Prompt Engineering for Managers and Non-Developers

Master prompt engineering to effectively communicate with AI tools, boost productivity, and optimize business outcomes, no coding or technical background needed.

Artificial Intelligence

2 Hours

Description

AI tools like ChatGPT and other large language models are quickly becoming core productivity accelerators for product, project, design, and engineering teams. But most professionals lack the skills to communicate with these models effectively. This workshop teaches managers how to think, structure, and iterate prompts to improve clarity, reduce rework, and generate reliable outputs. Participants will learn practical prompt patterns, apply them to real work scenarios, and walk away able to guide their teams on safe, effective AI usage.

Course Objectives

Understand how large language models interpret instructions and context. Write clear, structured prompts using role, task, format, and constraints. Apply prompt patterns for analysis, planning, synthesis, research, and writing. Iterate prompts using feedback loops and evaluation criteria. Detect hallucinations and improve accuracy with grounding techniques. Use prompting for project briefs, meeting summaries, requirements, and stakeholder communication. Coach teams on responsible AI usage, privacy protections, and review practices. Build reusable prompt libraries for consistent team outputs.

Target Audience

People Managers and Team Leads. Product Managers and Project Managers. Scrum Masters, TPMs, and Business Analysts. Change managers, operations managers, and consultants.

Basic Understanding

Ideal for anyone using AI to improve clarity, speed, and decision-making.

Course Content

No sessions available.

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Prompt Engineering for Managers and Non-Developers

Session 1: Kickoff & Mental Models

  1. What LLMs are (and are not)
  2. Why bad prompts fail
  3. Task vs. context vs. constraints

Session 2: Prompt Structure Fundamentals

  1. Role assignment (“Act as…”)
  2. Clear task statements
  3. Output formatting (tables, lists, JSON, outlines)
  4. Constraints and success criteria

Session 3: Prompt Patterns for Managers

  1. Summarization (structured vs. abstract)
  2. Comparison and decision matrices
  3. Action plan generation
  4. Meeting note extraction
  5. Risk identification
  6. Dependency mapping

Session 4: Iteration & Refinement Loops

  1. “Critique your own answer” prompting
  2. Chain-of-feedback patterns
  3. Prompt decomposition (breaking complex tasks down)

Session 5: Grounding & Accuracy Techniques

  1. Provide context documents
  2. Ask for citations and sources
  3. Use stepwise reasoning
  4. Reality checks and verification prompts

Session 6: Reducing Bias & Hallucination

  1. Stating unknowns explicitly
  2. Asking for confidence scores
  3. Scenario testing
  4. Multiple-perspective interrogation

Session 7: Prompting for Communication

  1. Tone shifting for executives vs. peers
  2. Message distillation
  3. Email drafting and rewrite patterns
  4. Explainer prompts for technical topics

Session 8: Prompting for Planning

  1. Work breakdown structures
  2. Project milestone drafting
  3. Risk registers and mitigation actions
  4. Dependency assumptions

Session 9: Prompting for Analysis

  1. Trade-off matrices
  2. SWOT and alternatives analysis
  3. Root-cause probing
  4. Theme clustering from text data

Session 10: Creating Prompt Libraries

  1. Reusable templates (summaries, retros, specs)
  2. Department-level prompt packs
  3. Versioning and team sharing

Session 11: AI Governance & Safety Basics

  1. Privacy and confidentiality considerations
  2. Review loops with human oversight
  3. When NOT to use AI
  4. Avoiding over-reliance

Session 12: Coaching Teams on Prompting

  1. Common mistakes to watch for
  2. Prompt hygiene practices
  3. Review/feedback frameworks

Session 13: Anti-Patterns

  1. Over-prompting
  2. Blind trust
  3. Output copy/paste culture
  4. Scope creep inside a single prompt

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