how much) Data science - insight - models (APIs) Product management - software AI products No direct users Output is number/test Data science teams Smaller teams End-users Front/back end IT Infra Architects Design Large teams
AI product team in < 18 months Fully rolled out two GenAI products < 9 months Manage a mature portfolio of 4 different AI products supporting 13k users Grew team from 5 FTE to 25 FTE on GenAI products Set up a dedicated change management program Reached over 7,500 people in internal talks on GenAI Reviewed over 500 use case submissions Won the Accenture Innovation Award
problems Problems we like: - Mandatory - Frequent - Growing - Costly - Are in the top 3 list of our main stakeholder - End users are really annoyed about
building minimum viable products Write the specs Timebox the specs Cut the specs What do we want to deliver as MVP Only build stuff that contribute to the learning you seek How fast can we deliver this? Which specs can we remove Any shortcuts we can take? Don’t touch it anymore Write the specs t the specs
If you can find someone with a problem that needs solving and you can solve it manually, go ahead and do that for as long as you can, and then gradually automate the bottlenecks. It would be a little frightening to be solving users' problems in a way that wasn't yet automatic, but less frightening than the far more common case of having something automatic that doesn't yet solve anyone's problems.