Prompt Engineering & AI Workflows for Professionals
The gap between an average AI user and an exceptional one is no longer access — everyone has the same tools. It is method: the exceptional user treats a prompt as a specification and a task as a workflow, because reliability is designed, not hoped for.
Format
Classroom · Virtual
Upcoming sessions
Pick a session to applyADMISSIONS OPENThe programme
This two-day prompt engineering course is the advanced stage for professionals who already use AI assistants and want results they can stake their name on. It replaces trial-and-error prompting with structure: instructions built from role, context, constraints, examples and output format, iterated rather than lucked into. From single prompts it moves to multi-step AI workflows — a market briefing or board paper decomposed into staged tasks, each step checked before feeding the next. Participants take these methods into documents and spreadsheets — drafting, restructuring, formula logic, data descriptions — and assemble a personal AI toolkit — tested prompts, templates and workflows curated for their role. Quality control runs throughout: rubrics for judging output, verification of facts and figures, and the rule that no AI-assisted deliverable ships unreviewed. Best taken after our Generative AI at Work programme or equivalent daily practice, and available in-house for teams standardising advanced practice. Delivered in English and French across the Middle East, Africa and Asia — Dubai, Nairobi, Johannesburg, Kuala Lumpur — and live online.
What you will do
Who attends
Professionals who already use AI assistants most working days and want to move from useful to formidable: analysts, consultants, project and programme managers, marketing and communications specialists, finance and strategy teams, and the internal champions expected to raise everyone else’s practice. Participants should be comfortable with everyday AI use — this programme builds on that base rather than laying it. In-house cohorts work on their organisation’s real deliverables and leave with a shared workflow library.
Programme agenda
Built for the decisions no textbook prepares you for
I.From prompting to prompt engineering
- Why results vary: what the model actually does with your instruction
- The structured prompt: role, context, constraints, examples, output format
- Deliberate iteration: diagnosing weak output and fixing the instruction, not the mood
II.Advanced prompting techniques
- Examples and counter-examples: showing the model what good looks like
- Step-by-step reasoning, self-critique and asking the model to check itself
- Long documents and context management: working beyond the single question
III.Multi-step AI workflows
- Decomposing a deliverable: research, outline, draft, critique, polish as separate stages
- Checkpoints between steps: catching drift before it compounds
- Worked builds: a market briefing and a board-ready paper, end to end
IV.AI in documents & spreadsheets
- Drafting and restructuring inside the document instead of beside it
- Spreadsheet work: formula logic, data cleaning steps and describing what the numbers say
- Knowing the boundary: what to trust the assistant with, and what stays manual
V.Quality control of AI output
- Rubrics for judging output: accuracy, completeness, tone and fitness for purpose
- Verification passes for facts, figures and citations before anything ships
- Accountability: the professional owns the deliverable, whoever drafted it
VI.The toolkit clinic
- Building your personal library: prompts, templates and workflows for your actual role
- Testing and versioning: keeping the toolkit sharp as tools evolve
- Sharing with the team: standards, curation and raising the collective floor
Frequently asked
How does this differ from an introductory AI course?
It is the advanced stage. Introductory programmes build everyday fluency; this course assumes it, and replaces trial-and-error prompting with structure — prompts built as specifications from role, context, constraints, examples and output format; deliverables decomposed into multi-step workflows with checkpoints; and systematic quality control of the output. Participants should already be using AI assistants most working days.
Do I need to take Generative AI at Work first?
Not formally, but the programme is best taken after our Generative AI at Work course or equivalent daily practice. It builds on an existing base of everyday AI use rather than laying one, so participants who are already comfortable instructing an assistant and reviewing its output will get the most from the two days.
What do participants take away from the course?
A personal AI toolkit: a curated, tested library of prompts, templates and multi-step workflows built for their actual role during the closing clinic, together with the rubrics and verification passes that keep output trustworthy. The habit of testing and versioning keeps the toolkit sharp as the tools themselves evolve.
Is an in-house edition available, and how are dates and fees arranged?
Yes — the course is available in-house for teams standardising their advanced AI practice, tailored to the institution and worked on its real deliverables, with a shared workflow library as the result. Dates follow a rolling calendar — including Dubai, Nairobi, Johannesburg and Kuala Lumpur, plus live online — and are confirmed on request; fees are provided by quotation on enquiry. Delivery is in English and French.
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