An Engineering Graduate’s Journey to Smarter AI Projects

The story

The Situation

When I started my final-year project, I knew I wanted to work with AI. The problem was, I wasn’t sure how to move beyond just building something that looked technical. I worried that my project might seem impressive on paper but wouldn’t actually solve a real problem or make sense to others.
Patterns

Our Approach

The UX for AI Manual helped me ask the right questions: when AI should be used, how to explain it clearly, and how to responsibly build my dataset. Its patterns gave me a framework that turned confusion into clarity and kept my project grounded.
Helped me confirm if AI was necessary, so my project focused only on areas where AI added meaningful value.
Guided me to translate technical outputs into clear outcomes, making my work understandable to professors and peers.
Taught me to consider accuracy, fairness, and credibility in my dataset, so the project results were reliable and defensible.
Activities

The Key Steps

How Might We
Turned vague challenges into design opportunities, helping me frame my project with creativity.
One Minute Pitch
Pushed me to explain my project’s value quickly and simply, which connected better with reviewers.
Stakeholder Map
Made me think about professors, peers, and end-users as different audiences, guiding how I shaped the project.
Lessons Learned
Encouraged reflection at each stage, helping me adapt and improve my work step by step.
Recommendation

Build Your Academic Project with AI Features

The UX for AI Manual helps students create AI projects that impress professors during evaluations and give you the confidence to stand out in job interviews.
“The UX for AI Manual gave me structure and focus. It helped me design an academic project that was not only functional but also responsible and easy to present.”
H&N
Rebecca Roy
H&N – CEO & President
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