WikiPRO

from its inception, wikipro was driven by a need to understand how modern users actually consume information. faced with rising competition from instant ai chatbots, the project set out to bridge the gap between "quick scanners" and "expert seekers," mapping their behaviors to uncover the hidden friction within the world's largest encyclopedia.

to get an accurate picture, i conducted foundational interviews with users ranging from high schoolers to graduate students . by mapping their behaviors across a utility-vs-experience matrix , i identified four distinct user archetypes: fact checkers, explorers, deep learners, and elite researchers . i then tracked these groups through a four-stage research journey—planning, execution, deep research, and post-research.

this deep dive revealed critical pain points. users constantly struggled with dense text walls, confusing link quality, scattered facts, and the inevitable tab overload that plagues deep research sessions . furthermore, there was a clear need to find a sustainable revenue model that didn't rely on aggressive donation drives or cheapening the site with intrusive ads.

using a moscow prioritization framework , i filtered the proposed solutions to focus purely on high-impact features. the final execution elevates wikipedia to 2025 design standards without compromising its open-knowledge ethos . it introduces a cleaner information architecture , semantic search for intuitive discovery , robust cross-article note-taking , personalized ui themes , and wikipal—an integrated ai assistant for instant summarization and fact-checking . ultimately, this creates a sustainable "pro" ecosystem that keeps core knowledge entirely free, while giving power-users the modern, frictionless tools they need.