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Eight Myths on Software Engineering and GenAI
61–70 of 269 posts
Re: Eight Myths on Software Engineering and GenAI
#6211-18% of time spent in coding is still very high number I think. For a large org with lots of process and risk aversion, this number could be as low as 5%. Even for 14%, the 10x improvement could mean 86+(14/10) => 87.4/100 => 12.6% overall time saved.
And time in coding is like time on highways for taxi drivers. A fairly useless metric.
Re: Eight Myths on Software Engineering and GenAI
#63> studies at Microsoft and elsewhere showing it’s closer to 14 percent This is a depressing stat. The real productivity gains come from leaving soul sucking big tech companies where nothing gets done with any sort of urgency.
It is not urgency. Large production systems mean you are doing mostly unsexy operational planning. If I had a dollar each time I hear the word "data migration" I reckon I could do well.
Re: Eight Myths on Software Engineering and GenAI
#64|--------|-------|------|------|-------|------| |Contract|Product|Design|Coding|Testing|Deploy| Writing Code Isn't the Bottleneck, until writing code is the bottleneck, until it's not again.
Getting a usable PRD is often the bottleneck.
The real bottleneck is Omega Star getting their shit together. And I ain't joking.
Re: Eight Myths on Software Engineering and GenAI
#65I feel like all you need to know about how seriously to take this is that they cite that ancient early-2025 METR study, and describe it in the text as "recently one even found..."
Same thought - 80% through reading it occurred to me to check the citations. A few items from 2025 and most well before that. So much has changed since late 2025 one can’t really draw any conclusions from this. In fact, I’m guessing things will continue to move so fast that by the time one were to execute a survey of developers, many of the responses and findings are no longer relevant.
Your point really goes both ways, we really don't know anything about how LLM usage is affecting anything. No one knows, it's the wild wild west, which is whatever. But I think no one can really draw conclusions from what's happening in tech right now.
Reminds me of COVID and how everyone was fighting over early trends during that time.
Re: Eight Myths on Software Engineering and GenAI
#66Earlier quoted context omitted.
> I, as the human, still have to do the thinking as Claude still 'can't jump' I still have to do quite a bit of thinking but the amount of of thinking I do per task is trending down. I agree LLMs are not good at abduction but very few humans are either and very few jobs/tasks require it. I can't talk for researchers jobs though. But perhaps fewer researchers would be desired by these labs (not none).
> I still have to do quite a bit of thinking but the amount of of thinking I do per task is trending down Don't worry, I'm sure you'll hit your goal of zero thinking soon!
Trending towards the Homo Amens Mechanicus: the mechanical thoughtless human. What a goal
Re: Eight Myths on Software Engineering and GenAI
#67Earlier quoted context omitted.
> That meeting that you spent an hour in to understand the requirements? You don't need that meeting if you're not writing the code. How are you going to prompt the LLM or validate its output if you don't understand the requirements?
In some number of cases, the business partner who would have passed you the requirements will just generate the code themselves.. I’m shocked shin some engineers don’t see a massive disruption coming..
Oh, some of us see a massive disruption coming, just maybe not in the way you think.
Talented, experienced devs leaving the field out of disgust would be pretty disruptive.
Crumbling, faulty technical infrastructure with unmanageable heaps of AI slop that no one understands would definitely disrupt businesses.
Skill atrophy, and an entire generation of "developers" that have never actually written code will be disruptive when something breaks and no one knows how to fix it (this isn't a hypothetical, I'm seeing this phenomenon in a lot of large enterprise groups).
The total elimination of novel solutions, new ideas and new approaches to development and the resulting industry wide stagnation won't be disruptive, but will certainly be a drag.
Re: Eight Myths on Software Engineering and GenAI
#68> We already know developers don’t actually spend most of their time writing code, with studies at Microsoft and elsewhere showing it’s closer to 14 percent. Anyone else finding they're spending more time writing code (or at least driving agents to write code) now? 14% used to feel about right for me - I'd spend the rest of the time researching approaches and libraries, planning things out in issues, or sometimes jus…
You read my mind. I suspect it is a transient spike while I blow through the backlog and I'll run out of things that AI can vastly accelerate in, say, 6 months. But right now? I'm spending 80-90% of my time blasting through implementing features, finding bugs, fixing old bugs, writing and improving my tools... Code was never the majority of my job. But right now the bar to doing things is so low and the sheer joy of blasting through some previously tedious, low to medium hanging fruit is thrilling.
Re: Eight Myths on Software Engineering and GenAI
#69Earlier quoted context omitted.
How's this? https://simonwillison.net/2026/Jul/13/datasette-code-frequen... I have similar charts across my three main open source projects: https://github.com/simonw/datasette/graphs/code-frequency https://github.com/simonw/llm/graphs/code-frequency https://github.com/simonw/sqlite-utils/graphs/code-frequency
I don't think volume of code changed was the metric the other commenter was asking for.
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Re: Eight Myths on Software Engineering and GenAI
#70Earlier quoted context omitted.
> That meeting that you spent an hour in to understand the requirements? You don't need that meeting if you're not writing the code. How are you going to prompt the LLM or validate its output if you don't understand the requirements?
Your PM can write the ticket, and your QA can test the output.
I think we would, at some point realize that the roles of PM and QA are best done by an LLM, while coding is left to humans.
So an 180 from the current coding-automation frenzy..