I run nine companies right now. Not investment holdings. Not logos on a portfolio page. Nine operating businesses that I built — most of them in the last three years, and most of them with AI agents doing work that used to require full teams.
Here's the list:
Stormbreaker Digital — my marketing agency, now focused on AI agent systems. Multi-six-figure annual revenue since 2020.
TextEvidence — a legal tech platform helping family law attorneys collect and analyze text message evidence. 46 database tables in production.
Skill Refinery — an AI coaching platform built in partnership with Tony Jeary that delivers expert coaching skills inside Claude, ChatGPT, and Copilot through MCP.
CigarSnap — a consumer AI app for cigar identification and digital humidor management. Validated the market with 3,522 Reddit leads scraped for $1.08.
HeyBaddie — an AI study companion for homeschool students that connects to school portals via browser automation, pulls real grades, and delivers personalized coaching with four personality modes.
MyPRQ — parliamentary procedure SaaS with Zoom integration. Went from a PRD to a working app on Christmas Day.
LeadStorm AI — a B2B lead generation platform with 696M+ contacts, born from running thousands of campaigns through Stormbreaker.
The Cat Behavior Lab — a digital publishing business selling research-backed behavior guides. Built from idea to live product in under two weeks.
Fractional CMO engagements — embedded with B2B companies across manufacturing, healthcare, defense, and tech, building autonomous marketing engines.
That's not a humblebrag. It's the actual output. And I'm not writing this to tell you how impressive I am — I'm writing it because the way I built these matters more than the fact that I built them.
The Part Nobody Puts on the Portfolio Page
I need to rewind, because the "9 companies" headline doesn't make sense without the context.
I'm originally from Canada. Moved to Texas in 2016. Before any of this, I spent six years running an international nonprofit called Rooftop Missions. I was a global associate trainer with John Maxwell's EQUIP International, overseeing programs in Cuba, the Dominican Republic, and India. I started a children's home in India — the Azlynn Noelle Children's Home, named after my daughter who passed away in 2012.
That loss changed everything. It's the kind of thing that either breaks you or rebuilds you into something different. For me, it was both.
An unexpected divorce in 2015 forced me out of nonprofit leadership and into single parenthood. From 2016 to 2019, I tried everything — cleaning pools, real estate, flipping houses, insurance — nothing stuck, especially with two kids under five.
I didn't build my way out of that season alone. But I did build my way out.
In 2019, I found LinkedIn. Not as a social network — as a business development engine. I taught myself outbound marketing, started landing clients, and launched what would become Stormbreaker Digital. I co-authored "The LinkedIn Advantage" with Tony Jeary. Built a following of over 70,000. Generated over $3 million in revenue through LinkedIn strategies for myself and my clients. I worked with professional sports franchises, SaaS companies, financial services firms, and B2B companies across a dozen industries.
That was the foundation. But it wasn't the inflection point.
The AI Pivot
The inflection point came when AI agent systems became viable.
I saw the same thing I saw with LinkedIn in 2019 — a massive capability gap that most people weren't taking seriously yet. LinkedIn was underpriced attention. AI agents were underpriced labor. Both required the same thing: someone willing to actually build with the tool instead of just talking about it.
So I started building. First for Stormbreaker — automating the repeatable parts of client campaigns. Then for clients directly — AI agent teams that could handle content creation, outbound sequences, lead qualification, SEO, even competitive intelligence. Then I started building standalone products, each one solving a problem I'd either experienced myself or discovered through client work.
The speed kept compounding. Not because I'm some 10x developer — I'm not a developer at all in the traditional sense. The speed compounded because each venture taught the AI agents new skills, and those skills transferred to the next venture.
MyPRQ taught me Phase-Gate AI Development — writing explicit PRDs with database schemas and acceptance criteria before handing anything to an AI coding assistant. That methodology made HeyBaddie possible in three weeks instead of three months. HeyBaddie taught me browser automation patterns that now power features across multiple products. CigarSnap's Isenberg Framework — a five-criteria filter for validating AI app ideas — now saves me weeks of wasted effort on ideas that won't work.
Each one built faster than the last, because the AI agents keep getting better.
What "AI Agent Systems" Actually Means
I should be specific, because "AI agents" has become one of those phrases that means everything and nothing.
When I say AI agent systems, I mean autonomous software that performs real business functions on a schedule, with defined inputs, expected outputs, and approval gates for anything customer-facing. Not chatbots. Not prompts you run manually. Agents that wake up, do their job, produce output, and go back to sleep until the next scheduled run.
For Stormbreaker Digital, that looks like a team of seven AI agents handling entity SEO — one researches keywords, one writes content, one reviews it against an SEO checklist, one publishes, one cross-posts to Medium and LinkedIn, and one monitors branded search results weekly. They run on cron schedules. I review the output when it needs approval. Otherwise, they just work.
For TextEvidence, it's an AI SDR named Claudia that handles all inbound email replies from our outbound campaign targeting family law attorneys. She qualifies leads, answers product questions, and books demos. She runs 24/7 and never forgets a follow-up.
For client engagements, I've deployed AI agent systems for a defense contractor running recruitment marketing across 25+ military installations, a healthcare company building a competitive intelligence engine, and an air freight company repositioning their entire brand and go-to-market.
These aren't experiments. They're production systems running real operations.
The Venture Breakdown
Let me walk through a few of these in more detail, because the build stories are where the actual lessons live.
CigarSnap — Validation for $1.08
I needed to test whether cigar enthusiasts would pay for AI-powered identification. Instead of building anything, I ran an Apify scrape on r/cigars and pulled 3,522 active users for $1.08 total. Market validation doesn't have to be expensive.
I put the idea through the Isenberg Framework — five criteria I use to evaluate AI mobile app opportunities: the audience actively spends money, a repeating problem exists, the solution involves photo or video input, accuracy matters enough to pay for, and existing tools are weak. Cigars scored on all five.
Then I built. 15+ features shipped in 48 hours using Replit Agent. A digital humidor. A smoking journal. A community feed. An AI persona named Don Carlos that talks like a seasoned tobacconist. And underneath the consumer app, a Trojan Horse strategy — the real revenue model is B2B lounge partnerships at $49-149 per month, using foot traffic data the consumer app generates.
MyPRQ — Christmas Day Build
Al Gage, a co-author of the actual parliamentary procedure standard used in organizations worldwide, needed a tool to manage speaker queues in formal meetings. He'd been doing it manually for decades.
On Christmas Day, I wrote a detailed PRD — database schemas, API routes, UI components, acceptance criteria for every feature — and handed it to an AI coding assistant. By that evening, I had a working Zoom application with OAuth integration, real-time speaker queue management, and a host dashboard.
That's not an exaggeration. PRD to working app, Christmas Day, one session. The Phase-Gate AI Development methodology — write the spec completely before touching code — is what made it possible. AI coding assistants don't struggle with building. They struggle with ambiguity. Remove the ambiguity and they build fast.
HeyBaddie — The Architecture Play
My daughter needed help with online school. The platforms her school uses don't have APIs. Most parents are just hoping their kid logs in.
So I built Baddie — an AI study companion that uses browser automation to log into school portals, scrape real grades and assignments, and inject that data into a dynamic system prompt. The AI doesn't guess what the student needs to work on. It knows, because it has the actual gradebook.
Four personality modes. A gamification layer with 47 badges, XP, and streaks — calibrated so every reward feels earned. A parent dashboard that shows academic progress without exposing private conversations. An extended family "Cheer Squad" feature where grandparents and aunts can send encouragement.
20+ database tables. Three parallel Claude Code sessions running simultaneously. Total platform operating cost: $15-25 per month.
Built in 2-3 weeks.
The Model
There's a pattern across all nine companies, and it's the same pattern whether I'm building a legal tech platform or a cat behavior guide:
Identify a real problem. Not a market opportunity. A problem someone has right now that isn't being solved well.
Validate before building. The Isenberg Framework for consumer apps. Discovery calls and proof-of-concept sprints for B2B. Never build first and validate later.
Write the PRD completely. Phase-Gate AI Development. Every database table, every API endpoint, every user flow, every edge case. The PRD is the product. If I can't spec it completely, I can't build it completely.
Build with AI agent assistance. Claude Code, Replit Agent, parallel development sessions. The AI handles the code. I handle the decisions.
Deploy autonomous systems from day one. The AI agents don't come later. They're part of the initial architecture. TextEvidence launched with an autonomous content engine. Stormbreaker runs on a 7-agent SEO team. The Cat Behavior Lab has automated DM sequences handling customer acquisition.
Ship fast, then compound. Every venture makes the next one faster. Frameworks transfer. Agent skills transfer. Even the mistakes transfer — I fail faster now because I've seen the patterns.
What's Next
In 2026, I'm focused on three things.
First, scaling the AI agent systems practice at Stormbreaker Digital. More clients need autonomous marketing engines — not agencies that bill hours, but systems that produce output 24/7.
Second, pushing the product ventures toward their next milestones. TextEvidence is running an outbound campaign to 432 family law attorneys. Skill Refinery is launching the self-serve extraction engine. CigarSnap is building toward B2B lounge partnerships. HeyBaddie is expanding browser automation coverage.
Third, building in public. This blog is part of that. I'm going to show the work — the technical decisions, the frameworks, the wins, and the stuff that doesn't work. Not because I have wisdom to dispense. Because I think the most useful thing I can share is what it actually looks like to build nine companies with AI agents, in real time.
The ability to create is the most human thing we have. I'm going to keep using it.
I'm Matt Cretzman. I build AI agent systems through Stormbreaker Digital, serve as fractional CMO for B2B companies, and run ventures across legal tech, AI coaching, consumer AI, EdTech, and more. If you want to see how AI agent systems work in practice, follow along — I'm publishing daily.
