| I fully agree with your sentiment, and it also drives me crazy sometimes. I wonder if the main problem was all the min maxing interview patterns that rewarded algorithm problem solvers back in the 2010's onwards. People applied for software engineering jobs because they wanted to play with tech, not because they wanted to solve product problems (which should have a direct correlation with revenue impact) Then you have the ego boosting blog post era, where everyone wanted to explain how they used Kafka and DDD and functional programming to solve a problem. If you start reading some of those posts, you'll understand that the actual underlying problem was actually not well understood (especially the big picture). This led the developer down a wild goose chase (willingly), where they end up spending tons of time burning through engineering time, which arguably could be better spent in understanding the domain. This is not the case for everyone, but the examples are few. It makes me wonder if the incentives are misaligned, and engineering contributing to revenue ends up not translating to hard cash, promos and bonuses. In this new AI era, you can see the craftsman style devs going full luddite mode, IMO due to what I've mentioned above. As a craftsman style dev myself. I can only set up the same async job queue pattern that many times. I'm actually enjoying the rubber ducking with the AI more and more. Mostly for digging into the domain and potential approaches for simplification (or even product refinement). |
Painful for me because I excel at architecture. My puzzle-solving skills are actually good too, but unfortunately, not under time constraints! Sometimes I feel like there's been an industry-wide conspiracy against the software architect archetype!
I remember since I first learned coding at a young age, I wanted to be a software architect and I was shocked to learn that this skill was rarely appreciated in the industry. I became convinced that the software developer role had become a kind of 'bullshit job' of sorts to meet the needs of the reserve bank's job-creation agenda.
I suppose the silver lining is that at least now LLMs have a bias towards puzzle-solving and so lead most codebases astray... This increases my value as a software architect or 'craftsman' in your words.
I think you make a good argument there. You can extrapolate it to almost every aspect of society. Since you go to school, everything has been geared towards measuring thinking speed... We've been using thinking speed as the definition of intelligence... You know who else besides high IQ individuals are good at thinking fast? LLMs!
It's kind of interesting and fitting though that the AI agents we invented have the same biases as the humans at the top of our organizations!
I feel like the whole "there is only one kind of intelligence" belief which was pervasive in big tech has been thoroughly debunked by now.