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saltwatercowboy • today at 2:01 PM • 3 replies • view on HN

Yes... there are statisticians on my team, for example. They're capable, thoughtful individuals however have little exposure to the oblique and (outwardly) contradictory ways in which production software fails.

But explaining that openly, as is your duty, means surfacing something which could be read as 'bad work' by a non-technical manager unable to grasp the complexity. So in low-trust teams it very quickly becomes a game of brinkmanship, or a prisoner's dilemma for technical diligence


Replies

leoqa • today at 3:32 PM

I am currently in a stalemate where I have written a proposal that is very technical. The only “business” outcome is that we clean up a massive security mess and rebase on a new consistent architecture.

My manager can’t understand the RFC, and knows that clean up projects aren’t palatable to his senior eng leadership so he keeps asking me to simplify or derive some business justification. I’ve proposed superficial ones like improving security posture etc but he wants a hard number that can be measured (yet another senior leadership mandate).

I’m kind of exasperated and honestly think it’s his job to figure this out.

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Loquebantur • today at 2:52 PM

The problem is the "interface" of software engineering being oblique to outsiders. It's alchemy in essence.

The logical extrapolation of AI capabilities stress-testing human software is all bugs being discoverable. Hence, you have to aim for actually bug-free software.

The only way to do that is to make your code provable. That again is only realistically doable using AI.

In the process, people will have to turn the current mere pretense of software engineering into reality, making the engineering part explicit.

That in turn only works when humans actually understand what they're doing and can communicate it to outsiders.

acedTrex • today at 3:59 PM

This is why open source eventually wins out, it doenst have this pressure.