I'm a big fan of this explanation/rant from Andrew Murphy.

Taken as a whole, there are many bottlenecks in a corporate software development process. The "load-bearing" calendar is a great example!

Speeding up code creation just increases pressure on the bottleneck, which decreases throughput.

https://andrewmurphy.io/blog/if-you-thought-the-speed-of-writing-code-was-your-problem-you-have-bigger-problems

If you thought the speed of writing code was your problem - you have bigger problems | Debugging Leadership

AI coding tools are optimising the wrong thing and nobody wants to hear it. Writing code was already fast. The bottleneck is everything else: unclear requirements, review queues, terrified deploy cultures, and an org chart that needs six meetings to decide what colour the button should be.

Debugging Leadership

So why are we still trying to optimize code creation?

For decades, people with power - executives and product people - have been shifting the blame for strategy failures and poor market insight onto development "productivity."

This AI moment should be incredibly clarifying. Like, it should be the reductio ad absurdum of a productivity-centric approach.

The fact that we are *not* seeing wildly improving software all around us tells us everything we need to know.

There is no flourishing of value delivery, new product categories, more needs being satisfied better. It’s the opposite.

All we are seeing is decreases in quality, because 👏 code 👏 creation 👏 is not 👏 the problem.

@elizayer Claude Code found a 23-year-old Linux vulnerability, the kind a regular human security auditor would have taken weeks or months to find (or in this case, 23 years). https://mtlynch.io/claude-code-found-linux-vulnerability/
Claude Code Found a Linux Vulnerability Hidden for 23 Years

Claude Code has gotten extremely good at finding security vulnerabilities, and this is only the beginning.

@ulveon so this case justifies bazillions of dollars to be invested in needless serverfarms? And if that vulnerability wasnt discovered for 23 years it was prolly so well hidden that it was not an issue at all. Think about it.

@elizayer

@diekehrseite Well, @ulveon doesn't say it explicitly, but this case *was* an interesting example of where we could no longer say the LLM "just generating code."

The fact that it can succeed at that level of sophisticated analysis suggests that when we have clear success criteria (e.g. "vuln found"), the LLM can do very hard things indeed.

Agree this will be really interesting to watch!

@elizayer
well … there is always a „but“.
Mine is: pattern recognition is fine and prolly helpful but doesnt need this hillarious amount of serverfarms at all. IMHO

@ulveon