On Demand: Agentic AI Fundamentals 2.0

Service Description

Session 1: The Agentic AI Mindset and Business Value What are AI Assistants vs. Agents? (Reactive vs. Proactive, Task vs. Goal) Real ANZ industry use cases and transformation outcomes “Before and After” skills and what this means for your role Session 2: Foundations: How Agents Think and Act OODA Loop: Observe, Orient, Decide, Act – the agentic process Memory, adaptation, autonomy—core capabilities Mapping out a simple agent: sample walkthrough Session 3: Designing Impactful Agent Workflows Step-by-step: From business problem to agent workflow Visual tools: Blueprinting agent pipelines Essential ingredients (inputs, goals, actions, feedback loops) Scaffolded design templates for non-coders Session 4: From Idea to Prototype: Hands-On Design Workshop Breakout activity: Choose a problem, map the agent workflow Tiered tasks for all skill levels (mapping, prototyping, full build for advanced) Peer feedback and facilitator guidance Session 5: Multi-Tool Agents & Integration How agents use APIs, tools, and external services Demo: How does "Building a simple end-to-end agent" with no-code/low-code tools Risks and best practices in agent integration (Microsoft/Google) Q&A: What platform? Session 6: Oversight, Safety, and Ethics in Agentic AI Data sensitivity, bias, and transparency (free vs paid/pro accounts used by individuals and organisations) Defining guardrails, governance, and the human-in-the-loop (AI policy) Practical frameworks: When to intervene Q&A: Real-world ethical dilemmas Session 7: Project Clinic & Expansion Bring your agent blueprint or prototype: rapid-fire feedback from our AI engineer Workshopping common stumbling blocks and “agentic thinking” in real orgs (vibe coding- pros and cons) Scaling up: multi-agent systems, advanced use cases, and workflow optimisation Session 8: Presentations, ROI, and Future Skills Roadmap Volunteer participant demos: share agent blueprints or prototypes Peer and facilitator feedback—emphasis on impact, business fit, and iterating Wrap-up: What transformation-ready teams need next