This is the second course in the LCPS "AI at Work" curriculum. It assumes you have completed Mastering Prompt Engineering — or that you can already write effective prompts, iterate on outputs, and use at least one major AI tool confidently in your day-to-day work.
Where the first course taught you how to talk to an AI well, this course teaches you how to build one that does a specific job for you, your team, or your clients — without writing a line of code.
You will learn how to design, build, test, deploy, and govern custom AI assistants using the features already built into ChatGPT, Claude, Google Gemini, and Perplexity. You will also learn where no-code tooling stops and where genuinely autonomous AI agents begin, so you can read the fast-moving agent landscape critically and know when to ask for developer help.
Take a recurring task from your own department as the starting point. Building Custom GPTs and AI Agents explores how to shape an assistant around that task and judge whether its output meets the brief. The emphasis is on purposeful creation that has a place in real work. A research request or an internal support need provides a concrete reason to learn. Participants explore configuration and organisational knowledge, then consider how testing reveals what still needs refinement before wider use.
Why this Training Matters for your Organisation
Repeatedly explaining the same requirements to an AI tool can make its usefulness depend on the person operating it. An assistant designed for a specific purpose offers an opportunity to make those requirements more explicit.
For a business, the useful question is whether a proposed assistant earns its place in a workflow. This learning encourages staff to assess that opportunity and examine the limitations, so development begins with a defined need and a way to evaluate the result.
Who Should Attend
Best suited to colleagues who know a business process and want to explore an AI solution. Prior prompt-engineering knowledge is expected, whether gained through Mastering Prompt Engineering or equivalent experience.
- Process owners and employees responsible for recurring operational work.
- Customer support leads and teams managing internal knowledge.
- Digital project staff and colleagues developing AI use cases.
