carpenter

Just an aside on the carpenter metaphor, there's sort of a running joke that a carpenter's house is never finished.

However, the carpenter is not paid for his labor for the last two hours a day.

Think the software equivalent of a contractor coming in to fix what the first carpenter screwed up, because the first carpenter didn't care once the house passed inspection.

So all totalled inputs are $80, and the labor from the carpenter produces $20 of wealth per table.

Designing in the browser feels like you're actually crafting something real, the same way a carpenter is refining the actual pieces of wood until it turns into furniture.

That would be like being a carpenter who refuses to use powertools and instead relies on manually operated ones.

This is like asking a carpenter to prove their skills by building you a deck, in a day, for free.

But as the carpenter goes on doing his stuff, the things he did stay put.

Maybe if every single thing the carpenter made was a highly customized bespoke piece.

The carpenter produces two tables an hour, and works for eight hours a day.

There's so many fundamental differences between physical objects and software that my eyes glazed over as soon as he started the carpenter rant.

The carpenter keeps all the wealth he creates for the first six hours a day - his daily take home pay is $240.

A lot of HN comments read to me as if a carpenter described his job as "swinging a hammer."

Carpenter analogy is as bad as the "book author" analogy.

I initially thought "Wait Jon Carpenter won 1M $ on Who Wants To Be Millionaire in 1999" which is way before 2006.

Using SCM is undeniably beneficial, but using it to become a "master programmer" seems a bit misguided, like becoming a master hammer swinger will make me a master finishing carpenter.

We’re a small (currently 8 full-timers) and fast-growing biotech startup with an amazing set of advisors including the Broad’s Anne Carpenter, and we're using high throughput biological experiments in human cells, automated image segmentation and feature extraction, and machine learning and statistics to find new treatments for rare genetic diseases faster than anyone has previously thought possible.

We’re a small and fast-growing biotech startup with an amazing set of advisors including the Broad’s Anne Carpenter, and we're using high throughput genetic perturbation experiments in human cells, automated image segmentation and quantitation of hundreds of features for every cell, and machine learning and statistics to find new treatments for rare genetic diseases faster than anyone has previously thought possible.