What Pain-Point are you Solving and How did you discover it?

@jake_friedberg Mine started with a problem I was tired of having.

I have ADHD, and one of the things that comes with it is time blindness. I'd get completely absorbed in what I was doing, look up at the clock, and realize I had missed a Zoom meeting or was already late for an appointment.

The strange part was that I already had Google Calendar reminders turned on. They just weren't enough. Notifications are easy to dismiss or overlook when you're hyper-focused.

I kept thinking, "Why can't my calendar trigger a real alarm instead of just another notification?"

I looked for an app that did exactly that. I couldn't find one. Well, I found some but they didn't work.

So I built Never Miss Meetings for Android. It syncs with Google Calendar and lets you create actual Never Miss Meetings alarms for the events you choose. Simple on purpose.

As for validation, I admittedly did it backwards. I built the app because I needed it. Then I found out I wasn't alone. People with ADHD, busy professionals, students, salespeople, PARENTS—anyone who lives by their calendar immediately understood the problem.

The biggest surprise? Building the app wasn't the hard part. I used a no-code platform, but getting Google OAuth approved, navigating Play Store requirements, and polishing the user experience took far longer than I expected.

One thing I learned is that simple products can solve big problems. I deliberately resisted the urge to turn it into another bloated productivity app. Sometimes the best feature is knowing when to stop adding features.

It's launching on Product Hunt tomorrow, so we'll see what the community thinks!

Love this thread.

My pain point was honestly pretty personal. I kept seeing families — especially parents with young kids and teens getting their first pet — completely overwhelmed by the naming process. Every resource online is just a list. No personality, no context, no fun. It felt like such a missed opportunity for something that should be a really special moment.

So I built My Petaverse — not to make money, but because I genuinely wanted to create something families could do together around a pet. Something a 12 year old and their parent could both enjoy.

I also loved the idea of sneaking in a little language learning through the name meanings and personality descriptions — available in five languages so kids around the world could use it.

The biggest surprise? Building it with zero coding experience through vibe coding and Google AI Studio. I had an idea and just... figured it out as I went. Shipped a real iOS app and I'm still kind of shocked that worked

I wanted something that felt genuinely fun for families and first time pet owners, not just another utility app. Honestly the money was never the point.

ours started from noticing a friend's voice go flat for weeks before they'd admit anything was wrong — the tone changed way before the words did. validated it by pulling old recordings where we already knew the outcome (diagnosis, layoff, breakup) and the vocal markers were there weeks earlier than anyone said anything out loud. hasn't drifted from that: still just trying to catch the change before the person notices it themselves.

Timing in outbound sales... I discovered it working as an Account executive!! I was tired to reach out too late to clients... So I built a tool for myself called clicke.io and the my collegues wanted to use it too so... I am here now and launching the 21st of july!!

ArtfulAsthetics started out as just another generic website to sell designs.

1. When starting the company, the first digital products I uploaded were aesthetic to-do lists. However, when I saw just how saturated the market was, I decided to make vehicle outlines instead and listed them on Etsy. After a few months of uploading, I started to think about the multitude of art being generated/prompted with no real creativity. Therefore, I built a platform where you sketch, outline, and then aim for a similarity of 80% or higher before you are allowed to publish your design.
   

2. A couple of signals that the problem was worth solving were consumer frustration over a design they purchased being computer-generated, and all other websites allowing prompted art to still be sold, meaning buyers needed a way to differentiate between real and fake art.

3. We tend to sometimes pay for things we can't find anywhere else. Thus, being able to buy designs you know aren't just generated, but created, will probably make some more willing to purchase hand-drawn designs over prompted ones.

4. Yes, the solution to the problem stayed the same. However, I did make many changes to the core functionality for how designs were published.

5. Up to this point, it has been the domino effect of features and ideas arising from other problems that needed to be solved within the platform.

If you happen to want to check it out, here is the link to the website: https://www.artfulasthetics.com.

Our whole app is built around one question: "Would you buy it again?"

The pain: my wife and I kept finishing bags of coffee we genuinely loved — and forgetting them. Three weeks later we're back at the roastery or coffee shop, staring at the shelf, no idea if it was this bag of Ethiopian or the other one.

And we weren't unusual. Specialty coffee has gone fully mainstream — every city has ten roasters now, every office has three people with strong grinder opinions — but nobody really had a "system" to keep track of what they liked and what they would buy again.

So we built Tamp. Log a bean in 30 seconds. When the bag's empty, answer the one question that matters: would you buy it again?

Here's where it gets interesting: those answers add up to your actual taste profile — not what's trending, what you rebuy. Tamp uses it to point you at your next bean, from a directory of 1,000+ roasters with live stock from their webshops. Loved that washed Ethiopian? Here are three you haven't tried, in stock right now, from roasters you've never heard of.

Journal in, discovery out. The more you log, the better it finds your next favourite.

I’m building VAT Engine to solve the fragmentation around cross-border EU VAT.

The problem is not simply finding a country’s standard VAT rate. The correct treatment can depend on the destination country, product category, supply date, customer context, thresholds, sales channel, and reporting scheme.

Smaller e-commerce and SaaS teams often end up combining spreadsheets, generic tax APIs, separate platform plugins, and manual accountant work. The calculation happens in one place, transaction evidence is stored somewhere else, and OSS reporting becomes another separate process.

I discovered the depth of the problem while researching how official EU VAT data could be turned into something developers could actually use reliably. The official data exists, but it needs normalization, historical validity handling, merchant-friendly product classes, and a clear connection between calculation and reporting.

VAT Engine turns that into one workflow: official EU rate data, historical lookups, exact VAT calculations, transaction evidence, threshold monitoring, and OSS/IOSS reporting preparation.

It is currently in alpha, so I’m still validating which parts create the most value for real merchants, developers, and accountants. The main thing that has stayed consistent is the belief that VAT calculations should produce reusable compliance evidence—not just return a percentage and disappear.

VAT Engine

I found the problem the same way most people do, by living inside it first. I was running three businesses at once, a software company, a care home, and until recently a cafe, and I was the one holding all of it together in my head. Not a dashboard, not a system, just memory and a running mental tally of what needed attention that day.

The signal was not one big moment, it was a pattern. I kept catching the important thing late. Not missing it entirely, catching it a day or two after it actually needed me, which in a business is often the same as missing it. I started asking other founders running more than one business if that felt familiar, and it did, almost every time.

Has it stayed true to the original idea? Mostly. The core problem never changed, knowing what actually needs you right now across everything you run. What evolved is how careful the answer has to be. Early on I underestimated how much founders needed to trust the answer, not just receive it, so a confidence label became as important as the alert itself, whether something is Verified, Very Likely, Needs Review, or Monitor Only.

What surprised me most is that I did not actually test this on a spreadsheet or a mockup. I tested it for months on a real small business, Bird's Nest Cafe, before I trusted it enough to build it out further.

FounderFlow is your AI Executive Chief of Staff. It watches your business, identifies what matters, protects your revenue, and tells you exactly what to do next. Right now I am inviting in the first 30 founders personally instead of opening it up to everyone.

Curious how you are validating that people would actually pay to have less on their plate, versus just agreeing that the problem is real.