In the early days of any product cycle—for everything from a small tweak in an established app to a shiny, new product—uncertainty often runs rampant. Doubts about product reach, impact, and engineering effort get amplified when working with new technologies like machine learning (ML). However, there’s good news: exploratory prototyping can help. By building quick, real-feeling (and often wholly simulated) versions of products and features, teams can be nimble, explore various directions, fail early, and pivot repeatedly—all before going too far through the entire costly, messy ML development process.
Guide