Better living through components
summary
A concrete pattern emerges: build fetch/persist components for data fetching, save/delete buttons and callbacks, and a separate compute components layer for browser ML. The stack includes fog town, mongolab, and a forked tensorflow J s using off-screen canvas to run TC in a web worker. A 178‑row wine set (13 dimensions) clusters correctly and a 260‑image Bob Ross corpus groups visually; default iterations are 1000 and a cache prop avoids recompute. Team size and roles (90 data scientists, 25 Data Platform, 3 front‑end) drive reduced Redux and practical reusable components that work.
AI-written summary · about
chapters (7)
- 0:00Introduction and context
- 4:16Stitch Fix overview
- 7:24Fetch components inspiration
- 12:20Save and delete components
- 16:59Benefits of components
- 18:02Compute components intro
- 23:09Bob Ross demo and conclusion
related talks
24mDesigning Components for Fun, Profit and Sanity
22mComponents are the New Thin Clients
43mHundreds of components, hundreds of experiments and only one page
01h 04mBuilding Design Systems for Scale: From Tokens and Components to Motion & AI Tools
44mIt’s all about components
28mAppetite for Components
38mThe Front End Architecture Revolution
47mAdventures in Rendering Off the Main Thread