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.
Natural language reproducible bioinformatics analysis.
No Python. No conda environments. No Stack Overflow rabbit holes.
Just the science.
Try it for free pipette.bio

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?