AI Ready: Hannah Hoffmaster - How a Non-Technical Student Became AI-Ready in One Year
Hannah Hoffmaster went from a self-described two-out-of-seven in technical skill to building multi-agent AI tools in a single year at Foster. This episode is for anyone — technical or not — trying to understand what genuine AI fluency looks like and how to build it.
Hannah Hoffmaster is a student completing the one-year MSIS program at the University of Washington Foster School of Business. She came to the program with some knowledge of statistics and R, but little coding experience. Through her coursework — including Prof. Leo Bousioux's AI and Generative AI in Business class — she developed the ability to design and build AI-powered tools, including a charity comparison platform and an ADHD-focused scheduling app. She describes experimenting with AI as something she now does for fun.
We covered alot of ground in this episode:
- How to think about AI as a build tool when you have no coding background
- Why "trust but verify" is the core discipline of working with AI, and how to operationalize it
- How to design a multi-agent workflow around the parts of a task you don't want to do
- What a deliberate, build-first job search looks like in a fast-moving field
- How to stay current as tools change — by building, researching versions, and talking to peers
- Why holding your career goals loosely can be an advantage in an uncertain market
Resources mentioned: GiveWise (Hannah's project); Offload and the "Nudge" chatbot (Hannah's project); Claude Code; Supabase; GitHub; Vercel; Lovable; ChatGPT; Gemini; Codex; Prof. Leo Bousioux's AI and Generative AI in Business course; Foster's AI club.
