Sitemap - 2024 - Scaling Biotech
Reader question: What would you ask an LLM when selecting software?
Can you trust AI to clean your data?
If you want something done right...
The problem with an AI computational biologist isn't the AI
Track your lab data from when it's just an idea.
Handoffs should have staging areas
Do you know what decisions you're making?
Introducing the Biotech Reference Stack
Categories are about the what, but the how matters too.
This is the middle school of emerging software markets
Software categories come from nails, not hammers
We need to have a talk about (design) philosophy
Monolithic biotech software is a market problem
There are no snowflakes in biotech
Are you looking for a drill or a hole in your wall?
Biology software isn't bad. You just haven't found the good stuff.
Are meta-decisions getting in your way?
Sometimes, breadcrumbs are enough
Do you have a "trust but verify" budget?
On AI and Information Theory (aka the obligatory LLMs post)
Do you have "hurry up and wait" problems?
Hit dashboards may feel easy but they're not
Beware the long tail of orthogonal assays
The bottom line is too far away
You don't need a platform to be data driven
Are you safe or are you comfortable?
Start normalizing data driven biotech
Biotech data is a three-dimensional problem
Deadlines are not just manager mind tricks
Time for automation? It's less common than you think...
You have a process, you just don't know what it is
There's more to keep track of than just the answer.
Running an analysis job is more than just running analysis
Biotech startups are the craft brewers of data generation
The 3 reasons infrastructure projects fail