Better AI Prompts for Better Results

Learn how to write better AI prompts that produce clearer, more useful results for business. This hands-on course teaches practical prompt engineering techniques for tools such as ChatGPT, Microsoft Copilot and Gemini, including how to add context, set constraints, refine responses and review AI-generated content before using it.

Overview

This course develops prompting as a professional communication and judgment skill. Participants learn to translate workplace assignments into clear AI briefs that define the intended outcome, evidence, audience, boundaries, deliverables and review threshold.

Using realistic business scenarios, participants practice creating prompts that produce relevant, evidence-based outputs for human review. The course emphasizes critical thinking and decision making before prompting, evaluating AI responses against defined criteria and retaining accountability for the final result.

Who Should Attend

• Professionals at any level and in any function who want to use generative AI more effectively for everyday work.

How You Will Benefit

• Save time by converting complex assignments into precise AI work specifications before generating an answer
• Improve relevance and consistency by defining evidence, audience, boundaries, deliverables, and review threshold
• Use AI across common professional tasks without relying on platform-specific commands
• Strengthen outputs through follow-up questions, critique, revision, and comparison
• Reduce risk by protecting sensitive information and checking facts, sources, assumptions, and bias
• Leave with a personal AI work brief, a review-threshold guide, and one ready-to-use prompt sequence

What You Will Cover

• How generative AI interprets instructions—and why vague prompts lead to generic or unreliable answers
• The Six Prompt Directive: outcome, evidence, audience, boundaries, deliverable and review threshold
• How examples, source material, audience, tone, and constraints shape output quality
• Prompt patterns for drafting, summarizing, analyzing, brainstorming, planning and decision support
• How to iterate: ask, inspect, challenge, refine, and reuse
• The Four-Move Revision Cycle: diagnose, redirect, compare and commit
• The Review Threshold Ladder: use, revise, verify, escalate or reject
• Privacy, confidentiality, copyright, bias and appropriate human oversight

Outline

• Learning Objectives
• Identify how prompt clarity, context, and constraints affect generative AI outputs.
• Construct an AI work brief by making the Six Prompt Directives.
• Select and apply prompt patterns appropriate to common business tasks.
• Improve an initial response through targeted follow-up and revision prompts.
• Recognize information that should not be entered into an AI tool and identify when human review is required.
• Build one reusable prompt or mini-workflow for an immediate job need.
• Building an Effective AI Work Brief
• Identify how prompt clarity, context, and constraints influence the quality and usefulness of generative AI outputs
• Recognize the capabilities and limitations of tools such as ChatGPT, Gemini, Copilot, and other generative AI assistants
• Apply the Six Prompt Directives to define the outcome, evidence, audience, boundaries, deliverable, and review threshold
• Construct and test an AI work brief for a common workplace assignment
• Applying Prompt Patterns and Improving Responses
• Select prompt patterns for drafting, summarizing, extracting information, analyzing, brainstorming, and planning
• Use approved notes, documents, and data to provide relevant context and source material
• Match the response format, length, tone, and level of detail to the intended audience and business need
• Improve an initial response with targeted follow-up prompts that critique, redirect, compare, tighten, and reformat
• Apply prompting techniques to realistic business scenarios across departments
• Applying Prompt Patterns and Improving Responses
• Review AI-generated content for accuracy, relevance, completeness, appropriate tone, and usability
• Identify when an AI response requires revision, independent verification, qualified human review, escalation, or rejection
• Consider data privacy, bias, copyright, organizational policy, professional voice, and human accountability
• Verify factual claims, assumptions, and missing information
• Recognize personal, confidential, regulated, client, and proprietary information that should not be entered into an AI tool
• Convert a successful prompt into a reusable template or mini-workflow for an immediate job need