I interviewed this founder. Here’s what he told me.
Last week I talked with Collin, founder of PetsenseAI, an iPhone app that helps pet owners look more closely at mood and body‑language cues in a photo.
He’s early, scrappy, and refreshingly honest about what’s working, what isn’t, and what he’d do differently if he had to start from $0 again.
Below are the highlights from our conversation.
What PetsenseAI actually does
“I’m building PetsenseAI as an iPhone app that helps pet owners look more closely at mood and body language cues in a photo. The idea started with wondering whether AI could help people put words to the small changes they notice in their pets. I see it as a second set of eyes, not a way to know exactly what an animal feels.”
In other words: not a “mind reader” for pets, but a tool that helps owners notice and name subtle signals they’re already seeing.
From Bolt.new to a real mobile app
Collin’s first version was built fast:
“The first version was built with Bolt.new toward the end of 2025. Since then, I have moved into a React Native and Expo app and spent a lot of time learning how the app backend and AI analysis work together. It’s been a lot of building, testing, troubleshooting, and fixing things I didn’t expect.”
Classic early‑founder arc: prototype quickly, then spend months turning “something that works” into “something that scales and doesn’t break.”
First customer, first revenue, and the attribution blind spot
When I asked how he got his first paying user, his answer was very “early stage”:
“I got my first paying customer after I started putting PetsenseAI in front of people. I would share it on Product Hunt and talk with people directly, but I didn’t have attribution set up, so I can’t honestly say which one brought that first customer in.”
Current numbers (as of our chat):
$27 MRR
$10 in one‑time revenue so far
Small, but meaningful:
“It’s small, but getting someone to pay was a meaningful step for me.”
Where he’s actually learning: Reddit
For growth and insight, Collin’s favorite channel so far isn’t a fancy ad platform — it’s Reddit:
“Reddit has been the best place for actual conversation so far. Talking with pet owners and other builders has taught me more than just posting a link. I can’t confidently call it my biggest source of intel yet because I haven’t tracked attributions well enough.”
The pattern: conversations > link drops. He’s using threads to understand language, objections, and use cases, not just to spam the app.
The biggest mistake so far
If there’s one thing he’d fix in hindsight, it’s this:
“Waiting too long to set up basic analytics. I can see downloads and scans, but it’s harder than it should be to tell where people lose interest or what brings them back. That makes product decisions more of a guess than I would like.”
No fancy dashboards, just: Where do people drop? What makes them come back? Those answers are still fuzzy.
If he had to start again from $0 a day
I asked the classic “what would you do differently?” question. His answer was specific:
“I would start with a smaller group of pet owners and pay closer attention to what happens after the first scan. Do they find the result useful? Do they check in on the same pet again? I’ll measure that early, then build around what gives them a reason to return.”
Launch Score: Pestless AI
Idea – 7/10
Clear, emotional use case: helping pet owners read and track small changes in their pet’s mood and body language.
Growth – 6/10
Early but promising: Product Hunt, direct convos, and real Reddit threads. No repeatable channel yet, but good instincts.
Money – 5/10
$27 MRR + $10 one‑time. Tiny, but a real signal that people will pay.
Moat – 5/10
Tech is easy to copy; potential moat is brand, data, and longitudinal pet profiles over time.
Scale – 6/10
Big pet market, narrow wedge today. Room to expand into broader behavior/wellness tracking.
Final Launch Score: 6 / 10
Solid early launch with a human idea and first traction. Worth watching as he tightens product, retention, and growth.
