Course Format and Delivery

Delivery Method: LiveOnline 
Schedule: 3 sessions of 4.5 hours
Cost: $1,695 USD

All sessions are delivered live by an expert instructor in a fully interactive online environment.

*20% off for group bookings when booking 3 or more attendees from the same organization on the same course dates in the same transaction.

About this course

Your next colleague could be an AI agent—and the businesses learning to work with these agents today are building capabilities you won’t want to discover too late. This practical, three-day course explores the opportunities of 24×7 agent workflows with ChatGPT Dot, Claude Cowork and Meta’s Facebook Muse, connecting AI capabilities to your everyday business environment. Move beyond using AI as a researcher and start delegating meaningful work with clear outcomes, repeatable methods and deliverables in the formats you actually need. Through our memorable “Training the AI Puppy” approach, you’ll practice giving feedback, creating rules, building reusable skills and setting appropriate boundaries. Leave with a business workflow, a practical deployment plan and a clear way to measure value—so your organisation can turn AI excitement into adoption, useful outputs and measurable ROI.

What you will earn

What you will learn

• Prompt engineering techniques to effectively control and optimize GPT outputs.

• Creating and customizing purpose-built GPTs for specific business needs.

• Challenges in AI implementation, including inconsistent responses, hallucinations, and bias.

• Using Retrieval-Augmented Generation (RAG) to enhance GPT performance.

• Technical components of Generative AI, such as Large Language Models (LLMs), inference engines, and the role of GPUs.

• Methods for integrating domain knowledge into GPTs to ensure accurate and consistent responses.

• Developing advanced AI solutions using Python and custom code for specialized GPTs.

• Responsible, ethical and secure AI practices.

• Evaluating and leveraging GPT technology for business innovation and new business models.

What you will need

To get the most out of this course, it is recommended that participants have familiarity with Generative AI through formal training like our AI courses or hands-on experience

This course is great for

• Technology professionals, developers and data scientists wanting to leverage and implement custom GPTs and LLMs for specific business needs or industry applications​

• Business leaders and innovators looking to leverage AI technology to drive organizational transformation and create new AI-powered products or services​

• Anyone looking to master advanced prompt engineering and GPT finetuning techniques​

Topics Covered

Day 1 — Understand the Technology. Find the Opportunity. Define Success.

• AI versus AGI: capabilities, expectations and business implications.
• From AI researcher to AI colleague.
• From prompt engineering and task instructions to defining outcomes.
• Transformers, tokens, context and performance—in business language.
• RAG: connecting AI to relevant business knowledge.
• Finding repeatable tasks with measurable ROI.
• Defining deliverable formats, quality standards and acceptance criteria.
• Lab: select a business workflow and create an outcome brief.

Day 2 — Train Your AI Colleague. Create Rules. Build Skills.

• Meet the agents: ChatGPT Dot, Claude Cowork and Meta Muse.
• Explore local, cloud and 24×7 workflows, capabilities and limitations.
• The secret no one tells you: teach AI how you want the work done.
• “Training the AI Puppy”: demonstrate, practise, review, correct and repeat.
• Lab: create a spaghetti sauce recipe without guidance.
• Lab: remove the onions—give feedback and check the entire result.
• Understand feedback loops versus model-level reinforcement learning.
• Lab: create Rules.md; retrieve and apply it through RAG.
• Lab: introduce AGENTS.md for persistent workspace instructions.
• Explore other locations for project instructions and preferences.
• Lab: build a reusable skill with instructions, templates and quality checks.
• Test fresh sessions, changed requirements and conflicting instructions.
• Lab: translate the recipe skill into a repeatable business workflow.
• Set access, authority, approval and escalation boundaries.

Day 3 — Integrate Responsibly. Create Adoption. Prove Value.

• AI ethics, transparency and human accountability.

• Agent security: sensitive data, malicious instructions and excessive access.

• Governance for agents that operate beyond a single conversation.

• Connect skills, knowledge, applications and business processes.

• Design human approvals, exception handling and recovery.

• Build employee confidence, adoption and ownership.

• Measure output quality, review effort, costs and realised business value.

• Capstone: assemble an integrated business solution and demonstrate its deliverable.

• Create a 30-day pilot with success measures and criteria to scale.

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