AI Tool-Use Engineering: Function Calling, Tool Routing, Permission Boundaries, Execution Control, and Verification

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.