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The Context Layer — a newsletter on AI memory, context synthesis, and building products that think.

VP of Product.
Context Architect.

I transform how organizations use data, intelligence, and AI to make decisions. The architecture most teams skip — turning raw data into decision-ready context — is the problem I keep solving.

In plain English: I help companies make their AI products smarter by organizing information better.

300%
Growth at $0 CAC
Grandstage
$3.25M
Pipeline pre-product
Helm Labs
$10M+
Revenue impact
IBM
I've shipped products for
IBM
IBM
Global Digital Experience & Growth Platforms
Twitter
Twitter
International SEO Automation Tools
Reddit
Reddit
Digital Customer Support Center
Mozilla
Mozilla
Global Developer Collaboration Platform
PBS
PBS
Washington Week Media Website
Al Jazeera
Al Jazeera
Omnichannel CMS
Sony Music
Sony Music
Collaboration Platform
Johnson & Johnson
Johnson & Johnson
Web Platform for 1,000+ Product Websites
Cigna
Cigna
Social Customer Service Platform
Bank of America
Bank of America
Customer Engagement Platform
Memorial Sloan Kettering
Memorial Sloan Kettering
The Well Editorial Brand Website
USAID
USAID
Crisis Response Platform
Ann Taylor
Ann Taylor
Digital Employee Workspace
Time Inc.
Time Inc.
Product Strategy for Teen People

200+ AI systems, data platforms, web applications and enterprise websites launched in my career.

Data is not context.

The AI industry is obsessed with retrieval — how to get the right chunks into the context window. But retrieval is downstream. If what you're retrieving was never curated, synthesized, consolidated, prioritized, or stored intelligently, your RAG pipeline is just efficiently delivering noise.

Most AI systems skip four of the five steps that turn data into context. That's the gap I build for.

Read the full thesis
The Five-Step Context Generation Pipeline
1
Curate
raw data
Filter signal from noise. Ingest only what matters from the firehose of data.
2
Synthesize
insights
Extract meaning. Classify, summarize, and pull key insights at ingest time.
3
Consolidate
patterns
Find connections across knowledge. The sleep cycle — where patterns emerge.
4
Prioritize
ranked
Rank by relevance, recency, and confidence. Not all context is equal.
5
Store Intelligently
context
Decision-ready context. Indexed, versioned, instantly retrievable.

Product leadership,
end-to-end.

I take AI products from zero to revenue. Strategy through execution, architecture through launch and go-to-market.

hub

Strategy

Customer and market research. Product strategy. Growth strategy. AI architecture decisions that map to business outcomes.

deployed_code

Build

Requirements. Prototyping. Technical architecture. Working directly with engineering and data science to ship products that hold up in production.

trending_up

Scale

Go-to-market execution. Growth experimentation. Analytics and optimization. Building the feedback loops that make products compound.

Execution at scale.

Every role has been a transformation story. Here's what I built, what changed, and what it taught me about context.

Suzy
VP Product

Led the transformation of a consumer survey platform trusted by 350+ enterprise brands into a Decision Engine — synthesizing fragmented marketing intelligence into decisions organizations can act on. Built and shipped in six weeks.

6 wks
concept → launch
Grandstage
Co-Founder & Head of Product

Built an answer engine fusing 10,000+ sources into synthesized market intelligence. Designed the hybrid search architecture and hierarchical relevance model that lifted user retention from 50% to 80%.

300%
user growth · $0 CAC
Helm Labs
SVP & General Manager

Defined product vision for a unified enterprise data platform integrating five acquired products and proprietary datasets covering 200M+ Americans. Built the GTM motion from scratch.

$3.25M
pipeline pre-launch
IBM
Digital Product & Growth

Transformed how IBM’s Cloud and AI business acquired, converted, and retained ~1M users globally. Deployed growth stack across 30+ countries with 100% adoption.

31%
trial conversion lift

Working with Riché

A product mind grounded in the bottom line.

I lead product end-to-end — and I can sell it, too. My strategies are anchored in generating revenue or saving millions.

01

A career built on transformation.

Every major role has been a transformation story — taking an organization, a team, or a product and fundamentally changing how it operates. I don’t maintain products. I transform businesses through them.

02

An original thesis backed by real builds.

A specific, defensible point of view on turning raw data into decision-ready context — grounded in cognitive science and information theory, validated by every product I’ve shipped.

03

The full stack: strategy to revenue.

Strategy, architecture, build, go-to-market, and growth — in one person. I’ve raised venture capital, sold enterprise deals, deployed growth infrastructure globally, and written production AI applications.

Ready to architect the next context?

I'm open to advisory engagements, board positions, speaking opportunities, and connecting with people building at the intersection of AI and product.

Get in touch