WiseBlock - AI Productivity App
AI-powered app to combat procrastination and digital distractions
Problem we worked on
This project came from a real problem I’ve noticed affecting me and a lot of my peers at school. Take a guess…
It’s PROCRASTINATION
Over time, I’ve come to accept it as a natural phenomenon and figured out strategies to deal with it. But here’s the thing – we’re living in an economy where tech companies invest heavily in capturing our attention. They understand our behavior patterns really well, which makes staying focused more challenging.
So I thought: what if we could use similar technology differently?
What if, instead of AI helping companies keep us engaged, it could help us stay productive? That’s when WiseBlock was born.
WiseBlock uses behavioral understanding similar to what tech companies use – except it works to help YOU focus. It learns your patterns, predicts when you’re about to procrastinate/distract yourself, catches you when you’re already distracted, and comes up with creative strategies to help deal with it. Plus, it blocks distracting websites before you even get the chance to click on them.
Think of it like having a productivity buddy with you 24/7 who gently (or sometimes firmly, depending on what you need) reminds you to stay on track. It’s the friend who knows when you need a nudge versus when you need someone to just close Reddit for you.
Product Development
As a part of the Product Development for Engineers class, we turned this idea into a full product proposal:
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Market Research – Surveyed people of different age groups to understand their digital habits and work behavior patterns.
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Competitor Analysis – Analyzed existing productivity apps and websites like Forest, Focus and Freedom etc., to understand their features and identify gaps we could fill.
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Market Specification – Defined user requirements with target and minimum performance criteria for AI blocking features.
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Product Specification – Developed test methods to validate user requirements against target and minimum acceptance criteria for quality assurance.
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DFMEA (Design Failure Mode and Effects Analysis) – Identified potential failure points and and established recommended mitigation actions.
Results
Presented to industry experts who provided valuable feedback on both the concept and implementation strategy. Got an “A” in the course which was like an icing on the top, but most importantly had fun learning about building products and ideation and iteration.