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/Index
03

Work

Enterprise credibility without the consultancy fog machine.

The work sits where GenAI strategy becomes actual operating capability: business vision, adoption, governance, product thinking, and employee enablement.

01

GenAI adoption at enterprise scale

Business vision, employee upskilling, governance, internal communication, and the messy human work of turning AI tools into capability.

GenAI Principal at N-SIDE; around 200 employees upskilled.
02

Business vision and AI opportunity framing

Helping teams separate real business value from AI theatre, then shape practical opportunities into experiments worth building.

Strategy that stays close to workflows, products, and operating reality.
03

Agentic workflow design

Practical thinking about agentic systems, human judgment, escalation, and traceability without overstating what should be automated.

Focus on where autonomy removes drag without hiding accountability.
04

Cloud, DevOps, APIs, and data flows

The product wiring behind the AI layer: web apps, Python services, APIs, data ingestion, deployment, and operational reliability.

Builder enough to make the thing real, operator enough to keep it legible.
05

Product thinking and MVP scoping

Translate fuzzy ambition into the first useful artifact: a prototype, internal tool, data product, or launchable wedge.

Prefer fast proof over abstract positioning.
06

Training and enablement

Hands-on sessions for people who need to use AI in their actual work, not admire it from a strategy deck.

Practical workshops, governance framing, and role-specific workflows.

Capability Stack

GenAI adoption programsBusiness vision workshopsEmployee AI literacyGovernance that people can actually usePython services and API designCloud / DevOps deliveryProduct scoping and MVP loops