Module 1: Introduction to Agentic AI
- Evolution from Traditional AI to Agentic AI
- What is Agentic AI?
- AI Assistants vs AI Agents vs Autonomous Systems
- How AI Agents Think
- Planning, Reasoning and Execution
- Single-Agent vs Multi-Agent Systems
- Human-in-the-Loop vs Fully Autonomous Workflows
- Business Applications Across Industries
- Future of Autonomous AI
Hands-on Activities
- Explore leading Agentic AI platforms
- Compare AI assistants with AI agents
- Identify automation opportunities in participants’ organizations
Module 2: Modern Agentic AI Platforms
Deep dive into:
- Claude
- Claude Artifacts
- Google AI Studio
- Gemini Models
- Manus AI
- AI Agents
- NotebookLM
- ChatGPT Projects
- Microsoft Copilot
- Emerging Agentic AI Platforms (2026)
Comparison
- Workflow creation
- Business automation
- Application development
- Research
- Coding
- Productivity
- Collaboration
- Enterprise deployment
Hands-on Activities
- Compare outputs across platforms
- Select the best platform for different business scenarios
Module 3: Prompt Engineering for AI Agents
- Agent prompting principles
- Goal-oriented prompting
- Task decomposition
- Context management
- Memory management
- Planning prompts
- Reflection prompts
- Iterative prompting
- Multi-step workflows
- AI reasoning strategies
Hands-on Activities
- Design prompts for autonomous task execution
- Improve workflow reliability using structured prompting
Module 4: Building Interactive AI Applications
Using Claude Artifacts
- Interactive dashboards
- Business calculators
- AI assistants
- Internal knowledge tools
- Report generators
- Learning applications
Using Google AI Studio
- Rapid AI prototyping
- Prompt testing
- Structured outputs
- AI application design
Hands-on Activities
Participants build:
- Interactive business dashboard
- AI-powered report generator
- Internal productivity application
Day 2
Module 5: AI Productivity & Workflow Automation
Automating workplace activities
- Email generation
- Meeting summaries
- Proposal writing
- Research automation
- Data analysis
- Documentation
- Knowledge management
- Customer support
- SOP generation
Tools Covered
- Claude Artifacts
- Google AI Studio
- Manus AI
- Microsoft Copilot
- NotebookLM
- Perplexity AI
- Zapier AI
- Make AI
- n8n AI integrations
Hands-on Activities
Design an end-to-end AI-assisted workflow that automates a common business process.
Module 6: Autonomous AI Agents with Manus & Google AI Studio
- Designing AI agents
- Task orchestration
- Autonomous planning
- Workflow execution
- Multi-step reasoning
- Agent collaboration
- Human approvals
- Error handling
- AI quality control
Hands-on Activities
Participants create:
- Research agent
- Business planning agent
- Document automation agent
- Customer support assistant
Module 7: Responsible Agentic AI & Governance
- AI governance
- Responsible AI principles
- Privacy and security
- Data protection
- AI hallucinations
- AI bias
- Intellectual property
- Compliance
- Risk management
- Human oversight
- Enterprise AI policies
Case Studies
- Successful enterprise AI adoption
- AI automation failures
- Governance best practices
Hands-on Activities
Assess AI agent outputs for accuracy, transparency, compliance, and business risk.
Module 8: Designing an Agentic AI Strategy
- AI transformation roadmap
- Selecting the right AI platforms
- Scaling AI across departments
- Measuring AI ROI
- AI adoption framework
- Future trends in Agentic AI
- Multi-agent ecosystems
- AI operating models
- Building an AI-first organization
Capstone Project
Working in teams, participants will design and present an Agentic AI solution for a real business challenge. The solution should leverage Claude Artifacts, Google AI Studio, Manus AI, and supporting productivity tools to automate a complete workflow—from information gathering and analysis to content generation, reporting, and decision support. Teams will present their architecture, workflow, expected business benefits, governance considerations, and implementation roadmap.