Senior product owner · Charlotte, NC

Clarity for complex
digital products.

I turn complicated product behavior into decisions teams can build, test, and improve. My work spans commercial banking, money movement, digital experience, and practical AI for product teams.

Commercial bankingMoney movementProduct specificationsAI-enabled workflowsAccessibility

Selected work

Work that makes delivery clearer.

These are public-safe descriptions of my methods and contributions. Internal banking artifacts and client information are intentionally omitted.

02 / Delivery definitionCommercial transfers

Turning feature scope into testable stories

I analyzed transfer capabilities across creation, review, approval, lifecycle changes, and exception paths, then translated the findings into stories with behavior based Given, When, Then acceptance criteria. The coverage framework separates behavior discovery from story formatting so teams can find gaps before writing.

Representative output

Behavior map, scenario coverage, story decomposition, acceptance criteria, and unresolved decisions.

Read a mock transfer user story
User storiesAcceptance criteriaEdge cases
03 / Product improvementFeature readiness

Making features ready for story refinement

I assessed whether feature scope, UI design, interaction rules, and system behavior were clear enough for the next story stage: PI planning placeholders, interim refined stories, or final sprint-ready stories. Gaps became explicit decisions or discovery work before Scrum refinement.

Representative output

A staged feature readiness assessment showing available evidence, unresolved rules, decision owners, and the next story handoff.

View the recreated framework
Feature readinessStory fidelityRefinement
04 / AI toolingReusable practice

Grounding AI in product knowledge

I designed an AI-enabled authoring approach that uses established rules and decision history as source material for specifications, stories, training, and review. I also developed an evidence-grounded learning framework that checks source fitness, contradictions, and uncertainty before turning information into action.

Design principle

Keep claims traceable, surface unknowns, and let people review decisions before they become delivery instructions.

See a simplified evidence model
Knowledge systemsAI-assisted authoringEvidence quality

Process & product improvements

Truist improvements I designed

Selected, recreated examples of how I made complex product work easier to understand and deliver. The artifacts use fictional scenarios and generic payment language.

01 / Future-state concept

Intelligent Treasury Orchestration Platform

Problem
Transaction-first tools can force people to navigate disconnected steps before they understand risk or next actions.
What I designed
An intent-led journey with guided setup, early feedback, safer corrections, and a visible decision trail.
Artifact
A recreated experience map and example correction path.
Why it matters
It makes a complex treasury task more understandable while preserving control and accountability.
Explore the concept
02 / Delivery practice

Feature Readiness Framework

Problem
Missing feature detail turns Scrum refinement into feature discovery.
What I designed
Readiness criteria for placeholder, interim refined, and final stories, grounded in UI design, interaction rules, and system behavior.
Artifact
A recreated evidence matrix tied to each story handoff.
Why it matters
Teams receive stories with enough detail for PI planning, focused refinement, or sprint development.
View the framework
03 / Requirements quality

Invariant Rules Framework for Transfer Systems

Problem
Well-written stories can still conflict when foundational rules are implicit or disputed.
What I designed
A way to separate always-true constraints from scenario behavior and flag gaps before development.
Artifact
A recreated rule register and readiness check using fictional examples.
Why it matters
Shared rules reduce contradictory assumptions across flows and teams.
Inspect the model

How I work

Make the implicit
explicit.

When a feature crosses interfaces, services, teams, and policies, the work starts by finding the behavior that has never been written down.

01

Understand the client and business goal

Clarify who needs the capability, what success means, and where the current journey breaks down.

02

Document the full behavior

Connect visible interactions to system rules, permissions, states, data, exceptions, and downstream dependencies.

03

Prepare the team to build

Break scope into reviewable stories, identify open decisions, and align product, design, engineering, and QA.

04

Check the delivered experience

Use demos, acceptance criteria, and production validation to compare what was built with the intended behavior.

Experience

Product depth, delivery range.

My background combines hands-on product ownership with UX, front-end leadership, backend and API work, and cross-functional delivery.

2025–2026

Truist Senior Product Owner, contract

Commercial digital banking: transfers and payments, information reporting, SFTP, behavioral specifications, AI enablement, and product knowledge practices.

2024–2025 · 2020–2022

Wells Fargo Senior Product Owner / Digital Product Owner, contract

Merchant Services and wholesale digital products: roadmaps, backlogs, delivery governance, release coordination, and production validation.

2022–2024

Charter Communications Digital Product Manager / Product Owner, contract

Customer-facing digital initiatives across web and mobile, with product, design, API, data, engineering, and QA partners.

Earlier

Ally Bank · Eastonsweb · Bank of America Leadership and consulting

Front-end and UX leadership, digital product consulting, and banking product management. At Ally, workflow improvements were associated with 90% on-time handoff, 20% fewer project defects, and 80% fewer production defects, as recorded in my résumé.

Let’s connect

Building a complex product? Let’s make the work clearer.

I’m interested in senior product owner roles where careful product definition, strong delivery partnership, and responsible AI practices can make a real difference.

Email John