Those who’ve worked in software will immediate recognize the phenomenon of “messes that look like successes.”

One of my old Paulisms is that the real purpose of a whole lot of software processes is to make large-scale failure look like a string of small successes.

The crisp “even an executive can understand it” version of the OP is:

⚠️ AI increases labor costs ⚠️

(“Why?” “Because it’s labor-intensive to clean up its messes.”)

I said “the purpose of a whole lot of software processes is to make large-scale failure look like a string of small successes.”

Huh? What does that look like??

It looks like this:

✅ Meetings held
✅ Plan signed off
✅ Tests passed
✅ Iterations iterated
✅ Velocity increased
✅ Thing implemented
✅ Checkpoints checked
✅ Thing released
✅ Blinkenlights blink
✅ Line goes up
✅ Thing updated
❌ Software never •really• solves the problem it was supposed to solve in the first place, creates more problems

or ❌ Problem the project was supposed to solve in the first place was the wrong problem

or ❌ Nobody actually wanted it

or ❌ We totally failed to understand the real effect of implementing this

or ❌ The goal was designed to benefit some individual / faction within the company, not the mission

or ❌ The goal was designed to benefit the bottom line / investors / some horrid systemic evil, and is net harmful to humanity / the world

(Yes, I consider that last one a failure too.)

@inthehands okay I'm booking this whole thread, it's so succinct and relatable. Honestly a nice reminder of the scope at play.

I'm curious, how pervasive would you say this is? Is this like every project in every org? Or half of half? Struggling to see past my own experiences, which are honestly a lot of this on repeat.