Carmelo Iaria

Cohort 1

Cohort 2

Most HITL implementations are basic approve/reject workflows that waste human expertise. Master sophisticated human-AI collaboration patterns where feedback becomes learning data, and you'll build systems that amplify human intelligence rather than bottleneck it. This elevates you from building simple chatbots to designing transformative business automation.

CrewAI Lightning Lesson Series - LL4

Master advanced memory architecture and you'll build agents that actually learn from interactions, remember context across sessions, and scale to enterprise workloads.

CrewAI Lightning Lesson Series - LL3

Master advanced prompt engineering and persona architecture, and you'll build agents with consistent, professional personalities that adapt to different collaboration contexts.&nbsp;

CrewAI Lightning Lesson Series - LL2

Slides used during Lightning Lesson #1 where I've shared a framework to master the strategic choice between autonomous agents and controlled workflows.&nbsp;

CrewAI Lightning Lesson Series - LL1

What if the future of building complex products isn’t about being the fastest coder, but about orchestrating a team of specialized AI agents—where your value lies in design, coordination, and vision, not just in the code you write? In this article I share some of my learning from building Agentic AI applications for enterprise clients and a link to a practical framework that will allow you to maintain the Agency required to preserve the economic and contextual value of YOUR work.

The Rise of the Agentic Architect

In this Project-based course, you’ll go beyond prototyping and build a real, production-ready AI application using CrewAI and the AI Assisted Multiagent Application Development (AAMAD) framework. A Capstone-based Learning ExperienceYou will choose ONE real-world enterprise use case (Automated Employee Onboarding Workflow, Multiagent Customer Support Crew or Sales Enablement Automation Crew) as your Capstone Project. Then you will design, build, and deploy a robust multiagent system—learning the actual process AI consultants use to land and deliver six-figure projects. An AI-Assisted Development ExperienceDeveloping applications with AI Coding Agents such as CursorAI or Claude Code does give you a lot of speed but can be very frustrating at times. This is why I developed a method that adds reliability and robustness to the AI-assisted software development process. I called it AI-Assisted Multiagent Application Development (AAMAD) framework and it is available open source on GitHub. In this course I will guide you to use the agent personas, cursor rules and templates available on this framework to develop your Capstone Project Here’s exactly what you’ll do:1. Set up your development environment in CursorAI and load the coding agents personas, rules and templates provided by the open source AAMAD framework.2. Create the project scope documents (Market Research and Product Requirements Document).3. Architect a complete multiagent solution with defined roles, workflows, and interactions.4. Build the Frontend of your multiagent enterprise application.5. Assemble and configure agents and crew in CrewAI—backend logic, integrations, and custom tools.6. Integrate your solution adding human feedback, observability.7. Optimize your application and run robust QA.8. Deploy, validate, and present your capstone solution, just as you would for a paying client or an executive stakeholder at your company. No filler, no generic demos, no passive content consumption.Every lesson and live session is mapped to building your own application, with direct coaching and code reviews along the way. You’ll finish with a production-grade capstone you can showcase in your Portfolio.

Build real applications where AI agent teams solve complex business use cases

Course syllabus

5+ years engineering or AI dev. experience. Intermediate Python skills.

Experience & Background

Basic API/web service knowledge. GitHub and AWS (or similar cloud) account.

APIs & Cloud Platforms

REQUIRED: CursorAI Pro, OpenAI API access ($20+ in credits), GitHub, AWS access, Python - RECOMMENDED: Perplexity Pro

Required Tools & Access

This will be our weekly live synch. We'll dedicate the first 30 minutes going over the key learning objectives for the week. We will then leave the remaining 60 minutes to address any questions you might have about the content or any challenges you may face in the project.

Tuesdays

Schedule time in your calendar to explore our learning resources and work on your weekly deliverables for the capstone project.

Weekly projects

Course schedule

AI/ML engineers at consulting firms, stuck with basic chats, want frameworks to build complex multiagent systems and win big contracts.

Tech leads and engineering managers asked to deliver AI projects, need architecture skills to turn demos into robust systems fast

Freelance AI consultants who want to escape low-fee gigs and sell enterprise-grade, production-ready agent solutions.

Who is this course for

What you’ll get out of this course

Design, build, and deploy a full multiagent system for an actual enterprise problem, with step-by-step guidance, weekly milestones, and direct code reviews.

Ship a Real-World AI Capstone—Not a Demo

Learn how to master Context Engineering best practices using the open source AAMAD framework and add robustness to your AI-Assisted software development process.

Apply the AAMAD Framework End-to-End

Apply CrewAI’s advanced architecture for orchestrating agent teams, assigning specialized roles, and managing complex workflows—a differentiator between you and commodity AI developers.

Master CrewAI for Production Use

Every live session is hands-on: real code reviews, architecture troubleshooting, and open Q&amp;A—skip the fluff and get answers tailored to your build.

Get Technical Feedback, Fast

Collaborate, critique, and get actionable feedback from peers with similar technical backgrounds and career ambitions.

Join an Expert Peer Network

Architect, build, and deploy a production-ready multiagent AI solution—step by step, on real enterprise use cases, with CrewAI and AAMAD.

Cisco

Claro Brasil

Pearson

Build your AI Moat as Software Developer in 2026

CEO at Synaptic AI Consulting | Perplexity Business Fellow

Daniel Adornes

Shift from coding tasks to orchestrating AI systems that amplify your impact.

Think Like an Agentic Architect

Discover how to design skills and systems that keep you competitive in 2026.

Build Your AI Moat

Learn frameworks to blend AI agents and human creativity for scalable results.

Orchestrate Human‑AI Collaboration

Advanced Observability and Performance

Set up comprehensive monitoring with metrics, traces, and alerts for multiagent system health and performance tracking

Implement Advanced Observability Beyond Basic Logging

Create monitoring that detects performance degradation patterns and prevents failures before they impact users.

Build Predictive Performance Monitoring Systems

Implement efficient resource usage tracking and optimization techniques for sustainable enterprise deployments.

Master Cost Optimization and Token Management Strategies

Human-in-the-Loop Design Patterns

Create HITL systems that ask context-aware follow-up questions and adapt dialogue based on human responses.

Build Dynamic Conversation Flows with Adaptive Questioning

Design feedback mechanisms where human corrections become training signals that enhance future agent performance.

Implement Iterative Refinement Loops for Agent Improvement

Build multi-step processes where human input seamlessly flows between agents while maintaining workflow continuity.

Architect Context-Aware Feedback Integration Systems

Build scalable Multiagent Memory Architectures

Founder & CEO at Synaptic AI Consulting | Perplexity Business Fellow

How to design and implement CrewAI's four memory types (Short-Term, Long-Term, Entity, Contextual) with custom storage

Architect Multi-Layer Memory Systems for Enterprise Scale

Configure memory persistence and retrieval patterns enabling agents to learn from interactions and improve over time

Build Self-Improving Agents Through Memory Optimization

Master memory storage optimization with vector databases and caching for enterprise-grade speed and reliability

Implement Production-Ready Memory Performance Patterns

Advanced Prompt Engineering & Agent Personas

Create specialized agent personalities that maintain professional tone while adapting to different business contexts.

Design Agent Personas for Enterprise Brand Consistency

Implement prompt_file attributes and template systems for consistent, maintainable agent behavior across projects.

Master Custom Prompt Templates and File Integration

Build prompt strategies that enable seamless collaboration between agents with distinct roles and expertise areas.

Apply Context Engineering for Multi-Agent Coordination

Flows vs. Crews: When Structure Beats Autonomy

Develop judgment to choose Crews vs Flows based on business requirements, risk tolerance, and enterprise needs.

Apply Strategic Decision Framework for Automation

Implement @start(), @listen(), @router() decorators for structured workflows with precise control and AI intelligence.

Master Flow Architecture Patterns with Decorators

Architect systems where Flows orchestrate processes while Crews handle complex reasoning for optimal performance.

Design Hybrid Systems Combining Flows and Crews

Go from Idea to Deployed Multi-Agent App in 30 minutes

Learn a clear, repeatable process to turn business needs into live multi-agent AI solutions.

How to apply a Plug-and-Play Workflow to any Use Case

Discover how to use Perplexity, CursorAI, and CrewAI to define, architect, and build a production-ready AI solution

Build complex Multi Agents Systems using proven tools

Build AI solutions—from idea to launch—independently and confidently, bridging skills across tech and business.

Carmelo Iaria

Carmelo Iaria

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Lightning Lessons

Resources