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The Agentic Architect Playbook

Published by Pearson

Intermediate content levelIntermediate

Design, orchestrate, and govern enterprise-grade multi-agent AI solutions

Course Outcomes:

  • Master the “Agentic Architect” skill set—context engineering, orchestration, and strategic leadership of complex AI project portfolios.
  • Learn frameworks for business value, reliability, governance, and observability, aligned with enterprise standards.
  • Develop rollout blueprints, SLOs, risk controls, and evaluation pipelines for agent-based automation at scale.

Multi-agent systems fundamentally reshape how organizations build AI-enabled solutions, requiring tight coordination across technical, operational, and business functions to extract real value and ensure reliability in production environments. As AI tools automate and blur traditional roles, success depends ever more on aligning diverse cross-functional teams—architects, product managers, engineers, and strategists—under clear strategies for design, governance, and lifecycle orchestration.

This course is for technical leaders, solution architects, and AI program managers who must design and govern multiagent automation projects. You’ll apply orchestration concepts, context engineering, and lifecycle management frameworks—not code labs—to drive real value beyond chatbot demos. Guided by Carmelo Iaria’s Agentic Architect model, attendees will build operating models, select collaboration and governance patterns, define SLOs and KPIs, and create actionable rollout plans for complex AI initiatives in real organizations.

What you’ll learn and how you can apply it

  • Design an operating model for agentic automation with defined SLOs and guardrails.
  • Select multi-agent orchestration and coordination strategies, mapping to business needs.
  • Implement policy and risk management for agentic systems; align stakeholders.
  • Build evaluation frameworks and rollout playbooks for successful deployment and stewardship.

This live event is for you because...

  • You are a solution architect, enterprise AI leader, or technical program manager tasked with delivering real business value and reliability from agent-powered automation initiatives.
  • You oversee cross-functional teams or platforms and need to master the design, governance, risk oversight, and lifecycle orchestration of multi-agent AI systems—not just their technical implementation.
  • You seek frameworks for scaling agentic automation across lines of business, ensuring compliance, robust operations, and stakeholder alignment.
  • Your focus is on strategy, architecture, playbooks, and change management—turning demos and prototypes into sustainable production systems that deliver consistent outcomes.

Prerequisites

  • Good understanding of Python programming and software architecture principles.
  • Basic familiarity with AI/ML concepts, language models, and API integration patterns.
  • General knowledge of enterprise software systems and deployment considerations.

Course Set-up

  • Computer with stable internet connection for viewing demonstrations.
  • Web browser for accessing GitHub repositories and resources shared during the session.

Recommended Preparation

Recommended Follow-up

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Segment 1: Agentic Architect Foundations & Enterprise Operating Models (50 minutes)

  • What is an Agentic Architect? Differentiating agent orchestration from simple AI automation
  • Mapping business goals to multi-agent architectures
  • Key concepts: context engineering, lifecycle management, reliability SLOs
  • Demo: Blueprinting an agent ecosystem for enterprise workflows
  • Exercise: Define SLOs and error budgets for a sample scenario
  • Q&A (10 minutes)
  • Break (5 minutes)

Segment 2: Collaboration Patterns, Risk Controls, and Governance (50 minutes)

  • Advanced agent collaboration: hierarchical, parallel, consensus patterns
  • Building guardrails: policy, RBAC, prompt/tool permissioning
  • Failure modes and recovery planning
  • Exercise: Map governance controls to a high-risk workflow
  • Q&A (10 minutes)
  • Break (5 minutes)

Segment 3: Observability, Evaluation, and ROI Frameworks (50 minutes)

  • Monitoring agent performance and tracing workflows
  • KPIs, metrics, and value assessment for agentic projects
  • Building evaluation pipelines: golden datasets, bias checks, incident response
  • Demo: Observability dashboards for agentic systems
  • Exercise: Design an analytics pipeline for agentic ROI and reliability
  • Q&A (10 minutes)
  • Break (5 minutes)

Segment 4: Rollout Strategy, Change Management, and Capstone Review (50 minutes)

  • Designing phased rollouts and stakeholder alignment
  • Change management and auditability in agentic systems
  • Capstone: Draft a one-page rollout blueprint and governance checklist
  • When NOT to deploy agents: identifying anti-patterns
  • Wrap-up and next steps discussion
  • Q&A (5 minutes)

Overall wrap-up and next steps (5 minutes)

Your Instructor

  • Carmelo Iaria

    Carmelo Iaria is an AI Strategy Consultant and award-winning EdTech founder with 30+ years of global experience driving enterprise AI adoption. As creator of the AAMAD framework and the top-rated CrewAI course on Maven, Carmelo specializes in helping organizations build production-ready multiagent systems for real business impact. Featured by the World Economic Forum and trusted by Fortune 500s, he translates complex AI into clear, actionable methods—empowering technical leaders and teams to move beyond demos and deliver robust, scalable automation. As a Perplexity Business Fellow and hands-on instructor, Carmelo’s practical insights and frameworks have enabled countless professionals to architect and deploy agentic systems that transform how enterprises operate.

Skill covered

Software Architecture