Sajiv Francis

Background

Eight years of building at the intersection of AI and enterprise systems: from a 2018 grad-school location tool for Connecticut seniors, to an NLP-powered adaptive learning system in 2019 (predating mainstream RAG by four years), to enterprise data orchestration, to leading architecture today for a multi-instance S/4HANA finance transformation and four enterprise AI programs inside one of the world's largest technology companies.

Why this work

I came into enterprise architecture sideways, through digital transformation projects in SAP and software engineering, then through trying to make AI useful inside organizations. What I care about now is the seam where new model capabilities meet decades-old enterprise systems, and how architects translate one to the other without breaking either.

Life outside work

Married, two kids. Most weekends are theirs.

When time allows: I ride a Harley, collect stamps (a habit my grandfather used to do, decades ago, that I've never quite outgrown) and I also pretend to follow Formula 1 and MotoGP as closely as I once did.

And there's almost always instrumental jazz on while I work. Here's the rotation, if you'd like it playing too:

Education & communities

Writing

I write about the future of architecture practice at the intersection of AI and organizational design, for practitioners rather than academics. Recent pieces are on the writing page.

How this site is written

The ideas and opinions here are mine. The drafting is AI-assisted, and I see no reason to hide that: every post runs through a grounded review pipeline I built myself, which checks my claims against my own code and notes before anything publishes. This site argues that leaders should work with these tools openly and with judgment, so it would be strange to produce it any other way. Where AI helped, it helped with the sentences. The thinking, and the mistakes, are mine.