KD / LAB
Ideas are cheap.
Make them tangible.
A working collection of AI, automation, systems, analytics, and product concepts. Less résumé. More evidence of how I think.
Three problems I like
pulling apart.
These are conceptual explorations, not client case studies. Each one shows the decisions, guardrails, and system thinking behind the work.
01 / AUTOMATION
The human-reviewed AI inbox
What if repetitive inbound work could be classified, drafted, and routed automatically without surrendering the final decision?
02 / SIGNAL
One decision, fewer dashboards
Instead of starting with charts, start with the decision. Then trace backward to the definitions, sources, and owners required to trust it.
03 / PRODUCT
From feature pile to release
Turn an overflowing wish list into a sequence of user problems, tradeoffs, dependencies, and measurable releases.
HOW I THINK
Useful beats impressive.
The interesting part is not adding technology. It is deciding where complexity belongs, where humans stay in control, and what information actually changes a decision.
01
Find the actual constraint
Separate the visible annoyance from the process, information, or decision causing it.
02
Design the smallest useful move
Prefer a focused experiment with clear boundaries over a transformation program nobody can explain.
03
Leave a clearer system behind
The outcome should make the next decision easier, not create another dependency on a consultant.
Have something messy?
Good. Those are usually the interesting problems.
dowhatkennydoes.com 