Ask LukeW: 2 Years and 27,000 Answers

Time flies (insanely) fast during the AI tsunami all of us in the technology industry are facing. So it was surprising to learn my personal AI assistant, Ask LukeW, launched two years ago. Since then I've kept iterating on it when time allowed and two years later...

Ask LukeW is a feature I created for my website to answer people's questions about digital product design, startups, technology, and related topics. It's designed to provide personalized responses using my body of work in a scalable manner.

Since launching two years ago, people have asked (and the system has answered) over 27,000 questions. That averages out to more than 36 a day, which is definitely more than I'd be able to answer using my physical embodiment. So I've certainly gotten scale from the digital version of me.

Ask LukeW works by using AI to generate answers based on the thousands of text articles, hundreds of presentations, videos, and other content I've produced over the years. When you ask a question, AI models identify relevant concepts within my content and use them to create new answers. If the information comes from a specific article, audio file, or video, the source is cited, allowing you to explore the original material if you want to learn more.

In other words, instead of having to search through thousands of files on my website, you can simply ask questions in natural language and get tailored responses. Behind that simplicity is a lot of work on both the technology and design side. To unpack it all, I've written a series of articles on what that looks like and why. If you want to go deep into designing AI-powered experiences... have at it:

New Ways into Web Content: rethinking how to design software with AI
Integrated Audio Experiences & Memory: enabling specific content experiences
Expanding Conversational User Interfaces: extending chat user interfaces
Integrated Video Experiences: adding video experiences to conversational UI
Integrated PDF Experiences: unique considerations when adding PDF experiences
Dynamic Preview Cards: improving how generated answers are shared
Text Generation Differences: testing the impact of AI new models
PDF Parsing with Vision Models: using AI vision models to extract PDF contents
Streaming Citations: citing relevant articles, videos, PDFs, etc. in real-time
Streaming Inline Images: indexing & displaying relevant images in answers
Custom Re-ranker: improving content retrieval to answer more questions
Usability Study: testing a conversational AI interface with designers