The conclusion also completely contradicts a previous point, which is that managing an LLM is not like managing a human. So the skills are, in contradiction to that LLM-ism of a conclusion, new. The author isn't using their people management skills, they're using new LLM-management skills. They think the two are similar, but didn't bother breaking down how they're the same vs where they contrast. It's just a lazy observation expanded out to a short essay that says nothing interesting.
At my startup, my team reached a headcount of ~30 and I had to design process to keep things moving. Getting a bunch of disparate parts in even a 100 person company to produce the artifacts needed to create software is a massive undertaking that doesn’t involve people management at all. The two responsibility can be completely divorced from each other if you want.
I never thought I’d be dusting off those skills again, but I’m now using them every day. It feels (a subjective term, which the author used as well) like when I was in “leadership”.
My head is in exactly the same place as coding - deep technical connection to the mental model of what is being built.
This isn’t leadership, it’s just communication. Suddenly realizing that real SWE is full of soft skills isn’t a novel epiphany.
Companies like Anthropic seem to understand that too. It's impressive how many CTOs and CEOs Anthropic have hired for individual contributor positions, which I think is because those leadership skills transfer surprisingly well to working with agents.
Of course, managing agents is massively easier than managing humans! You don't have to consider the agent's own desires, goals, opinions, or emotional state when telling them what to do. Humans have agency; agents (despite the name) do not.
The resulting decisions are fed into the coding loop with guardrails derived from those decisions. The agent one-shots features once it goes into the coding loop.
To go anywhere serious you have to lead people, but even the ones who should be leading people are heads down talking to the LLM
Pointless, stupid article. Digital garbage, as garbage as LLM slop. So many words to say nothing.
Just astounding we decided to put a DMV in our IDEs.
Anyone who's fallen in love with programming itself and doesn't see software production as a means to an end is not really likely to see things like this.
I see AI as an accelerator of implementing my own choices. I'm generally opposed to metaphors, designs or strategies which excessively anthropomorphize it; it seems completely wrong-headed and counterproductive.
They're different kinds of work, and both are interesting in their own way. But in the freelance market, LLMs have already become the baseline, so I have to use them whether I like it or not. There are both pros and cons.
It's good to be able to read code and understand its structure, but writing code and reading it to transform it into a different structure are different skills. There's definitely some decay in raw coding ability, though. So I use LLMs for professional coding and for tasks that I couldn't do before, while I keep hand-coding smaller things that feel manageable.
Honestly, I think most people who hate LLM coding actually hate being forced to use it under workplace pressure. And when LLM output looks bad, it's often because managers tend to be strict about their subordinates' work but lenient about their own. Once an LLM generates something, people tend to get attached to it and become more forgiving—since it feels like they made it.
It's tough that LLMs have made deadlines tighter. But these days, compared to the old days when I had to go through interviews and conversations to build a proposal, I actually find it more convenient that clients send me proposals written by LLMs. There are pros and cons to everything.