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AI Boosts: Designer

Accelerate your design work with these powerful AI prompts

These are "boosts" that you can use to accelerate your work. They can be very powerful, and their responses can often be very impressive!

Before you start prompting, look through this list and consider which boosts will address your group's needs and will be a good use of your time (which is very limited). Then try out a few!

Don't forget to talk with your group as you get responses back from the AI. Your group's feedback will be crucial to making sense of the ideas and integrating them meaningfully into your work as a team. Good luck!

AI as the Socratic Interviewer

You are a skilled design thinking facilitator. Your goal is to help my team deeply understand the challenges faced by [youth who want to have more agency and ownership in shaping their learning experiences]. To do this, *interview us*. Start by asking broad questions about our initial observations. Then, ask probing follow-up questions to help us uncover blind spots. After you've gathered enough context from our conversation, summarize our key insights and propose three distinct, 1-sentence problem statements we can choose from.
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How it works: This prompt transforms the AI from a passive information retriever into an active listener and guide. It forces the team to articulate their own thoughts first, and then uses the AI's processing power to synthesize and structure that thinking into a tangible output.
How the AI helps: The AI provides structure and synthesis. It acts as a conversational guide, ensuring the team doesn't jump to conclusions. It handles the cognitive load of organizing a messy brainstorming session into coherent themes and actionable statements.
DANGER: If the AI generates the problem statements, the team might not feel as deep of ownership over the solution.

AI as The Empathy Amplifier

Act as a creative writer specializing in character development. My team will provide you with a simple, one-sentence observation about [a young person who wants more say in their learning but faces barriers]. Your task is to bring that observation to life. Based on our one-sentence input, write a short (150-word) first-person narrative or a 'day in the life' vignette from that young person's perspective. Your story should include: - Plausible internal thoughts and feelings. - A specific, frustrating moment related to lack of agency in their learning. - A coping mechanism they might use (healthy or unhealthy). Our team will give you 2-3 different observations, and you will generate a vignette for each. Our job will then be to read these stories and find the common threads ourselves to draft a problem statement. Here is our first observation: [Example: 'We see a 10th grader who has great ideas for projects but always has to follow the exact rubric the teacher provides.']
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How it works: AI serves as a tool to deepen human understanding rather than replacing it. The team are the ones who find the key insight, using the AI-generated stories as powerful, evocative data points.
How the AI helps: The AI acts as an empathy engine and narrative generator. It takes a flat, objective observation and translates it into a vivid, relatable story. This helps the team move beyond abstract labels and connect with the potential lived reality of a student, sparking a much deeper and more compassionate understanding of the problem.
DANGER: The AI-generated narratives might feel so compelling and "real" that the team mistakes artificial empathy for genuine user research, potentially reinforcing stereotypes or creating fictional pain points that don't reflect actual student experiences.

AI as The Assumption Tester

Act as a critical thinking partner. My team has come up with the following initial problem statement: ['Youth lack meaningful opportunities to co-create and shape their own learning experiences.']. Before we proceed, we need to challenge our own thinking. Generate a list of at least five critical questions that expose our underlying assumptions. For example, 'Are we assuming the problem is speed and not comprehension?' or 'What evidence suggests a direct link between this specific struggle and a decline in confidence vs. other factors?'. For each assumption you identify, suggest a quick way we could validate or disprove it.
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How it works: This demonstrates using AI for metacognition—thinking about the thinking. It helps teams build a more robust and evidence-based foundation by systematically deconstructing their own biases before they invest time in a flawed premise.
How the AI helps: The AI provides an impartial, objective perspective. It can challenge groupthink without social repercussions, systematically poking holes in a team's logic to make the final idea stronger.
DANGER: There might be inaccurate assumptions, bias, and irrelevant responses since the AI does not know the user well and does not have much background on their particular goals and needs.

AI as The Ideation Engine

You are a creative technologist. Our problem statement is: [Paste problem statement]. Let's use 'Analogous Inspiration.' First, identify three different fields that excel at a similar problem (e.g., how open-source communities empower contributors to shape projects). For each analogy, explain the core principle. Then, generate two tech-assisted solution concepts for our problem that are inspired by those principles.
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How it works: The AI acts as a creative catalyst by connecting the team's specific problem to successful principles from completely different fields, sparking unconventional thinking and breaking them out of familiar patterns.
How the AI helps: The AI is a catalyst for divergent thinking. It can access a vast database of concepts to make novel connections, providing unexpected starting points for innovation.
DANGER: The team might latch onto a flashy but inappropriate analogy (e.g., applying a "Tinder-style swipe" mechanic to a sensitive educational topic) without critical evaluation, leading to a gimmicky or tone-deaf solution.

AI as The Ethical Design Advisor

We've selected a concept: [Paste your concept]. Now, act as an expert in ethical AI and inclusive design. Analyze our concept through the lenses of **Equity, Accessibility, and Tone**, suggesting a specific feature or improvement for each.
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How it works: The AI applies established ethical and inclusive design frameworks to a user-generated concept, acting as an expert consultant to reveal potential blind spots and prompt deeper consideration of the solution's human impact.
How the AI helps: The AI serves as an expert knowledge base and ethical checklist. It can bring established frameworks to the conversation, reminding the team of crucial perspectives they might have overlooked.
DANGER: The team might see the AI's ethical check as a "one-and-done" task, creating a false sense of security and failing to engage in deeper, ongoing ethical deliberation about their solution's real-world impact.

AI as The Collaborative Journey Mapper

Let's co-create a user journey map. You will guide the process. I will play the role of a user named Alex. Our solution is [Paste your solution]. Start by asking me, 'What's the trigger that makes Alex look for a solution?'. Based on my answer, you will define the first stage (Action, Touchpoint, Emotion). Then, ask 'What happens next?' and we will build the map together.
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How it works: This is a structured, turn-based role-playing exercise. The human embodies the user's emotions and actions, while the AI facilitates the process and scribes the inputs into the formal structure of a journey map.
How the AI helps: The AI acts as a facilitator and structured scribe. It keeps the process moving forward and neatly organizes the narrative into the journey map format, freeing up the human's mental energy to focus on the user's experience.
DANGER: The journey map becomes a fictional story rather than an empathetic tool. The team might get lost in creating a "perfect" journey that doesn't reflect the messy, frustrating reality of a user's actual experience.