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PRACTICAL AI AUTOMATION: Harnessing Agentic Artificial Intelligence for Business Automation with LLM-Powered Agents - Softcover
Synopsis
What if your automation could interpret messy requests, choose the right tools, recover from failures, and still behave like production software—bounded, auditable, and safe?
Practical AI Automation is a hands-on guide to building agentic business automation systems where probabilistic reasoning is contained inside deterministic engineering controls. Instead of treating a single model response like a function call, this book shows how to design governed execution loops: typed tool calls, runtime policy enforcement, persistent state, and termination rules you can test, monitor, and explain.
Inside, you’ll learn how to:
- Build a production agent architecture using a typed state machine, budgets, and replay protection
- Expose enterprise capabilities through a schema-validated tool protocol boundary with structured errors, timeouts, and rate limits
- Engineer memory and retrieval as governed subsystems that refuse to act without evidence
- Implement human-in-the-loop approvals with deterministic pre-execution diffs and resumable interrupts
- Defend against prompt injection, data leakage, and unauthorized actions with sanitization, scopes, and audit trails
- Evaluate agent systems using trace-based metrics and regression gates that catch prompt/topology drift before release
- Deploy and scale with a microservice split (API, workers, tools, state/cache, queue) that enforces backpressure and predictable SLAs
Written for engineers, technical operators, and product teams, this book provides practical blueprints you can adapt to sales/support workflows, financial operations, and internal tooling, without relying on “trust the model” as your safety plan. The result is agentic automation that can ship: constrained where it must be, flexible where it can be, and accountable everywhere.
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PRACTICAL AI AUTOMATION: Harnessing Agentic Artificial Intelligence for Business Automation with LLM-Powered Agents
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PRACTICAL AI AUTOMATION
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Practical AI Automation (Paperback)
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Paperback. Condition: new. Paperback. What if your automation could interpret messy requests, choose the right tools, recover from failures, and still behave like production software-bounded, auditable, and safe?Practical AI Automation is a hands-on guide to building agentic business automation systems where probabilistic reasoning is contained inside deterministic engineering controls. Instead of treating a single model response like a function call, this book shows how to design governed execution loops: typed tool calls, runtime policy enforcement, persistent state, and termination rules you can test, monitor, and explain.Inside, you'll learn how to: Build a production agent architecture using a typed state machine, budgets, and replay protectionExpose enterprise capabilities through a schema-validated tool protocol boundary with structured errors, timeouts, and rate limitsEngineer memory and retrieval as governed subsystems that refuse to act without evidenceImplement human-in-the-loop approvals with deterministic pre-execution diffs and resumable interruptsDefend against prompt injection, data leakage, and unauthorized actions with sanitization, scopes, and audit trailsEvaluate agent systems using trace-based metrics and regression gates that catch prompt/topology drift before releaseDeploy and scale with a microservice split (API, workers, tools, state/cache, queue) that enforces backpressure and predictable SLAsWritten for engineers, technical operators, and product teams, this book provides practical blueprints you can adapt to sales/support workflows, financial operations, and internal tooling, without relying on "trust the model" as your safety plan. The result is agentic automation that can ship: constrained where it must be, flexible where it can be, and accountable everywhere. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798191447766
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Practical AI Automation : Harnessing Agentic Artificial Intelligence for Business Automation with LLM-Powered Agents
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Taschenbuch. Condition: Neu. Neuware - What if your automation could interpret messy requests, choose the right tools, recover from failures, and still behave like production software-bounded, auditable, and safe Practical AI Automation is a hands-on guide to building agentic business automation systems where probabilistic reasoning is contained inside deterministic engineering controls. Instead of treating a single model response like a function call, this book shows how to design governed execution loops: typed tool calls, runtime policy enforcement, persistent state, and termination rules you can test, monitor, and explain.Inside, you'll learn how to: - Build a production agent architecture using a typed state machine, budgets, and replay protection- Expose enterprise capabilities through a schema-validated tool protocol boundary with structured errors, timeouts, and rate limits- Engineer memory and retrieval as governed subsystems that refuse to act without evidence- Implement human-in-the-loop approvals with deterministic pre-execution diffs and resumable interrupts- Defend against prompt injection, data leakage, and unauthorized actions with sanitization, scopes, and audit trails- Evaluate agent systems using trace-based metrics and regression gates that catch prompt/topology drift before release- Deploy and scale with a microservice split (API, workers, tools, state/cache, queue) that enforces backpressure and predictable SLAsWritten for engineers, technical operators, and product teams, this book provides practical blueprints you can adapt to sales/support workflows, financial operations, and internal tooling, without relying on 'trust the model' as your safety plan. The result is agentic automation that can ship: constrained where it must be, flexible where it can be, and accountable everywhere. Seller Inventory # 9798191447766
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