alt Hacker NewsIf it’s not trivial, it’s worthless, because writing things out manually yourself is usually trivial, but tedious.
With LLMs, the point is to eliminate tedious work in a trivial way. If it’s tedious to get an LLM to do tedious work, you have not accomplished anything.
If the work is not trivial enough for you to do yourself, then using an LLM will probably be a disaster, as you will not be able to judge the final output yourself without spending nearly the same amount of time it takes for you to develop the code on your own. So again, nothing is gained, only the illusion of gain.
The reason people think they are more productive using LLMs to tackle non-trivial problems is because LLMs are pretty good at producing “office theatre”. You look like you’re busy more often because you are in a tight feedback loop of prompting and reading LLM output, vs staring off into space thinking deeply about a problem and occasionally scribbling or typing something out.
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So, I'd like you to talk to a fair number of emacs and vim users. They have spent hours and hours learning their tools, tweaking their configurations, and learning efficiencies. They adapt their tool to them and themselves to the tool.
We are learning that this is not going to be magic. There are some cases where it shines. If I spend the time, I can put out prototypes that are magic and I can test with users in a fraction of the time. That doesn't mean I can use that for production.
I can try three or four things during a meeting where I am generally paying attention, and look afterwards to see if it's pursuing.
I can have it work through drudgery if I provide it an example. I can have it propose a solution to a problem that is escaping me, and I can use it as a conversational partner for the best rubber duck I've ever seen.
But I'm adapting myself to the tool and I'm adapting the tool to me through learning how to prompt and how to develop guardrails.
Outside of coding, I can write chicken scratch and provide an example of what I want, and have it write a proposal for a PRD. I can have it break down a task, generate a list of proposed tickets, and after I've went through them have it generate them in jira (or anything else with an API). But the more I invest into learning how to use the tool, the less I have to clean up after.
Maybe one day in the future it will be better. However, the time invested into the tool means that 40 bucks of investment (20 into cursor, 20 into gpt) can add 10-15% boost in productivity. Putting 200 into claude might get you another 10% and it can get you 75% in greenfield and prototyping work. I bet that agency work can be sped up as much as 40% for that 200 bucks investment into claude.
That's a pretty good ROI.
And maybe some workloads can do even better. I haven't seen it yet but some people are further ahead than me.