Data AI in life sciences
Dark data: science below the waterline
Life sciences does not lack data. It lacks usable records of what happened at the bench—and AI cannot learn from evidence it cannot see.
Read article →Sous.bio
HomeNotes from the bench
Writing about reproducible wet-lab work, connected experiment records and the software that supports them.
Articles
Product thinking
Protocols are the building blocks of experimental work
Laboratory protocols should be more than static instructions. They should connect planning, execution and learning without taking control away from the scientist.
Read article → Lab notes
Why experiment context matters
A result is only as useful as the record around it. Here is what laboratories should capture to make experiments interpretable, reproducible and easier to build on.
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