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

great question 🙌 i build a few apps under studio.gold and each one came from a diffrent frustration:

speakeasy - i had 400+ articles saved in pocket that i never read. realized my eyes/hands are busy but my ears are free like 90% of the day. so i made an app where u paste any url and get audio back in seconds. the signal it was worth building? i was paying speechify $140/yr for basically this one feature buried in their bloated app.

astrologica - my gf checks her horoscope every morning but all the apps are either generic af or require like 10 mins of reading. built her a daily podcast version thats personalized to your actual birth chart. validated it by asking in r/astrology if ppl would want this - overwhelmingly yes.

wordplay - i got into cryptic crosswords and wanted to learn but theres no good beginner-friendly app. most ppl dont even know what a cryptic is. so i made a 1-clue-per-day app that teaches you how to solve them gradually. the surprise? retention is insane because its just 1 clue so ppl come back every day.

biggest learning: solve your own problems first, then check if others have them too 💡

Hey !
• How did you uncover the problem you decided to work on?
At previous job internal documents was always a mess. Even if updated and organized frequently. Chatbot trained on them would mitigate the mess.

• What signals told you this problem was worth solving?
The issues occurred in every company I've worked for. No solutions were or are out there to make so chatbot works within each departments needs without overpaying with per seat pricing or token markups. And should live in chats that company already uses - Google Chat or MS Teams.

• How did you validate (if at all) whether people would actually pay for a solution?
Validation basically came before the product was created as at first it was built for internal usage only. Currently there is no cheaper with the same capabilities option even after a year. The main validation came from building to resolve a real pain point most of the companies have.

• Has your product stayed true to the original problem, or did it evolve into something different?
Yes, the core has always stayed the same, Control and security over everything else. Recently it evolved from chatbot trained on companies knowledge to Chatbot trained on companies knowledge with option to trigger automation with guardrails. You can imagine it as personal assistant. "Hey I need a vacation" "Hey something is off with the report" - User interacts with AI then the interaction gets turning into an action and executed how ever client (NOT USER) wishes to via webhook. Why not User chooses what gets triggered? Because that is done by responsible people for the setup in each company. Another crucial guardrail in today's mess of AI automation.

• What surprised you the most along the way?

To be honest, the most recent was how versatile OpenAI API can be. Using the custom tool you can basically make anything. The hard part is the logic and system design. Which is the 2nd part which made me surprised : for some reason I got really good at designing the systems. How they interact, how to turn limitations into real product.

My first site actually came from the pain point of our main project. Non developers needed to be able to edit our copy without touching code. So we created Skyblobs, a lightweight copy editor for GitHub hosted websites.

I’ll be honest, my starting point was mostly irritation.

I was using disposable email services quite a lot while testing products and signing up for random tools. Most of them had the same problems: slow inbox loading, way too many ads everywhere, and some of the “good” ones were surprisingly expensive for what they offered. The UX was usually pretty bad too.

After dealing with that over and over, I just thought there has to be a cleaner way to do this.

That’s what pushed me to build @FCE - Temporary and disposable email — mainly focused on privacy, speed, and a cleaner UI without turning the inbox into an ad wall. Initially it was just something I built for myself and other developers who needed disposable inboxes while testing signups and workflows.

The signal that it might actually be useful was pretty simple: a few friends and developers started using it and asked if there was an API. That’s when I realized the problem wasn’t just mine — people wanted temporary email thats reliable and developer-friendly, not just spammy public inboxes.

What surprised me the most is how many services and platforms actively try to detect and block temp mail domains. That turned out to be a whole separate challenge I didn’t expect in the beginning.

Still evolving a lot, but it’s been fun learning along the way.

The pain point behind CoreSight came from watching consulting up close. Millions spent on work that follows repeatable frameworks.

After years of working in consulting, we encoded those frameworks into AI agents. 1,000+ users in with zero marketing spend felt like all the validation we needed.

Taking each of the questions one by one for PostGod:

Pain point: Founders know they should post on LinkedIn, but stare at blank screens for hours. Generic AI makes them sound like everyone else, and they don't have the resources to work with a ghostwriter.

How I discovered it: I have multiple friends working in personal branding, doing LinkedIn ghostwriting on their own or via agencies. The process now looks like this: agencies charge $1,200/month to ask clients questions, feed answers into ChatGPT, then invoice. The markup was insane for what was basically a systematic process.

Validation: Started talking to founders at startup events. Almost everyone had the same response: "I know I should post, I just never do." They simply didn't know what to say or how to say it without sounding generic and they didn't want to pay the insane fees agencies were asking.

Evolution: We stayed focused on the original problem (LinkedIn personal branding) but refined HOW we solve it. Started as "posts that sound like you" and evolved into "replicate the agency process" - because that framing clicked better with people who'd considered hiring ghostwriters.

Biggest surprise: How many people are willing to try it just because they're tired of sounding like ChatGPT. The "everyone sounds the same now" problem resonated way more than expected.

So, we built PostGod to give people the agency process without the agency price. postgod.app

We are helping B2B companies improve their website engagement and conversion using Agentic Live Video Agents. I discovered it by talking to over 30+ product heads, marketers and founders who repeatedly mentioned that they have been trying to fix it. Hence we built www.kickkers.com to support early stage & mid market cos. to help them in business growth.

For me, Paythread started from feeling like every tool was just… too much. I didn’t need a full accounting suite or some bloated system—I just wanted to track my time, send an invoice, and get paid (credit card or Zelle, done).

The signal it was worth building was realizing I kept trying different tools and none of them felt right. They either did way more than I needed, cost more than I wanted to pay, or made simple things feel complicated.

I didn’t formally validate it—I just noticed other freelancers were in the same boat, kind of hacking together their own setups to keep things simple.

It’s still pretty true to that original idea. If anything, I’m constantly trying to fight the urge to overbuild it and keep it focused on “just enough.”

Biggest surprise has been how easy it is for tools to drift away from what made them useful in the first place—and how hard it is to stay simple on purpose.

Two things hit at once, an MIT paper showing regular AI use for simple tasks measurably reduces cognitive engagement, and my own ChatGPT history full of "rewrite this sentence" and "what's the word for X." Things I already knew. I wasn't using AI as a tool, I was using it as a reflex. Same with feeds, opening Twitter with no intent, scrolling, closing, opening again.

Screen time apps tell you how much you used something. They don't ask if you tried first. That gap is what pause.do sits in.

25 years in US technology staffing. The pain was always there. I just finally got angry enough to build.

A client called one day — a candidate we presented had fabricated their entire employment timeline. Three companies, four years, complete fiction. Passed every manual screen. Cost us the relationship.

Signals that told me it was worth solving: — 1 in 3 profiles had some form of misalignment — Every staffing firm I spoke to had the same story — Nobody had built a pre-decision verification layer. BGC happens after offer. Way too late.

Validation came the hard way — I started running manual forensic checks for firms in our network. They didn't ask for a product. They asked "can you just keep doing this?" That's when I knew.

So I encoded 25 years of pattern recognition into an AI forensic engine. 4-layer check — credential integrity, timeline consistency, location signals, resume vs reality. Under 30 seconds.

Biggest surprise: how many people in HR knew this problem existed and just accepted it as normal. Nobody expected a fix. That's the best possible market signal.

— Navneet, WackoWave