Enterprise AI leadership
I help teams move from AI interest to practical architecture decisions: workflow fit, data trust, cost, risk, governance, and ownership.
Workflow fitCost and riskOwnership
What I do
AI-native product work
I build products to keep the thinking grounded in real users, constraints, payments, support, trust, and product behavior.
ScrollbookMoneyVibeAIMasterz
AI Economics & Architecture
I write about the money layer behind AI: where value is created, where cost hides, and what architecture choices make the system usable.
EconomicsArchitectureField notes
Practical AI training
AISA turns architecture thinking into briefs, decision logs, risk reviews, cost models, templates, and cohort exercises.
AISARubricsTemplates
01Profile
Background, AWS AI leadership, resume, and contact context.
02Product workProducts explained by problem, experience, AI architecture, and operating lesson.
03WritingAI Economics & Architecture, product notes, and practical field thinking.
04LearningAISA, templates, resources, and cohort material.
Quick directory
Not sure where to go? Start here.
Use this as the homepage map. Each link opens one clear area.
Profile
Who I am and what I do
AWS AI leadership, enterprise architecture experience, career scope, resume, and contact context.
Open profile Work Products I am buildingScrollbook, MoneyVibe, TiffinPal, LegacyPal, and AIMasterz explained by customer problem, product experience, AI system design, and operating proof.
See work Writing How I think about AIAI Economics & Architecture: practical notes on business value, product judgment, system design, and the hidden cost layer behind AI.
Read writing Learning Training and templatesAISA, resources, templates, and cohort material for people who want to practice AI architecture with real artifacts.
Open learning
Profile timeline
Career arc with product proof at the end.
The profile should read like a progression: delivery discipline, enterprise systems, cloud architecture, AI leadership, then products that prove the judgment in public.
2006
Foundation
Started in enterprise delivery.
SAP implementation work across manufacturing, pharma, energy, and public-sector programs built the habit of starting with process, data quality, testing, and support reality.
2010
Platform
Moved into large-system architecture.
IBM SAP-on-AWS and enterprise platform programs sharpened the architecture lens: dependency mapping, migration risk, stakeholder alignment, operating model, and cutover discipline.
2017
Cloud
Owned global-account architecture.
At AWS, global account work connected technology choices to executive tradeoffs, commercial urgency, migration strategy, and customer trust at enterprise scale.
2021-now
AI leadership
Built and led AI Solutions Architecture.
Leading AI Solutions Architecture means turning AI demand into field execution, customer programs, architecture judgment, hiring, coaching, and operating cadence.
Now
Product proof
Current builds turn the profile into operating evidence.
These are not resume decorations. Each product forces decisions about users, trust, workflow, economics, support, and what AI should actually own.
Live
Scrollbook
A learning product that turns serious books into visual, listenable, queryable chapters.
Open Beta MoneyVibeA personal finance operating system that converts cash flow, debt, savings, and goals into next-best action.
Open Live TiffinPalA marketplace for South Asian home-chef meals, subscriptions, chef operations, pickup, and delivery.
Open Building LegacyPalA voice companion that checks in with aging loved ones and turns conversations into a searchable family memory layer.
Details