Module 2: The Rise of Agentic AI and Emerging AI Platforms

Summary: Welcome to Module 2! If Module 1 was about understanding what generative AI is, this module is about watching it grow up into something far more powerful — agentic AI.

What Is This Module About?

Welcome to Module 2! If Module 1 was about understanding what generative AI is, this module is about watching it grow up into something far more powerful — agentic AI.

Think of it this way: generative AI is like a very talented assistant who answers your questions brilliantly. Agentic AI is like that same assistant, now given a phone, a computer, a calendar, and the authority to act — booking meetings, writing reports, running code, and coordinating with other assistants — all on your behalf.

💡 What This Means: "Agentic" means capable of taking action. Agentic AI doesn't just respond to prompts — it pursues goals, makes decisions, and executes multi-step tasks with minimal human supervision.

What You'll Explore in This Module

This module covers four major areas:

1. Emerging Agentic Platforms

The AI tools market is evolving fast. We examine five leading platforms — LangChain, CrewAI, Ollama, Codex, and n8n — and break down what each one does, who it's for, and where its limits are. Think of this as a buyer's guide to the agentic AI ecosystem.

2. Vibe Coding — Programming Without Being a Programmer

One of the most exciting shifts in tech right now: you can describe what you want in plain English, and AI writes the code. This "vibe coding" movement is democratising software development. We explore what it means, how to use it responsibly at scale, and what tools are available today.

3. Single vs. Multi-Agent Architectures

Some tasks are simple enough for one AI agent. Others — like running a whole business process — need a team of agents working together. We explain the five types of agents, from simple reflex bots to sophisticated learning agents, and show how multi-agent systems work like a well-coordinated team.

4. Open-Source vs. Closed-Source AI

Should your organisation build on open tools that anyone can inspect and modify, or rely on polished proprietary platforms? We weigh the trade-offs and help you think strategically about this crucial choice.

Why This Module Matters

⚠️ Why This Matters: The organisations that understand the landscape of agentic platforms today will be best positioned to make smart technology investments tomorrow. This module equips you with the knowledge to evaluate, compare, and choose the right AI tools — not just follow the hype.

Key Takeaways

• Agentic AI goes beyond answering questions — it takes actions autonomously
• A new ecosystem of platforms (LangChain, CrewAI, n8n, etc.) is making agentic AI accessible to businesses of all sizes
• "Vibe coding" lets non-programmers build software using plain language
• Multi-agent systems combine specialised AI agents for complex, end-to-end tasks
• The open vs. closed source debate has real implications for cost, privacy, and control

Module 2: Learning Objectives

Summary: By the end of Module 2 — The Rise of Agentic AI and Emerging AI Platforms — you will have developed three core skills:

What You Will Be Able to Do After This Module

By the end of Module 2 — The Rise of Agentic AI and Emerging AI Platforms — you will have developed three core skills:

🎯 Objective 1: Evaluate Agentic AI Platforms

You will be able to: Assess the core benefits, drawbacks, and implementation considerations of emerging agentic AI platforms.

In plain terms: When someone pitches you on using LangChain or n8n or CrewAI for a project, you'll know the right questions to ask. What does it actually do? What are its limitations? Is it the right fit for our team and our budget?

🎯 Objective 2: Articulate AI-Assisted Coding Governance

You will be able to: Explain the key operational and governance factors needed when adopting AI-assisted coding tools at scale.

In plain terms: "Vibe coding" is exciting, but deploying it across an organisation requires guardrails. You'll understand what those guardrails are — compliance rules, quality checks, skill training requirements — and why they matter.

🎯 Objective 3: Design an AI Solution Blueprint

You will be able to: Develop a high-level AI solution blueprint that incorporates key considerations for enterprise-level AI adoption.

In plain terms: You'll be able to sketch out a plan for how an AI system could be built and deployed in your organisation — choosing the right platforms, architectures, and governance structures.

How These Skills Connect

Key Takeaways

• This module builds decision-making skills, not just awareness
• You'll learn to critically evaluate AI platforms — not just use them
• Governance is as important as capability when adopting AI tools
• The module culminates in the ability to design your own AI solution blueprint