Get Better at Prompting and Reviewing AI Responses

Define the work before prompting to reduce model assumptions about the job to be done. That approach yields clearer, culture-aware outputs for tasks like job postings.

Define the job to be done by imagining a colleague completing the task, specify what they need to know, and guide prompts so AI delivers concise, narrative outputs.

Define good before prompting to set a target, then tailor output for the task, audience, and minimal editing with talking points.

Learn to define the task, shape the output, and strengthen responses by mixing basic prompts with focus, roles, and multi-perspective techniques.

Explore how prompt levels: basic, focus, role, and process shape outputs from simple answers to rich analysis. Learn to frame prompts for clear problem statements and repeatable processes.

Explore prompt techniques that define how the model should act, shape outputs, and generate multiple perspectives with constraints to improve AI outputs and adoption planning.

Enhance prompts by adding context and criteria to specify the situation and the desired output, guiding AI to deliver accurate, timely results.

Add specific data to prompts to improve outputs, making responses more personalized and relevant. Select only task-relevant data—documents, emails, notes, transcripts, images, or videos—to guide analysis and avoid flawed results.

apply power moves to prompts to reduce assumptions, ask clarifying questions before answering, build and verify a plan, and identify missing information for clearer outputs.

Define the task, shape the output, and feed context to choose prompting techniques that fit the task. Iterate in the improvement loop by evaluating results and refining prompts.

Learn to evaluate AI outputs as a core prompting skill by naming what is wrong, diagnosing causes, and guiding concrete improvements in formatting, tone, accuracy, and completion.

Spot common AI hallucinations in work tasks by recognizing factual, source/reference, company/industry, and reasoning/context errors; learn to rewrite prompts, verify sources, and treat AI output as a first draft.

Learn practical prompting strategies to reduce AI hallucinations, including being specific about what you want, telling it not to guess, citing sources, separating tasks, and providing data to guide reasoning.

Master the iteration loop to turn prompts into higher quality outputs by evaluating results, giving specific actionable feedback, and refining with constraints, examples, and critique.

Reflect on your prompts during the iteration cycle to identify what works, what’s missing, and what to rewrite, then test revised prompts to improve results.

Recognize two signals to stop iterating: frustration, and when doing it yourself is faster than relying on artificial intelligence.

Explore prompt libraries and templates to simplify prompting by reusing structured prompts with placeholders. Build and share a team prompt library to accelerate learning, customization, and consistent ai results.

Learn how ai can write your prompts by answering tasks, outputs, and audience questions, then convert them into high-quality prompts or templates for reuse.

Build a personal prompt library of 10–20 reusable templates for project management, covering planning, stakeholder communication, risk management, and execution, with placeholders for easy reuse.

Discover your AI learning journey with a five-question snapshot that reveals where you stand, what you're strong at, what to work on, and your archetype as a strategic catalyst.