The danger here is that many people think that software is all about having code that seems to work when you try it. Those people have never been able to get past “Hello, World” in X for Dummies, so they don’t realize all the practical realities of software distribution that are very much more nuanced and complicated than just writing the code. They get their hands on some working code and wheeeee!!! Ship it!!!
A while back I compared LLMs to lightsabers - and pointed out how many amputees are found in the Galaxy far far away that has lightsabers.
This is one of the big issues i have in my job. I’m on a dev team but a majority of the people around here are research data scientists. And a shitty 1000 line python script with zero regard for quality, that only really produces a bar chart as output and is never used again after 6 months is all they ever work with. And LLMs are amazing for that. But these data scientists don’t seem to understand that not all software is like that. So it’s really hard to have a real conversation about it.
And wouldn’t you know it, these are some of the same kind of people building this stuff and pushing the vibe coding narrative.
Produce correct results even when encountering “edge cases.”
Not crash, even when encountering “edge cases.”
Work correctly in all deployment environments.
Work correctly after scope creep multiplies the feature set by 3x, 10x, 30x… yeah, successful projects experience that kind of expansion.
Work correctly after the operating environments shift under your feet - can the code be updated to work with the next version of Android? iOS? Windows? Linux? After “security updates” take away the infrastructure you were depending on for correct functioning?
Will it scale to 100 users? 10,000? 10,000,000?
What happens when “threat actors” actively target the system?
What happens when your methods / development processes aren’t compliant with new government regulations?
Are you ready for IP lawsuits, whether deserved or not?
The danger here is that many people think that software is all about having code that seems to work when you try it. Those people have never been able to get past “Hello, World” in X for Dummies, so they don’t realize all the practical realities of software distribution that are very much more nuanced and complicated than just writing the code. They get their hands on some working code and wheeeee!!! Ship it!!!
A while back I compared LLMs to lightsabers - and pointed out how many amputees are found in the Galaxy far far away that has lightsabers.
This is one of the big issues i have in my job. I’m on a dev team but a majority of the people around here are research data scientists. And a shitty 1000 line python script with zero regard for quality, that only really produces a bar chart as output and is never used again after 6 months is all they ever work with. And LLMs are amazing for that. But these data scientists don’t seem to understand that not all software is like that. So it’s really hard to have a real conversation about it.
And wouldn’t you know it, these are some of the same kind of people building this stuff and pushing the vibe coding narrative.
Or should produce “correct results.”
Produce correct results even when encountering “edge cases.”
Not crash, even when encountering “edge cases.”
Work correctly in all deployment environments.
Work correctly after scope creep multiplies the feature set by 3x, 10x, 30x… yeah, successful projects experience that kind of expansion.
Work correctly after the operating environments shift under your feet - can the code be updated to work with the next version of Android? iOS? Windows? Linux? After “security updates” take away the infrastructure you were depending on for correct functioning?
Will it scale to 100 users? 10,000? 10,000,000?
What happens when “threat actors” actively target the system?
What happens when your methods / development processes aren’t compliant with new government regulations?
Are you ready for IP lawsuits, whether deserved or not?
That is a pretty high bar compared to being correct. XD