Field notes.
The gap between a sound design and a working implementation is where some of the most valuable lessons live. This is a place to examine that gap.
Less "success story."
More useful learning.
The focus will be on concrete architectural and organizational problems: what was assumed, what changed during implementation and what the trade-offs taught us.
Questions worth unpacking.
These are working topics, not completed or client-attributed case studies.
When a data platform becomes a permanent reconciliation engine
Where to draw the boundary between upstream ownership and downstream harmonization.
Why the enterprise lakehouse pattern doesn't translate directly to SaaS product data
Different product requirements create different architecture and operating-model choices.
Scaling AI agents without scaling unmanaged risk
Ownership, permissions, monitoring and value measurement in real operating environments.
Case notes will remove sensitive organizational, customer and implementation details unless explicitly cleared for publication.