We ran this loop by hand for a decade. AppDNA is the loop, automated.
Ten years of growing other people's apps taught us exactly what works, what breaks, and why the knowledge keeps evaporating. AppDNA is that decade, encoded into a system any team can run.
AppDNA AI is an App Growth OS for subscription mobile apps, founded by Michael Synowiec and Michael Mroz. It encodes ten years of hands-on practice — roughly 300 apps worked on as a services team, including engagements for Aion Bank, Dunkin', and Homa Games — into an AI system that analyzes a subscription app's full funnel, proposes improvements, and ships approved changes without an App Store release.
Ten years. ~300 apps. The same loop, every time.
I've been growing mobile apps since iOS 10 — not advising, doing: onboarding flows, paywalls, store listings, retention journeys, ad accounts. Across ten years and roughly 300 apps, my team and I ran what adds up to hundreds of thousands of tests and optimizations — all delivered as services, by hand, before AppDNA existed as a product.
The loop never changed: audit the funnel, find the biggest leak, design the fix, ship it, measure, keep what works. What changed was how good we got at running it. A few engagements from that services era we can name:
SERVICES ERA
SERVICES ERA
SERVICES ERAAll of the above was delivered as services by the AppDNA team — the practice that became the platform. The software you can buy today didn't produce these results; the method inside it did.
Along the way I wrote an app-growth course that sold over 1,000 copies. Teaching the method is how you find out which parts of it actually transfer.
The problem was never knowing what to do. It was shipping it — and keeping what you learned.
Around year seven I started asking every team the same question: "What did you test in the last 12 months?" 8 out of 10 couldn't answer. The other 2 sent me 50 Excel files. That's not a study — it's my own count, from a decade of doing this work.
Eight to fifteen tools stitched together — analytics here, paywalls there, messaging elsewhere — each seeing one slice, none shipping anything. Smart people spending their week being the integration layer between their own tools.
A tester leaves — the context leaves with her. A contract ends — the doc goes stale. Ours included: we'd find the leak, hand over the plan, and six months later the learning had evaporated. Expertise that lives in people doesn't compound.
So we stopped selling the loop and built it.
By 2026, AI made the choice obvious. What took our team of specialists weeks — the analysis, the hypothesis, the variant design — can now happen in minutes, if it's a system grounded in a real funnel, not a consultant with a chatbot. The one thing AI didn't fix on its own was the part that was always broken: shipping the change and keeping the learning.
That's AppDNA — the audit that finds the leak, the playbooks from ~300 apps, the experiments engine, and the SDK that puts approved changes live on devices without an App Store release. The knowledge that used to leave with people now compounds in Growth Memory, in your workspace.
From manual growth to a self-improving app.
The App Growth OS for subscription apps: nine growth modules covering the full funnel, one event pipeline, one experiments engine, one SDK. And behind every module, its own specialist agent — the team we used to be, encoded: watching your data, diagnosing problems, drafting fixes. The system proposes. You approve. It ships. It learns. Complete on its own; compatible with everything you already run.
It's live in production today, with founding engagements running now — their measured results will publish on /customers as they complete.
Two Michaels. One loop.
Both halves of the loop, in one person. A decade in app growth since iOS 10, roughly 300 apps worked on personally, and the course that taught the method — and the engineer who wrote the platform and the SDK himself. He connects how subscription apps actually grow with the engineering to ship it, and that connection is what AppDNA is built from.
The growth architect. Over 7 years designing app growth — the playbooks, the paid and organic marketing experience, and the funnel and category patterns the system now runs on. He keeps the growth thinking deep and current, so the product's recommendations come from real practice, not generic advice.
The rules we run on.
Strategy stays human. Execution becomes automatic. We measure ourselves by experiments shipped, not reports delivered.
One-off wins reset every quarter. We build the system where every experiment becomes permanent Growth Memory.
Weekly cycles beat quarterly plans — but nothing ships without approval, rollouts start at 10%, and a stop-loss withdraws anything that hurts a guarded metric.
One source of truth for growth data — and the same standard for our marketing. Every number we publish is verified and framed for what it is. This page included.
Onboarding moves paywalls; paywalls move retention; retention moves acquisition. We never optimize one stage blind to the rest.
The industry sells dashboards and calls it growth. The world doesn't need more charts — it needs execution. We say so, politely, everywhere.
The audit is where every engagement of the last decade started. Yours is free.
Paste your App Store or Google Play link. Get your Growth Score, your biggest funnel leak, and a 90-day plan — the same first step we ran for every app we've ever grown, now in about 2 minutes.
Everything your app needs to grow. In one system.