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I think saying “we are all product engineers” is not accurate, but this aligns with stuff I’ve been telling my teams for a while. Everyone needs to start becoming closer to product and moving away from programming as the thing they’re valued for. (e.g. I’m not valued because I know Java inheritance rules) To be honest, it always should have been this way (it’s how I’ve lived my career), but some organizations have created this weird “product does the thinking, engineering does the programming” dichotomy and it’s in those situations where this argument makes sense. At a small startup where every new hire understands the business problem and works to achieve that goal is not where this argument makes sense.
My first job was “Analyst/Programmer I” - somewhere along the line it turned into “Programmer” and then “Software Engineer” – pushing the role farther into a technical silo and farther away from the product “because the product managers know best and the nerds need to make it happen by next quarter /s”. The success of individuals on the product side are going to be with folks who can shift to leverage AI for technical chops, and vice versa for Engineers shifting to put on their “Product Hat” more often. With any career, there’s going to be a spectrum of what skills fit into the role (e.g. some positions may be more or less technical or more or less business analyst), but I see the shift happening as a way to preserve ones career in an ever changing world. Those that do not adapt will find themselves on the outside looking in and wondering why (or as an alpaca farmer in northern Idaho because they noped out).
Dude seems to be high on AI propaganda and is completely ignoring that running any model has some cost. Sure, right now many companies are burning through tokens like wildfire, but that won’t last forever - it possibly won’t even last thru 2027 - so calling any part using AI “free” is just dumb, even for people who run models locally.
He mentions how frontier models, the most expensive ones, are doing the best job. Guess what, those are the ones that aren’t on huggingface and joe schmoe isn’t going to pay up for.
This is a really great point. AI tokens are expensive for quality today, and that will continue. We’re already seeing a bit of a plateau, and this whole “let’s slow down so we don’t kill ourselves” is propaganda, I think. AI companies that leverage “price to value” are going to succeed. I see Google Gemini fitting this mold long term, GLM, Kimi did fit this mold but their later models seem to jump in price pretty fast chasing Opus capability. If you take “capable models” as the standard for price to value and then charge what it actually costs (not VC subsidized), then you’re going to see a world where Software Engineers are probably back in high demand. I think the article points out the hard part: how do you grow new Sr. Engineers if you’re replacing Jr’s with Claude. (I think the obvious answer is that we shouldn’t be replacing Jr’s with Claude)
I think the author gestures at a pretty solid argument that most of the “mechanical” arguments for LLM capabilities have a clear trend line towards “can do thing”.
Strictly speaking, the job he’s describing even falls into that category, there’s just not a lot of training data for it.
Anecdotally this has matched what I’ve seen. Which is unfortunate because the part of tech I like the least, regarding software development, is when the thing that was built was actually used for anything.
I got into this specifically, and exclusively, for the craft. I don’t like making other’s lives " better", I don’t like “solving problems”, I don’t like the customer. But here we are staring down the barrel of a career making “products”.
As a software developer I’ve always been a product engineer as well. AI tools did not change that for me.
Coding, reviewing, and ops is certainly not gone nor disappearing fast for me.
