Work / Advisory

AI/ML, Data Architecture & Advisory

Work with me on AI/ML systems, data platforms and the infrastructure that connects them. I bring architecture and hands-on engineering to agent harnesses, memory systems, streaming data and production ML, starting with your problem and the trade-offs that matter.

◆AI/ML Architecture & Technical Strategy
◆Agent Harnesses & Memory Systems
◆Data Warehouses, Lakehouses & Streaming Architecture
◆ML Infrastructure, Serving & Distributed Training
◆AI-Native Teams, Operations & Governance
Engage Advisory
Becoming AI-Native

Every engineer working as if there were ten.

Most organizations have bought the tools and stopped there. The licences are paid for, a handful of people use them well, and everyone else carries on exactly as before. The work is turning that into throughput — across engineering, and across the far larger group of people who never write code.

01
Where you actually are
Which tools your teams have, which they are using properly, and which they are paying for and ignoring. Usually the gap is not the licence — it is that nobody showed them what good looks like.
02
Engineering throughput
Helping engineers use AI effectively: agentic coding, review and testing loops, and the judgement to know when to trust the output and when not to.
03
Everyone else
The larger win is usually outside engineering — operations, finance, legal, marketing. We identify repeatable tasks where AI can help, agree the checks, and teach people how to use it well.
04
Workshops that stick
Hands-on sessions with real work, not slideware. People leave having done the thing on their own problem, with the habits and the guardrails to keep doing it.

I teach this as Lead Instructor at AI Academy Singapore, and run the same material privately for engineering and venture teams. If you'd rather start small,buy a research task and I'll tell you where your biggest gap is before you commit to anything.