Building production RAG systems that actually work
Retrieval-Augmented Generation sounds straightforward until you face real documents, inconsistent data, and latency requirements that matter.
Insights
Practical thinking about product strategy, applied AI, and the systems beneath an experience that feels simple.

Retrieval-Augmented Generation sounds straightforward until you face real documents, inconsistent data, and latency requirements that matter.
A first release earns its keep by reducing uncertainty. Here is how to choose what stays in the frame.
The delivery work after launch is where interface decisions become either leverage or ongoing drag.
What does an actual multi-agent system look like when it needs to be reliable, observable, and maintainable?
Multi-tenancy, auth, and billing decisions made early define the product's future cost — not just its current state.
The upfront investment in a proper design system returns significant velocity as products grow in complexity.