Prompt Engineering for Business Professionals

Course overview

Course outline

1. 1Day 1: Prompt Engineering Fundamentals for Business Applications

   • Understanding prompts, context, instructions, AI responses, and the role of large language models in business applications
   • Identifying why vague, conflicting, or incomplete prompts produce weak business outputs
   • Structuring prompts around objectives, background information, tasks, constraints, audience, and expected deliverables
   • Controlling response format, tone, length, terminology, scope, and level of detail
   • Comparing zero-shot, example-based, and iterative prompting approaches for different professional tasks
   • Practical exercise: Transforming poorly written prompts into structured business prompts and comparing the resulting outputs
2. 2Day 2: Advanced Prompt Design and Context Engineering

   • Providing relevant business context without overwhelming the model with unnecessary information
   • Using examples, reference content, templates, and desired output structures to guide AI responses
   • Breaking complex assignments into smaller tasks through prompt decomposition and staged workflows
   • Using follow-up prompts to clarify, expand, challenge, restructure, and improve generated content
   • Designing prompts that request assumptions, limitations, missing information, and verification requirements
   • Prompt workshop: Developing reusable prompt templates for reports, proposals, emails, summaries, presentations, and executive briefings
3. 3Day 3: Prompt Engineering for Research, Analysis and Decision Support

   • Designing research prompts that define scope, questions, evidence requirements, and expected analytical outputs
   • Prompting AI to summarize, compare, classify, extract, and organize information from business documents
   • Using structured prompts for SWOT analysis, scenario exploration, root-cause analysis, and option comparison
   • Developing prompts for financial, operational, customer, project, and performance-related business questions
   • Challenging AI-generated conclusions through critique prompts, alternative perspectives, and verification steps
   • Case study: Building a sequence of analytical prompts to investigate a business problem and prepare a management decision brief
4. 4Day 4: Building Reusable Prompt Workflows for Business Functions

   • Developing prompt libraries for management, HR, marketing, finance, procurement, projects, operations, and administration
   • Designing multi-step workflows that move from research and analysis to drafting, review, refinement, and final output
   • Creating reusable prompt templates with variables for audiences, objectives, data, constraints, and deliverables
   • Using AI to transform information between reports, tables, summaries, presentations, action plans, and stakeholder communications
   • Establishing human review points for sensitive, high-impact, or decision-related AI outputs
   • Practical workshop: Designing an end-to-end prompt workflow for a recurring professional business process
5. 5Day 5: Prompt Quality, AI Verification and Professional Governance

   • Establishing criteria for evaluating prompt effectiveness and AI response quality
   • Identifying hallucinations, unsupported claims, missing context, bias, and misleading confidence in generated responses
   • Applying fact-checking, source verification, cross-checking, and human review to AI-assisted work
   • Protecting confidential information, personal data, intellectual property, and commercially sensitive business content
   • Measuring prompt effectiveness through accuracy, relevance, consistency, time savings, and reduction in manual rework
   • Capstone exercise: Developing and presenting a Professional Prompt Engineering Toolkit containing reusable prompts, workflow templates, quality checks, and responsible-use controls