real consequences. Eleven chapters cover the full tool-use stack: - Tool-using AI architecture: tool catalog design, schemas, routing, and a separated execution layer- Function calling interfaces: typed arguments, interface-level validation, typed outputs, actionable error surfaces- Tool routing and selection: intent mapping, capability boundaries, cost-aware routing, fallback chains- Permission boundaries: scopes, least privilege, execution-layer-only credentials, informative approval gates- Execution control: tool-specific timeouts, layered resource limits, runtime-enforced sandboxing, clean cancellation- Result verification: automatic schema checks, genuinely independent cross-validation, confirmed side effects- Reliable multi-step tool workflows: externally tracked state, explicit dependencies, step-level retry, compensation- Security and abuse resistance: injection defense, misuse detection, exfiltration prevention, execution-layer policy- Testing tool-using systems: deterministic mocks, failure injection, decision-path coverage, regression triggers- Production tool infrastructure: a single tool registry, explicit versioning, decision-inclusive observability>Every section pairs the concept with the trade-off that makes it a real engineering decision, the pitfall teams most often hit, and practical checks. Each chapter closes with a worked scenario. Four appendices cover architectural comparisons, a tool-use maturity model, a failure-mode reference organized by symptom, and common questions. Written for engineers building AI agents, copilots, and any system where a model's decisions translate into real actions.…

Paperback. Condizione: new. Paperback. AI Tool-Use Engineering is a guide to the interface between a language model's reasoning and the systems it can actually affect: function calling, tool routing, permission boundaries, execution control, and verification. This is the layer where a model's decision to act becomes a real action with real consequences. Eleven chapters cover the full tool-use stack: - Tool-using AI architecture: tool catalog design, schemas, routing, and a separated execution layer- Function calling interfaces: typed arguments, interface-level validation, typed outputs, actionable error surfaces- Tool routing and selection: intent mapping, capability boundaries, cost-aware routing, fallback chains- Permission boundaries: scopes, least privilege, execution-layer-only credentials, informative approval gates- Execution control: tool-specific timeouts, layered resource limits, runtime-enforced sandboxing, clean cancellation- Result verification: automatic schema checks, genuinely independent cross-validation, confirmed side effects- Reliable multi-step tool workflows: externally tracked state, explicit dependencies, step-level retry, compensation- Security and abuse resistance: injection defense, misuse detection, exfiltration prevention, execution-layer policy- Testing tool-using systems: deterministic mocks, failure injection, decision-path coverage, regression triggers- Production tool infrastructure: a single tool registry, explicit versioning, decision-inclusive observability- Cost and latency management: per-call attribution, latency budgets, volatility-aware caching, batching Every section pairs the concept with the trade-off that makes it a real engineering decision, the pitfall teams most often hit, and practical checks. Each chapter closes with a worked scenario. Four appendices cover architectural comparisons, a tool-use maturity model, a failure-mode reference organized by symptom, and common questions. Written for engineers building AI agents, copilots, and any system where a model's decisions translate into real actions. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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

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

Condizione: New. Print on Demand.

Paperback. Condizione: new. Paperback. AI Tool-Use Engineering is a guide to the interface between a language model's reasoning and the systems it can actually affect: function calling, tool routing, permission boundaries, execution control, and verification. This is the layer where a model's decision to act becomes a real action with real consequences. Eleven chapters cover the full tool-use stack: - Tool-using AI architecture: tool catalog design, schemas, routing, and a separated execution layer- Function calling interfaces: typed arguments, interface-level validation, typed outputs, actionable error surfaces- Tool routing and selection: intent mapping, capability boundaries, cost-aware routing, fallback chains- Permission boundaries: scopes, least privilege, execution-layer-only credentials, informative approval gates- Execution control: tool-specific timeouts, layered resource limits, runtime-enforced sandboxing, clean cancellation- Result verification: automatic schema checks, genuinely independent cross-validation, confirmed side effects- Reliable multi-step tool workflows: externally tracked state, explicit dependencies, step-level retry, compensation- Security and abuse resistance: injection defense, misuse detection, exfiltration prevention, execution-layer policy- Testing tool-using systems: deterministic mocks, failure injection, decision-path coverage, regression triggers- Production tool infrastructure: a single tool registry, explicit versioning, decision-inclusive observability- Cost and latency management: per-call attribution, latency budgets, volatility-aware caching, batching Every section pairs the concept with the trade-off that makes it a real engineering decision, the pitfall teams most often hit, and practical checks. Each chapter closes with a worked scenario. Four appendices cover architectural comparisons, a tool-use maturity model, a failure-mode reference organized by symptom, and common questions. Written for engineers building AI agents, copilots, and any system where a model's decisions translate into real actions. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…