Ventures
I build what I teach.
I'm not a consultant who has never shipped. The behavioral science and experimentation discipline I bring to Fortune 500 growth teams is the same playbook I use to build and grow my own products.
Building Now
An AI-powered recruitment platform that tailors résumés to each job and automates the application workflow.
35K+ users at $0 current paid user-acquisition spend in July 2026, after earlier paid tests stopped. Visit ↗An experimentation and CRO analytics platform that turns raw A/B test data into behavioral-science insight growth teams can act on.
Built for teams running 30+ experiments a year — self-taught the data pipeline and analytics architecture from scratch to turn scattered test results into searchable institutional knowledge. Visit ↗A fully automated content system built for my own use first — testing whether my voice, writing, and video can turn into genuinely distribution-ready content across social platforms and blogs, instead of productizing it as a SaaS from day one.
In active development — self-taught the automation and LLM-orchestration pipeline solo, and I'm validating it end-to-end on my own content before deciding whether to productionize it further.A newsletter on experimentation, behavioral economics, and evidence-based growth — the thinking behind the products.
Published weekly on Substack. Visit ↗Built & Closed
Not everything I've built is still running. Here's what I shut down — the thesis it started from, what actually happened, and the lesson it left behind. The ones I killed taught me as much as the ones that worked.
My first real company — a test of whether the marketing and economics I was studying actually held up in the real world.
A full e-commerce lifecycle — sourcing, selling, and a 25-person team — wound down when I graduated. Read the teardown →An AI agent that finds the right Reddit conversations and helps you reply with something genuinely useful — turning the best free traffic source into a repeatable channel.
Validated demand and paying customers — then discontinued on principle when it became a cat-and-mouse fight with Reddit's anti-automation. Read the teardown →A privacy-first AI companion built around the real technical problem — keeping an AI's memory of you from drifting or being erased as the models underneath it change.
Built a working prototype and ran deep user research — then chose to sunset it rather than build in a space I couldn't stand behind. Read the teardown →A fast way to make pixel-perfect App Store screenshots — build it in a day, prove distribution in ninety.
A few hundred users and real sales, entirely from Reddit and AI directories — closed as we each moved toward the different halves of the business we most wanted to run. Read the teardown →A dev agency built with a partner to help small businesses implement AI agents and automation — service first, product later.
Built out a partner, a delivery team, and real client-pipeline potential — sunset as we each found our own next direction to build in. Read the teardown →A privacy-first AI chat app, explored in the same wave that produced Myeverly — before checking whether it belonged in a category facing rising regulatory risk with no real differentiation.
Exited before productionizing — the mechanics worked, but the regulatory risk and competitive differentiation didn't hold up once I checked them. Read the teardown →A B2B learning resource for founders and startups on how to grow without burning capital — spend a first funding round on marketing that compounds, not on vanity metrics.
Ran as its own site and newsletter — consolidated once the audience and thesis turned out to overlap almost entirely with what I already wrote elsewhere. Read the teardown →A SaaS concept for cleaning companies — helping short-term-rental hosts vet, schedule, and verify quality across a roster of cleaners — seeded by a good friend's real-world rental-management business.
Stayed in market research — one friend's real pain never closed the gap to a repeatable, paying market. Read the teardown →A publication applying real experimentation rigor — sample size, test duration, design quality — to the behavioral-science literature, to separate what actually replicates from what's just popular.
Sunset as a standalone site — folded into research that's stronger next to an existing audience than standing on its own. Read the teardown →One-click cross-posting from WordPress to Medium — turn every post into syndication, backlinks, and a second audience.
Scoped, built, and shipped inside a single week — earned early signups, then moved on when my co-founder and I read the next move differently, keep pushing distribution or start the next build.An online academy applying research-backed behavioral economics to personal finance — teaching people to out-design their own biases.
Built a 2,900+ community and paid coaching clients, then wound down as I moved on to build the next thing — the behavioral-economics teaching muscle behind everything since.A local SEO consultancy for small businesses — Google, YouTube, and reputation management, delivered by a distributed freelance team.
Ran client work while managing 20+ freelancers with briefs, quality standards, and delivery workflows.Fight online misinformation by putting actual academics on the record — professors interviewed about their own research.
150+ professors contacted, 40+ interviews secured — including Dr. Thomas Simpson of the Federal Reserve Board — but only 10 fully produced; a one-person production and editing workload was the real bottleneck, not the outreach.A portrait photography business built on organic Instagram growth and referral trust — good creative and business fundamentals, wound down once it became clear I wanted to build software and companies more than run a service business.
6K+ Instagram following in year one, a 5-star rating on my Airbnb Experiences offering, and published editorial work — closed when I chose to put that time into building products instead of scaling a one-person service business.How I Build
Every product starts with a behavioral hypothesis, ships lean, and earns its next feature through real experiments — not opinions.
I build solo with AI-augmented development, validate demand before scaling, and treat my own products the way I treat a client's program: name the cognitive mechanism, predict the outcome, measure the lift. It's the fastest way I know to learn what actually moves people.
Ideas I'm Exploring
Beyond what I've shipped, I keep a running set of startup and product ideas — the problems I find worth solving and the first experiments I'd run to test them.
Browse the ideas →Building in growth, experimentation, or AI?
I angel-invest in and advise early-stage teams in these spaces — and I take on a small number of consulting engagements each quarter.
Revenue Frameworks
for Growth Leaders
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