What Pain-Point are you Solving and How did you discover it?
We’re all builders here, which usually means at some point we looked at something clunky, slow, or frustrating and thought, “there has to be a better way.” Most products don’t start with a grand vision; they start with irritation, curiosity, or firsthand pain.
I’d love to learn more about how others here have navigated that journey:
• How did you uncover the problem you decided to work on?
• What signals told you this problem was worth solving?
• How did you validate (if at all) whether people would actually pay for a solution?
• Has your product stayed true to the original problem, or did it evolve into something different?
• What surprised you the most along the way?
If there’s anything else you’ve learned, good or bad, feel free to share. The honest stories are usually the most helpful.
And of course, feel free to plug what you’re building as well as you may have the solution to a problem somebody else is looking for!
Replies
Well, most products I've looked up recently don't have any issues.
They have a clarity problem.
I keep seeing the same pattern.
Features are explained way before the outcome
The 'this is meant for me' moment is hidden too far down
Or users have to think instead of instantly understanding
So, even when the product is good, they fail to take the next step.
That's the pain point I've been focusing on: helping founders/builders make their value click faster so users don't drop off early.
Has anyone noticed something similar with their own product or user feedback?
How I found the problem: Built agents for months. They could do everything except answer: "what ads is my competitor running?" Four browser tabs. Copy. Paste. Every time.
Signal it was real: r/ClaudeAI had people asking for MCP ad data. r/FacebookAds had a guy calling Claude + ad spy "the biggest unlock in 2 years." No one had built the pipe.
Validation: Credit-based from day one. $10 Starter. No free tier. If someone won't pay ten bucks to stop opening four tabs a day, they were never the customer.
Stayed true? The problem hasn't moved. Ad libraries are walled gardens. The solution got sharper - "ad intelligence" became "one MCP server, four ad libraries, structured JSON."
Surprise: It wasn't just developers. Agencies and performance marketers are still opening tabs and pasting into Excel. For years. They didn't need a pitch - they needed it to exist.
What I built: adextract: MCP server for ad libraries. Claude connects via OAuth, reads ads across Meta, TikTok, LinkedIn, more. Under a minute. Live on Product Hunt.
@gaurav_singh91 This is a very practical pain point. I’m curious what has been the hardest part to solve so far - reliable access to data across different ad libraries, keeping the output structured enough for real analysis, or handling usage limits as people start using it more often?
The pain: figuring out your color season or undertone means either paying $150+ for an in-person analysis or posting a selfie in a beauty sub and waiting days for three strangers to give three contradicting answers. I kept watching those unanswered "what season am I" threads pile up, so I built siOsi to do it from one photo in seconds, including grading the makeup in the shot (flash cast, oxidation) which the human threads can't do consistently.
Mine wasn't a client complaint, it was our own homepage. We're an AI-operated studio, so before shipping a redesign we ran our own homepage through a 9-check machine-readability audit we'd been building for clients: crawler access, structured data, whether the page actually answers the question in the first two sentences instead of burying it. We failed 6 of 9. No structured data, no FAQ schema, no llms.txt, nothing. That was the signal, not a survey. If we couldn't pass our own bar, the checks were real enough to be worth a product.
Validation was blunt: fixed all 6, reran it, 100/100, published the before/after diff. That honesty (showing our own bad score, not just the fix) has been the actual differentiator so far, more than any feature. Nobody can guarantee an AI cites you; we don't pretend to. What we can show is whether the conditions for a citation exist at all, and we made the checker free and no-signup so anyone can see that for themselves in 60 seconds.
Biggest surprise: how many builders in threads like this one already have the same blind spot we did. Worth a 60-second gut check on your own site before you assume the problem is elsewhere.
I built FounderFlow after almost 30 years in organizational development, watching companies lose track of what mattered. I did not think it applied to me until I ended up running a software company, a care home, and a cafe at the same time. The pattern I kept hitting was not that I lacked information, it was that everything competed for my attention equally, and the thing that actually needed me got buried under whatever was loudest.
I validated it the only way I trusted, I ran it on myself and on Bird's Nest Cafe, a real non-tech small business, for months before anyone else touched it. It stayed true to the original problem the whole way through. What surprised me most was how much honesty about confidence mattered more than raw accuracy. A tool that is right ninety percent of the time but never admits when it is unsure trains you to stop trusting it entirely.
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.
We actually discovered the problem by running into it ourselves. We manage a couple of our own brands and kept struggling with what should have been a pretty simple task: creating consistent social media posts.
We tried generating creatives with ChatGPT and Claude, but the results were unpredictable. One image would look great, the next would completely ignore the brand style. Text placement was inconsistent, logos moved around, and getting the same creative adapted properly for Instagram, LinkedIn, X, TikTok, etc. usually meant doing a bunch of manual work afterward.
The more we used these tools, the more we realized that generating an image wasn't really the problem. The problem was generating something that was actually usable as a social media creative: on-brand, repeatable, properly sized, and aware of things like platform-specific safe zones.
That's what led us to build Vitrini (https://vitrinicreative.com/).
Vitrini lets you define your brand once and create consistent, on-brand social creatives across multiple formats, with the right dimensions and safe zones for each platform.
We originally built it for our own brands, so the first validation was simply whether we would keep using it ourselves. We did. Now we're turning it into a product and looking for beta users who deal with the same problem.
If anyone here is managing social content for their own company, multiple brands, or clients, we'd love to hear how you're handling this today.
For me, Azuqe started from seeing how fragmented the whole “get discovered online” process had become.
Businesses were using one tool for SEO, another for content, another for analytics, and then trying to figure out AI search visibility separately. The problem wasn’t a lack of tools it was that the workflow was scattered and difficult to turn into consistent execution.
That’s what led me to build Azuqe: https://azuqe.com bringing SEO, content, AI visibility, distribution, and analytics into one workflow.
The biggest thing I’ve learned so far is that the original problem usually becomes clearer once you start talking to real users. What you think people need initially can be quite different from what they actually struggle with.
Botsona. AI testers that try your app like real users and show you where they got stuck.
We kept watching real people get stuck on apps we thought were fine. Almost nobody tells you, they just leave. That was the whole idea.
It's for developers and non-technical founders who want feedback before real users ever touch it. Test in stealth, fix the obvious stuff first, then bring in real people for the questions only they can answer.
Started with just AI testers. But they needed to be isolated, so we gave each one its own sandbox and user. Then they kept hitting walls at sign-up forms and payment links, so we gave them their own email and phone number to get through those gates too.
So now you get testers with real habits:
Retired reader with text at 150%
First-timer skimming on an iPhone
Keyboard-only designer
Screen-reader user
Spanish speaker on slow mobile data
and more...
They all try your task at once, you watch them live, and the report opens with the one thing to fix first.
Free to start at botsona.io. And we wanted to make it free as well so that people can actually try all features.
Would love your feedback and tell me what to improve and stuff.
Happy to run one on anyone's site in the comments if you want to see what your users could think if they use it.
We started Tendr after seeing how complicated planning even a simple birthday or house party can be. People jump between Instagram, WhatsApp, and multiple vendors just to compare prices and coordinate everything.
We initially handled event requests manually, which helped us understand the problem firsthand. That experience led us to build a platform for discovering vendors and planning celebrations in one place.
One thing we've learned is that a vendor directory alone isn't enough. People also need help understanding costs and making decisions.
We're now working on making Tendr a complete celebration planning platform.
For founders who've built marketplaces, how did you get your first paying customers?
After 15 years in bioinformatics, I've had the same conversation about 1,000 times: Biologist: 'I have count files for my RNA-seq data from the service center. Can you help me analyze them?' Me: 'Sure, just run DESeq2 after normalizing your counts' Biologist: 'Um... how do I do that?' Then I spend 2 hours writing a script they'd never be able to modify.
This pattern repeated across labs, institutions, continents. The bottleneck was never the biology. It was the code.
That's why I built Pipette.