Hi, I'mKarl Nguyen

Technical Product Manager – Container Shipping & Logistics Systems

Specialized in Booking, Shipping Documentation (SI/BL), and Shipment Visibility — delivering measurable impact across global logistics platforms, with hands-on execution from concept to product.

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My Domain Expertise

I can talk both languages — carrier rules and shipping docs, or services, APIs, and data models

Container Shipping

  • •Container Booking Systems
  • •Shipping Documentation (SI, BL, VGM)
  • •Shipment Tracking & Visibility
  • •eCommerce Platforms for Carriers

Applied Product Domains

  • •Logistics Documentation & Compliance Systems
  • •Inventory & Operations Management
  • •eCommerce Profitability & Cost Tracking
  • •Workflow Automation for SMEs

Currently at VX Solutions

Helping smaller businesses in Vietnam digitize exports, inventory, and cross-border flows. Building tools that enable local offices, forwarders, and small shippers to get answers without email chaos.

What I Work On

I sit in the middle of product strategy, technical implementation, and AI-augmented workflows

Product Strategy & Execution

Define product direction from problem framing to delivery, balancing immediate outcomes with long-term platform scalability.

  • Frame problems clearly before jumping to solutions
  • Balance short-term delivery with long-term platform health
  • Obsess over end-to-end journeys: booking → documentation → execution

Technical Product Management

Design workflows across booking, documentation, and tracking. Define system logic, validation rules, and data structures to support real-world operations.

  • Think in architecture, APIs, data flows, and trade-offs
  • Define validation rules and system logic grounded in domain knowledge
  • Bridge the gap between business needs and technical reality

AI-Augmented Product Thinking

Apply structured data and rule-based systems as a foundation for practical AI use cases — including compliance guidance, document validation, and workflow automation.

  • Build rule catalogs and structured data as AI foundations
  • Apply AI to compliance checks, document validation, and query answering
  • Use AI daily for research, prototyping, and validation

Enterprise Product Work

High-level descriptions from work on a global ocean carrier eCommerce platform

Enterprise (Anonymized)

Express Booking Flow (Container Shipments)

Problem

Traditional booking flows are complex and require excessive upfront input, creating friction and drop-offs.

Solution

Designed a simplified, guided booking experience with reduced input complexity and improved workflow structure.

Impact
  • Increased booking completion rate by ~15–20%
  • Reduced user friction and time-to-book
  • Improved usability across user segments
Enterprise (Anonymized)

End-to-End Shipment Overview Dashboard

Problem

Shipment data was fragmented across booking, documentation, and tracking systems, forcing users to navigate multiple interfaces.

Solution

Built a centralized dashboard consolidating shipment status, milestones, and document visibility into a single interface.

Impact
  • Increased feature adoption by ~20–30%
  • Reduced reliance on manual tracking (emails / support) by ~25–35%
  • Enabled real-time shipment visibility and self-service

Product Work at VX Solutions

Execution-focused product work validating real logistics problems through hands-on building and iteration.

Document Management System (Shipping)

Problem

Critical shipment documents are scattered across emails, PDFs, and shared folders.

Solution

Built a centralized document system with structured metadata, search, and access control.

Impact
  • Reduced document retrieval time from hours → seconds
  • Improved visibility and collaboration across teams
  • Reduced risk of missed renewals and compliance gaps

Smart Compliance Hub

Problem

Compliance requirements are fragmented across shipment lifecycle and difficult to track.

Solution

Designed a rule-driven system mapping compliance requirements, document templates, and workflows.

Impact
  • Reduced errors from missing compliance steps
  • Made regulatory requirements structured and searchable
  • Enabled foundation for AI-assisted compliance guidance

Smart Profit & Expense Tracker

Problem

eCommerce sellers lack visibility into true profitability after operational costs.

Solution

Built a system for tracking costs, margins, and financial performance.

Impact
  • Enabled accurate profit tracking beyond revenue
  • Reduced reliance on spreadsheets
  • Improved decision-making for non-technical users

Smart Inventory Management

Problem

Inventory is fragmented across channels, leading to overselling and stock issues.

Solution

Built a unified inventory system with alerts, tracking, and replenishment logic.

Impact
  • Reduced overselling and stock emergencies
  • Improved inventory planning
  • Provided real-time operational visibility

How I Work

A consistent flow from idea → shipped feature → monitored outcome, with AI assisting at every step

1

Ideas & Problem Shaping

Collect inputs from customers, ops teams, data, and market signals. Use AI to summarize feedback, cluster themes, and draft problem statements.

Clearly framed problems, not raw feature requests
2

Pick Ideas & Define the Bet

Assess ideas against impact, effort, risk, and strategic fit. Use AI to simulate scenarios, propose alternatives, and challenge assumptions.

1-3 bets worth deeper discovery
3

PRD / Concept Brief

Draft a concise PRD: problem, users, scope, constraints, success metrics. Use AI as a co-writer for structure and edge cases.

Shared concept document the team can argue with
4

User Story Map & Journeys

Map the end-to-end flow (booking → documentation → tracking → support). Use AI to suggest missing steps and failure paths.

Story map or service blueprint for slicing work
5

Backlog & Story List

Break flows into stories, constraints, and technical tasks. Use AI to draft initial user stories and acceptance criteria.

Structured backlog linked to the story map
6

Story Details & Edge Cases

Clarify details with engineers, designers, and domain experts. Use AI to generate edge-case lists and validation rules.

Story-level specs for dev + QA
7

UAT & Pre-release Validation

Define UAT scenarios and success criteria with stakeholders. Use AI to expand test scenarios and spot patterns in feedback.

UAT reports and go/no-go decisions
8

Release & Metrics Monitoring

Coordinate releases with engineering, ops, and support. Use AI to summarize dashboards and highlight anomalies.

Clear view of whether the bet is working

"AI doesn't replace discovery or decisions — it compresses the busywork so I can spend more time on framing, trade-offs, and alignment."

View PM Automation Workflows & Templates

Tools & Comfort Zone

Where I feel most comfortable operating

Product & Delivery

Value creationProduct discoveryBacklog managementRoadmappingDiscovery frameworksStakeholder alignment

Design Collaboration

WireframesJourney mapsService blueprintsUX collaborationDomain expertise integration

Technical

API design discussionsData modelingPrototype buildingProduction data analysisEngineering collaboration

I build my own prototypes (scripts, demo apps) and query production-like data to uncover insights. Enough hands-on to collaborate effectively with engineers without doing full implementation work.