From AI Fundamentals to Agentic Automation

Artificial intelligence is moving beyond chat-based assistance into systems that can retrieve organisational knowledge, interpret incidents, modify software and coordinate business processes. Understanding how these systems work is essential before allowing them to take actions inside a real environment.

This course begins with the foundations: what AI is, how machine learning and large language models work, how prompts are processed, and how Retrieval-Augmented Generation grounds responses in external information. It then introduces specification-driven development and the structure of an agentic automation harness capable of receiving an incident ticket, investigating the problem, proposing a fix, raising a pull request and progressing towards deployment under human approval.

A focused amount of theory is deliberately included because many AI risks—such as prompt injection, sensitive-data exposure, unreliable outputs, excessive permissions and untraceable automated decisions—are not immediately visible to users. Current guidance from NIST and OWASP emphasises that generative AI must be governed throughout its design, deployment and operation, rather than treated as an ordinary software feature.

Approximately the final third of the course will consist of instructor-led, hands-on demonstrations. Python will be used as the primary demonstration language, with Google Workspace presented as an alternative technology stack for building accessible business automations through services such as Gmail, Drive, Docs and Sheets.

The instructor brings more than 30 years of industry experience and will present practical, industry-demanded content rather than an academic treatment of the subject.