PITA 067
Working with a consortium of accountants, working with them on AI adoption. Where do we start? There’s no product - it’s a greenfield.
Start with 3 things:
AI policy
Market posture, positioning, identity, future-casting
Map & territory
Pain points
What people say they are doing
What they’re actually doing
Conclude with some complexity thinking: When AI is relevant and when it’s not
Look for low-hanging fruit and automation (CPO Circles preview)
Start with experiments and a Slack channel - people playing and sharing what they’ve done and any success or learnings
Small Centre of Excellence - champions who could answer policy and adoption questions
They have strong opinions - but zero tech discipline. Need to look for how this fits against their market positioning and business strategy.
Identify pain points and see if AI approaches can help resolve or accelerate development in these areas.
Create a Wiki-based LLM.
Strategic level: Positioning, future-casting, innovator or fast follower?
Operational level: Experiments and efficiencies
AI-pril - selected tools made available to employees, some training implemented, time to experiment, and then we got together to discuss what we tried, what we changed, and how we could use this better
I'm working with a client that has a complicated approach to roadmaps - they do both hardware & software, and are dependent on 3rd party schedules for both vendors and sales channels. Does anyone have an example that they can share or point to of what good could look like in this space? (I have some ideas and a way forward, but examples are always helpful!)
Decision matrix vs roadmap - certain decisions need to be made by specific dates
Pockets of autonomy that lead up to those fixed decisions
There’s a lot of experience with this in automotive and similar areas, but public examples of documentation are limited
Clarity of risks and the implications of decisions
Competitive merging to core dev cycle - what MUST we have, what is OPTIONAL to have