AI
Models, agents, and evals in production. The capability that actually ships.
Getting AI to work was never the hard part.
The hard part is the line from a working model to money in the P&L. It runs through three jobs most companies split across three people, and the margin leaks in the seams. I own all three.
Marketing
Positioning, category, and demand. The story the market repeats and acts on.
Revenue
Pricing, pipeline, and P&L. Where capability and demand become money.
One operator owns all three. Nothing leaks in the seams.
Open the systems. Read the receipts.
Working demos you can open right now. The production builds sit under NDA. These show the thinking, live, so you can judge the operator and not a screenshot.
Live demo
Chief AI Officer
AI Operations Control Center
A governed fleet of AI agents, running and reconciled. Twenty-six workers plus a read-only Investigator, watched from one cockpit.
Proves: I can stand up and govern a production AI operating system, cost reconciled and access controlled. Not slideware.
Open demo control.jeffbrokaw.com
Live demo
Demand & RevOps
The Outbound Machine
Raw signals in, qualified conversations out. Enrichment, scoring, and routing run as one pipeline instead of a stack of disconnected tools.
Proves: I build the demand layer, not just the deck. Signal to reply, instrumented end to end.
Open demo unignorable.jeffbrokaw.com
Live demo
Commercialization
Cold-Start Personalization Engine
First-visit personalization on Shopify Plus, with no prior data on the shopper. The storefront re-ranks itself the moment a stranger lands.
Proves: The engine behind a board-ready GTM is real and shippable, not a projection on a slide.
Open demo personalize.jeffbrokaw.com
Live demo
Applied AI
The Agent-Native Storefront
A storefront you shop inside ChatGPT or Claude. Edit the cart by hand and the model already knows: the view, the conversation, and its context all ride one shared state.
Proves: I ship agent-native products on real MCP, not a chatbot bolted onto a UI. Live context sync that holds across every surface.
Open demo lumen.jeffbrokaw.comWhere capability became revenue.
Shopify AI Personalization
Board-ready GTM for cold-start first-visit personalization. Roadmap ARR ~$2.7M to ~$27M.
Electrical Distribution AI
Usage-based pricing and a training-data moat over ERP-grounded AI workflows.
Advanced Materials Narrative
Narrative behind a $50M Defense Production Act award. $185M new-business revenue.
Battery Storage Challenger
Premium challenger position against Tesla Powerwall. Scaled past $20M.
Crypto Mining GTM
Reframed as energy-backed digital infrastructure. A $114M institutional raise that came together in under 30 days.
Public-Market Comms
Investor narrative that survived management transitions, acquisitions, and the public-market spotlight.
All work →
The receipts
Twenty-five years of getting it to actually pay.
The work above isn't a portfolio. It's a track record that adds up to $850M+ in associated exits, $185M in new-business revenue I helped build, a $114M institutional raise that came together in under 30 days, and an AI fintech I co-founded that went zero to $1M ARR in nine months. Same operator, every line.
Credential
Certified Chief AI Officer (2025), covering enterprise AI strategy, governance, and ethics. Backed by a 2025 stack: HubSpot Revenue Operations, Clay Outbound Automation, n8n AI Agent Builder, Snowflake, 6sense, Shopify Plus Partner, Google AI Essentials, Azure AI-900.
Built
Tabbris, a 23,500 sq ft innovation hub that backed 50+ startups and ran 100+ events. Startup Grind Charlotte, 3,000+ members. FaaStrak, the AI fintech, zero to $1M ARR in nine months. QC Marketing, named the number one web-design firm in North America in 2012.
Recognized
Charlotte Inno on Fire, three times. Charlotte Observer Seven to Watch. Top 25 in Charlotte's startup community.
In the rooms
Guest lecturer at UNC Charlotte's Belk College of Business. Advisory councils at George Washington University and the University of South Florida. Mentor at City Startup Labs, Startup Weekend, and AIM.
Origin
Built a web-hosting business at 14. Ran a broker-dealer's IT and marketing at 16. Wrote The Bitcoin Blueprint in 2013. Self-taught, two exits, still building.
Working stack
Not a tour. The daily kit: ClaudeCursorn8nClay6senseGongSnowflakeRAG + vector searchHubSpotSalesforce
The thinking behind the work.
All writing →FAQ
Questions I get asked.
What does a Chief AI & Marketing Officer do?
A Chief AI and Marketing Officer owns both the AI capability and the go-to-market system that turns it into revenue. Most companies split those jobs across separate leaders, and margin leaks in the seams. Jeff Brokaw runs them as one role: the models and agents that ship, the story the market repeats, and the pricing and pipeline that turn both into P&L.
How does Jeff Brokaw turn AI into revenue?
He starts by finding where the line from a working model to money is leaking, usually in positioning, pricing, or pipeline. Then he builds the system that closes the gap: production AI, a category story buyers repeat, and a demand engine instrumented end to end. The work runs in production, not slideware, and every dollar ties back to pipeline and margin.
What AI systems has Jeff Brokaw built?
He builds production AI, not prototypes. Examples include server-side visitor identification that names the company behind anonymous traffic, answer-engine optimization that gets products cited by the models buyers now query first, and governed AI fleets that run inside an export-controlled environment where controlled data never touches a public model. Several are live and pokeable in his Lab.
What business results has Jeff Brokaw produced?
He built the engine behind $185M in new business for a defense manufacturer, taking inbound web leads from 43 a year to a pace of more than 450. Across early-team operator roles he has $850M or more in associated exits, and he co-founded an AI fintech that went from zero to $1M ARR in nine months. He also authored a $50M Department of Defense grant.
What's stuck?
One conversation. No deck. I'll tell you where the line from AI to revenue is leaking, and what it takes to fix it.