AI product strategy / Growth & lifecycle

I turn AI
capability into
customer habit.

Senior Product ManagerThomson Reuters · CoCounsel

I own engagement and retention for CoCounsel, helping tax and audit professionals make AI a repeatable part of how they work.

Building products since 2019 New York City

The adoption loop
  1. 01Activate
  2. 02Engage
  3. 03Retain
  4. 04Expand
First value. Lasting adoption.Product craft & experimentation
Built across
complex industries
Thomson ReutersAuraEarnestBusiness InsiderGannett
01 / Current workThomson Reuters · CoCounsel

The product work behind
lasting AI adoption.

An AI answer needs to move real work forward. I focus on the product decisions that help customers find value, deepen their workflows, and keep using CoCounsel across their firm.

My ownership
Product strategy & execution
My focus
Engagement & retention
The customer
Tax & audit professionals

Selected CoCounsel work.

Shipped experiences and current areas of focus. Diagrams illustrate the product concepts.

02 / Workflow discoveryShipped

Agent-driven chat recommendations

Shipped chat recommendations that use the current task to suggest another relevant conversation.

Context from the current task
Recommended next workflow
Start a connected conversation
Relevant context. A useful next step.
From context to a new workflow
03 / ActivationShipped

Onboarding around the task

Shipped onboarding built around the work a customer needs to do and the first outcome they want to reach.

  1. Identify the goal
  2. Find a relevant workflow
  3. Reach a useful outcome
From first session to first value
04 / Return usageFocus area

Notifications that support return usage

Connect notifications and lifecycle touchpoints to relevant work, giving customers a useful reason to return.

Relevant customer context
A timely notificationA reason to pick up the work
Return with intent
From relevant prompt to return
05 / Firm adoptionFocus area

Admin insights for firm adoption

Develop admin metrics dashboards that help firms understand adoption and identify opportunities to improve seat utilization.

AccessWho can use the product?
ActivityWhere is value showing up?
ActionWhere can adoption improve?
From access to active use

One connected customer journey.

Explore each stage
01 / Activation

Get to the first useful outcome.

I shape onboarding around the customer’s task, so the first session leads toward an outcome they can use.

OnboardingFirst valueEntry points
What I look forA useful first outcome

Where does a new user lose momentum before seeing value?

02 / Selected impactResults from previous roles

Different products.
Measurable progress.

A track record across digital security, financial services, and subscription media—connecting customer insight to product decisions and business results.

AuraDigital security
+40%

Average order value

Launched introductory checkout pricing that increased order value without sacrificing conversion or retention.

Pricing & monetization
EarnestConsumer finance
20%+

Increase in user retention

Introduced gamification to Going Merry, making the scholarship search more engaging and improving retention.

Engagement & retention
Business InsiderSubscription media
+20%

Subscription revenue

Used customer research and pricing experiments to improve subscription economics. Also increased checkout completions by 30%.

Conversion & experimentation
GannettDigital publishing
−35%

Subscriber churn

A/B tested 17 product enhancements that reduced churn and increased subscriptions by 45%.

Subscription growth
03 / How I workCustomer insight & product judgment

An experimenter’s discipline.
An AI-native practice.

I use AI agents to investigate funnels, explore segments, and sharpen hypotheses. A/B tests and customer feedback help me decide what to ship, refine, or stop.

The learning loop
Customer feedbackFunnel evidence
Agent-assisted analysisA testable hypothesis
A / ControlCurrent
experience
B / VariantProposed
change
Outcomes + guardrailsScale · Refine · Stop
Carry the learning into the next decision
01

Start with the customer’s work.

Understand the task and where progress breaks down. Define the customer outcome before choosing a feature or setting up an experiment.

02

Turn evidence into a sharper hypothesis.

Work with agents to explore drop-offs and patterns, then use product judgment to choose the opportunity and design the test.

03

Measure the whole relationship.

Read conversion alongside repeat usage and retention. A result matters when it supports a better customer experience over time.

The lenses I use
Time to valueFeature adoptionRepeat usageSeat utilization
04 / BackgroundEngineering roots. Product focus.

I like complex systems.
And making them useful.

My engineering background shapes how I approach product work: understand the system, find the constraint, and make decisions with evidence.

I’m comfortable with ambiguous problems and the work of turning them into clear priorities, a shipped product, and the next thing to learn.

Selected experience

  1. Current

    Thomson Reuters

    Senior Product Manager · CoCounsel

    AI engagement, retention & adoption

  2. 2024–2025

    Aura

    Senior Product Manager, Growth

    Conversion, pricing & retention

  3. 2023–2024

    Earnest

    Product Manager, Growth

    Engagement & lifecycle experiences

  4. 2021–2023

    Business Insider

    Product Manager, Growth

    Subscription growth & monetization

  5. 2019–2021

    Gannett

    Associate Product Manager, Growth

    Acquisition, conversion & retention

Full background on LinkedIn (opens in a new tab)
An engineering
foundation
Johns Hopkins UniversityB.S., Mechanical Engineering
Carnegie Mellon UniversityM.S., Mechanical Engineering
M.S., Engineering & Technology Innovation Management

Say hello

Let’s talk about
what you’re building.

I’m always interested in exchanging ideas about AI products, experimentation, and the work of building something useful.