sonal waghchoure's profile on Product Hunt

About

10+ years of Quality Assurance experience in Banking, Healthcare, and E-Commerce domains. This work gave me insight into how products are built, where requirements go wrong, and what it takes to deliver something that actually works for the user. I have developed a keen interest in building products that solve niche problems. My current areas of focus include: Product Strategy Customer Research and Product Discovery New Product Development and Product Lifecycle Management AI in Product Development Building an understanding of how AI is used in product development, including evaluating AI features for accuracy and reliability.

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Forums

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30d ago

How do you decide how many features to add so your product is not too broad or too narrow?

I believe that when launching a product on Product Hunt, you should focus on one main feature and two supporting features that help bring the whole idea together.

When I see a new product with too many features and the whole tool feels complex, I start to lose my understanding of what it actually does.

p/touchgrass-2

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1mo ago

How much time should we pend in front of a computer (when our work depends on being online)?

I probably spend more than 10 hours a day at my computer and I know it s not ideal. It is actually bad.

It has quite a few negative effects on our eyes, posture, stress levels, and overall well-being.

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1mo ago

My AI model broke down 2 times in 8 days and it made me think differently about choosing one

Picking the AI model is a crucial decision for my product, and I really underestimated how hard it would be to pick one.
Before launch, I was considering things like:

Will users trust something that processes their messages with a model they have never heard of?
What is the real uptime record, versus the claimed one?
Do I go cheap/free, or pay more for something that will last longer?
Self-hosted? Or just ride on someone else s frontier model and take their roadmap?

I took a solution and moved on, as you do when there are fifty other decisions to be made. And then on July 9th everything just stopped. There were no warnings I could see I spent hours debugging my own code before realizing the model itself was the problem. It turns out it was being decommissioned that October, and apparently a silent outage is how that gets communicated.
I re-engineered the architecture to always have a backup model running in parallel, which quietly nibbled into margins I had already modeled carefully. Then again, same thing happened July 16. I don't think I've really worked this out so much as I've gotten better at taking it in when it happens again.
For other founders building on someone else's AI model -- do you build in redundancy from day one or did it take getting burned once before you took it seriously?