81–90 of 124 posts
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they have, loudly and repeatedly, it doesn't really make it very far on HN for obvious reasons.
Not sure it’s obvious reasons, but understandable , sure. When someone questions your credentials the default is to tell them to jump, whether that’s a good idea or not.
I'm a hands on engineering leader for a team of about 20 engineers and I've been spending the past 6 months trying to get my team to understand just this. On Friday we had a coffee hour to share how we've been working recently and they all seemed perplexed at the workflows I've been adopting. It seems natural to me as someone who's been a manager for some time now, but very alien to all those who've never gone down t…
Can you share some details of the workflows that work for you?
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The joke at my school was when the engineering students failed (mech, EE, civ) out, they went into business, when they failed out of business they went into software engineering.
And what happened when they failed out of "software engineering"?
That’s because most Software Engineers aren’t Engineers, they’re computer science majors. It’s a completely different discipline.
Relatedly, I fully expect the software business to fail to learn from (nearly) literally every other industry how to operate when your marginal costs are no longer zero. It drives me nuts the number of people in software who think that people in other industries are slow because they’re just not as smart as us, rather than because when it takes months to get a cast part made, it better be right the first time.
> It drives me nuts the number of people in software who think that people in other industries are slow because they’re just not as smart as us. . . Ha! I studied computer science and became a programmer because I knew I was too dumb for med. school and the other engineering paths.
The central point, that working with agents is some tried and true variation of existing processes, is incorrect. Managing agents has some similarities with EM and program management but a whole lot of other dimensions like token use, avoiding drift, successful concurrency at scale, variations in prompting, testing, evaluation, etc., not to mention that the agents are hyperintelligent coders with zero common sense an…
That’s why predicting the future is really really hard.
There’s a good list of reasons why we do this, but it leaves out the biggest one, at least for me: building stuff is fun. Reinventing stuff is fun. It’s the most natural hammer to reach for whenever I encounter a nail. Not necessarily the best, but such is life.
Lawyers are informed by ancient case law and bankers leverage trade instruments with roots in medieval Italy. Why is the software profession so exceptional that replacing hundreds of years of engineering wisdom with blog posts on agentic workflows is considered best practice?
But the article has a big irony: the article accuses engineers of oversimplifying other disciplines and then does exactly that itself.
> "Data science was statistics with a cooler name"
The author mentions David Donoho's "50 Years of Data Science" but that work presents a much more complicated concept of data science: one with data exploration, transformation, computing, visualization, modeling, etc. Even the study of data-analysis practice itself.
Look at that XKCD he posted with it.
Horn took a nuance argument and converted it into the "human slop" formula mocked in the XKCD:
complicated subject = simple thing I already understand is really just
The cartoon is criticizing the same operation the article is doing. Maybe that is the joke?