AI Solution Navigator

Work from a business problem to a solution class — rules, classical ML, deep learning, generative models, agents, or operations research — before anyone commits to a stack.

It covers rule-based systems, classical machine learning, deep learning, generative models, agents and operations research, plus the hybrids between them. It is written for architects and PMs framing a problem before a stack gets chosen for them.

Every branch states the trade-off that decided it, so the recommendation you end on comes with the reasoning attached — something you can paste into a design note or defend in a review.