343 karma · joined October 20, 2023
Most definitions of genius are more liberal than a 1 and a million talent and he was at least that.
Actually try a definition and see what happens.
Rolling stone made a best list. SLTS was number 5.
He’s written some of the best songs ever by many definitions. That makes him a genius. Both terms are ambiguous, debating that is boring.
In fact, the ability to tap into mass media only makes the impact of a song greater. Access to electric instruments and effects only gave them more ability to create interesting music.
I’m a fan of all kinds of music old and new. But anyone saying German leders or old timey civil war ditties are better than Smells Like Teen spirit are high on their own supply.
Most of history humans expressed an extraordinarily limited range of emotion in song, in rigid form. Kurt Cobain wrote more than one song that you could play for a toddler and they’d love it. He wrote more than one song that hundreds of millions of people are listening to 30 years later. I’m sorry but your favorite Gregorian Chant is just not very good in comparison.
Also part of what made him so good was how he played vocal melody and rhythm off of chords. So in some songs you might have plain power chords but the melody hits important major or minor notes.
I don’t know what your definition for genius is but the guy wrote some of the best songs in human history and did so without a primary collaborator or big production crew of cowriters and collaborators. I think we can call him a genius.
so not just google sheets as the backend, google sheets as your personal backend for you instance of the app.
In general, put off automation for anything that's not every day or month that you can't just do in a few hours , e.g.:
* Parts of performance assessment & compensation tooling
* Sophisticated recruitment analytics (especially important because with small data it's often not precise or accurate/needs manual attention)
* Provisioning new stuff that doesn't happen often: databases, clusters..etc.
* Maybe the biggest bucket of stuff in general is analytics. Often times people try to get whiz-bang end result numbers with data sets of like 100. It's almost always the wrong move to have crazy analytics abstraction layers and automation when the numbers are small.
A potential simple heuristic might be something like: if it take a day or longer to automate, you need to save at least 5 days of time in the next 6 months for it to be worth it.