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en zyme's avatar

"technical debt" is real. However, it also can be used a way just to spin cycles. Rewriting code and capriciously updating tools, can a) be disastrous, b) achieve no net gain, c) distract from more operational needs. Coders who are too keen to address technical debt might just be seeing the twigs and not the trees.

What does technical debt look like in biotech?

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Jesse Johnson's avatar

Right - Just like monetary debt, technical debt isn't universally bad and paying off your mortgage early may not actually be the best option.

On the data side of biotech, you have all the same kinds of technical debt as you do in Tech, except that your user bases is typically much smaller, and many things stay as more-or-less prototypes, so the "interest rates" are much lower.

Of course, there are all sorts of other types of debt involved in experiment and process design, but that's a whole different can of worms.

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en zyme's avatar

Writing down "goals and objectives" is hard. Oftentimes they are replaced by slogans and platitudes. Developing metrics is key. If the goals for each department are the same, there is a flaw. If a goal is too easily agreed to, that's another weak link. Revisiting goals along the way, might just prevent a runaway traiin.

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