2026-11-02 11:04 UTC
Replies (3)
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@lagrangeinterpolator@awful.systems 2026-11-02 14:50
Why has productivity not increased dramatically if everyone is using LLMs all the time already? Honestly, the manifesto should have stopped here. They admitted defeat right out of the gate. But the manifesto must continue, because the LLM cannot fail, it can only be failed. I wonder if this report is starting to get under their skin. The first is a change in engineering culture and engineer mentality. Your job has fundamentally changed. It is no longer to write code, and LLMs are not here to help you write better code faster. Your job is to help the LLM write better code faster. This is not even a meaningful distinction. If I use an IDE command to change the name of a method everywhere its used, did I change all the names or did the IDE change all the names? What difference does it make? I can only see this as them ordering engineers to use the AI more and go faster. The manifesto talks a good game about how “expertise” and “good engineering practices” are not dying, but telling engineers to offload more of their work to AI has the unavoidable tradeoff of making these things worse. As a side question, how is it that all of these fuckers always want to use the precious gift of AI to go faster, not to, say, give their engineers more time to improve the quality of their software? Almost like they don’t actually give a shit about good engineering practices! The second reason we have not been able to take full advantage of the AI revolution is that we have been almost completely stuck at phase 1 — using LLMs to speed up tasks as part of existing workflows. But writing code is not the only part of the software development lifecycle, and what happens when you eliminate a bottleneck? Another takes it is place. At least they’re realizing that maybe one of the anti-AI talking points has some merit to it. But they don’t seem to realize why they need stuff like code review and CI/CD: the AI is unreliable and these processes are needed to reduce the probability of a major fuckup reaching production. All they think is, hey, more opportunities to use AI! The third reason is a collective action problem. Using LLMs effectively to write code is something an individual engineer can do for themselves… But to retool the company at large requires amounts of both organization and resourcing that we simply have not invested in yet. What do I even say to this? Once again the problem is that there isn’t enough AI, and the solution is to buy more AI. We’re gonna buy so much more AI that we’re retooling the entire company and shoving it up every bodily orifice.
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@Soyweiser@awful.systems 2026-11-02 18:06
If you know there are always new bottlenecks tha keep slowing things down why try at all? When do you go ‘wow none of this helped and we wasted a lot of energy on spinning our wheels’ (Or perhaps you dont know what the actual bottlenecks are, a manager should know better).
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@YourNetworkIsHaunted@awful.systems 2026-11-03 04:16
It’s always vague talk about how they need to rearchitect their workflows to better integrate blah blah blah. There’s never a specific model they want to move to or a specific plan or even a single detail about what this should look like other than “more LLMs!” I propose the reason for this is that we’ve already seen what this kind of model looks like with Gas Town or whatever he’s calling it now and it’s both blatantly stupid and incredibly expensive so any CTO who honestly tried to move a real company towards that model would laughed out of the room or sued for breach of fiduciary sugy.