Build products from zero
Digital products, app surfaces, local workflows, and owner-level product choices.
Hi Brian
Product / operator
buildingproducts from scratch. high-performing teams. AI-assisted workflows.
That is the through-line across 15+ years in entertainment, acquisition systems, driver app products, global operations, and AI workflow design.
Company builderTeam builderMarketplace operatorAI workflow designer
From Scratch To Scale
Three chapters. One builder pattern.
I have built across entertainment, acquisition systems, driver products, global operations, and now AI-assisted workflows. The pattern is consistent: find the real signal, make a product choice, build the team ritual, then use AI to compress the next cycle.
Moosin
Offline business to digital entertainment.
Head of Product for the shift into digital media, social distribution, and a new operating model.
digital mediasocial distributionnew operating model
Uber SEA
Regional launch systems in Southeast Asia.
Built online acquisition, verification, paid acquisition, and all-channel driver growth during hypergrowth.
online acquisitionverificationpaid + all-channel growth
Uber Global
Product/operator systems at global scale.
Built high-performing teams and AI-assisted workflows around products serving 10M+ earners globally.
10M+ earnersteam ritualsAI-assisted workflows
Scale acquisition systems
Online acquisition, verification, paid channels, referral loops, and regional operations.
Own marketplace surfaces
Driver and earner journeys across earnings, trust, loyalty, reliability, and transparency.
Build operating systems
Launch readiness, decision cadences, feedback loops, and global-to-local product narratives.
Build high-performing teams
Hiring bars, coaching, calibration, product judgment, and team rituals that raise the floor.
Build AI-assisted workflows
Knowledge systems, agentic workflows, source-backed briefs, and human-in-the-loop review.
System Design
The work is operating system design for product teams.
A product organization gets faster when market truth, team rituals, and AI workflows are designed as one system. That is the thread underneath the CV.
Interactive Strategy Console
Turn noisy marketplace signals into product choices.
customer + market signals
leadership-ready tradeoffs
one recommendation
Workflow sketch
if signal.isNoisy():
triangulate(field, data, support)
ship(decision_memo)Highlighted Work
AI-Assisted Product Operating System
A public-safe view of how I am testing the next product operating model: training teams, building reusable workflows, and using agents plus knowledge systems to compress context before decisions.
product-ai-os
PrivateTeam enablement + knowledge workflows + agentic operating model
team-ai-enablement
PrivateWeekly study group, hands-on setup, prompt practice, and culture change
agentic-workflows
On requestReusable agents for synthesis, brief drafting, and decision support
knowledge-ops
PrivateObsidian-backed product truth, meeting memory, and source-backed retrieval
applied-ai-ops
PrivateAI applications for my own work and company-scale product/operator workflows
prompt-library
On requestReusable templates for research, reviews, market scans, and exec prep
governance-model
PrivateShared context, access patterns, and human review for sensitive work
Experience
Built from field operations into global marketplace leadership.
Uber
San Francisco Bay AreaGroup Product Operations
2024-Present
Leads Group Product Operations for global earner product surfaces, bringing product ownership, marketplace operations, team design, and AI-assisted workflow building into one operating model.
- Builds and scales a high-performing product/operator bench across multiple product pillars and geographies.
- Turns field signals, product constraints, regional nuance, and marketplace tradeoffs into clearer product decisions.
- Leads practical AI adoption through team demos, agentic workflows, knowledge systems, and hands-on upskilling rituals.
Uber
San Francisco Bay AreaProduct Operations, Global Earners and Grocery Delivery
2019-2024
Brought product management and operations judgment into global marketplace workstreams across driver, courier, and grocery delivery products.
- Helped scale important earner-facing products across a global marketplace serving 10M+ earners.
- Helped launch and scale grocery delivery in top markets through experimentation and defect analytics.
- Translated earner insights into product requirements across loyalty, reliability, transparency, and marketplace design.
Grab
SingaporeLead Product Manager, Driver App
2018-2019
Owned driver app product surfaces across earnings, job cards, receipts, performance management, and in-trip experience across Southeast Asia.
- Led redesign work across critical driver app surfaces including job card, earnings history, receipt, and in-transit flows.
- Partnered with design, engineering, analytics, and operations to improve high-frequency driver workflows.
- Built product instincts across transportation, food, payments, and Southeast Asia super-app contexts.
Uber
SingaporeSenior Regional Operations Manager, APAC
2015-2018
Built online acquisition, verification, and all-channel driver acquisition systems during Uber's hypergrowth phase across Southeast and North Asia.
- Built online acquisition paths from web pages to paid acquisition and paid ads.
- Helped set up online acquisition verification flows in early Southeast Asia markets.
- Led all-channel acquisition operations across online, referral, and offline channels with regional targets and budgets.
- Worked with local operations, marketing, and San Francisco product and engineering teams on regional experiments and rollouts.
- Built regional products such as loyalty web apps and vehicle marketplace workflows for local business needs.
Moosin
South KoreaHead of Product
2012-2015
Helped transform an offline sports, media, and hospitality business into a digital entertainment, commerce, and membership platform.
- Launched digital products including online sports store, publishing surfaces, and paid content experiences.
- Implemented CRM-backed membership workflows with Salesforce partnership support in South Korea.
- Owned web design, administration, programming, and digital promotion foundations for the business.
Portfolio
What I build repeatedly.
Filter
AI
PrivateAI-Enabled Product Ops Adoption
A hands-on AI adoption system for Product Ops teams: source-backed briefs, reusable knowledge, workflow demos, and human-in-the-loop decision support.
AI adoptionteam learningknowledge systems
Weekly AI study group materials, Claude Code adoption threads, Knowledge Base LLM workshop notes, AI transformation baseline, and Product Ops AI vision notes.
Open case studyTeam Building
PrivateHigh-Performing Product Ops Team
A Product Ops team model built around pillar ownership, market truth, leadership cadence, coaching, and repeatable judgment.
team designcoachingoperating cadence
Product Ops charter notes, team operating model docs, leadership review rituals, coaching notes, team structure, calibration patterns, and AI capability investment.
Open case studyProduct Leadership
PrivateMarketplace Product Operating Model
A leadership cadence that turns market signals, earner pain, data, regional nuance, and product constraints into clear product choices.
product strategymarketplacegovernance
Business reviews, launch governance, stakeholder maps, metrics cadences, marketplace health frameworks, and decision-ready product narratives.
Open case studyMarketplace
PrivateMarketplace Sentiment System
A system for converting qualitative feedback, competitive benchmarking, survey signals, and marketplace performance into product strategy.
sentimentresearchtrust
Driver and courier sentiment notes, EMEA roundtables, competitive analysis, DSAT/BHT context, app reviews, support signals, and market-level operating readouts.
Open case studyMarketplace
PrivateMarketplace Transparency and Trust
Product operations around how marketplace participants understand earnings, incentives, reliability, fairness, and product trust.
earningstrusttransparency
ECR and earnings transparency notes, tipping and receipts work, gas/refueling context, support comprehension, and trust-related product narratives.
Open case studyMarketplace
PrivateLoyalty, Progression, and Quality Programs
Operating support for programs that reward high-quality marketplace behavior while preserving clarity, fairness, and regional adaptability.
loyaltyqualityprogression
Uber Pro, Eats Pro, progression, quality supply, scheduling, rewards, and engagement planning notes across mobility and delivery.
Open case studyProduct Leadership
On requestMoosin Digital Transformation
A from-scratch chapter moving an offline entertainment business toward digital surfaces, content distribution, audience memory, and growth loops.
from scratchdigital mediacommerce
Older CVs and employment materials cite Head of Product work, online products, sports store, publishing surfaces, paid content, CRM, and digital promotion.
Open case studyProduct Leadership
On requestUber SEA Acquisition Systems
A hypergrowth chapter building regional acquisition, activation, verification, vehicle-access, referral, and local-market experimentation systems across Southeast and North Asia.
growthacquisitionlaunch systems
Older CVs cite Growth Marketing Manager and Senior Regional Operations roles, online acquisition paths, regional targets, budgets, vehicle marketplace, and loyalty web apps.
Open case studyProduct Leadership
On requestGrab Driver App Product
A product-learning bridge across high-frequency driver app surfaces: earnings clarity, job cards, receipts, performance, loyalty, and local marketplace fit.
driver appproduct managementSoutheast Asia
Older CVs cite Lead Product Manager and Senior Product Manager work on driver earning and in-transit flows, job cards, receipts, earnings hub, and performance management.
Open case studyBuilder Lab
On requestPersonal OS and OpenClaw
A local-first AI operating layer for memory, routing, generated context, agent activity, and human-reviewed decisions.
personal AIObsidianagents
Obsidian vault, OpenClaw agents, generated context files, obsidian-os tooling, and os.brianlevu.com read-mostly dashboard.
Open case studyBuilder Lab
On requestTradeDeck
An AI-assisted prediction-market decision system built around evidence quality, source freshness, calibration, and safety gates.
AI productmarket intelligencecalibration
TradeDeck dashboard, source registry, macro and market-intelligence pipeline, structured decision memos, calibration loops, and explicit no-auto-trading rules.
Open case studyBuilder Lab
PrivateRental and Real Estate Operating Tools
A private operating lab for property decisions, booking operations, taxes, maintenance, and AI-assisted evidence trails across a real small-business context.
small businessreal estateoperations
Rentals map, property operations notes, STR workflow notes, finance agent context, LandlordHours, and related Personal OS workflows.
Open case studyBuilder Lab
On requestCamping Tracker
A small personal utility that monitors Bay Area campsite availability and routes useful alerts without auto-booking.
automationfamily utilityalerts
Node/Express service, Recreation.gov and ReserveCalifornia scanning, config-based preferences, health checks, and human-reviewed alert handoff.
Open case studyOperating Principles
How I tend to run the work.
Ground truth first: start with customers, markets, and field reality before polishing the narrative.
One clear recommendation is more useful than five options with no owner.
The best product/operator teams raise the quality and speed of product decisions.
AI adoption is a team operating model problem before it is a tooling problem.
The operator still owns judgment. Agents earn trust by making the source trail clearer.
Product Leadership
Product ownershipProduct operating modelsGroup-level prioritizationExecutive product reviewsDecision qualityCross-functional ownership
Marketplace Product Strategy
Marketplace healthCustomer trustOnline acquisitionSentiment systemsCompetitive benchmarkingIncentive and loyalty systems
Product Ops Craft
Global launch readinessExecutive reviewsProgram governanceCross-functional escalationOperating cadence design
Team Leadership
Cross-geo team managementAI upskillingHiring systemsPromotion narrativesStakeholder mappingAsync-first communication
AI-Enabled Systems
Knowledge basesAgent workflowsWorkflow automationPrompted researchDecision-support toolsHuman-in-the-loop review
FAQ
The short version for collaborators.
Where does Brian add the most leverage?
In product organizations where marketplace complexity, customer reality, product ownership, team performance, AI workflow adoption, and leadership decision quality need to connect.
What is the through-line in Brian's experience?
The through-line is building from scratch: digitizing an offline business at Moosin, scaling marketplace acquisition across Asia at Uber, owning driver-app product surfaces at Grab, building high-performing global product/operator teams, and now applying AI to knowledge and workflow systems.
What makes this profile relevant in the AI era?
Brian is not positioning as an AI engineer or as Product Ops only. He is a product/operator builder testing how AI changes the way teams learn, decide, and operate: adoption, agents, workflow automation, knowledge systems, and human-in-the-loop judgment.
Why keep this public-safe instead of using all internal details?
A public portfolio should communicate scope, judgment, and craft without publishing confidential company details. This site intentionally avoids sensitive metrics, private stakeholder context, and internal-only program specifics.