LLMs evaporated 90% of the "moments of despair" when you have an error and googling it isn't helping, or googling it made you realize you have to read 30min of documentation.
Coding is a joy now. LLMs shaved off all the rough edges.
A year ago I would've told my boss “can't be done” about my work today. I'd tell him to get me the right person to talk to (our partner, not an alien) who could give me some insight into what the hell I'm supposed to be doing to consume their API. Or to at least explain why it is that this can't be done.
Nowadays, I spent a couple of weeks reverse engineering their terrible ideas. Yeah, it worked. But it's a complete waste of my time, and tokens, energy, chips and RAM. And worst of all, it will lead to a terrible design.
That will work, but will eventually colapse under its own weight, as we use our increased power to increase our sloppiness and take it a little further. Because we can manage it. For now.
It's getting hard to keep up with trying to teach new devs what bad code looks like. And I swear sometimes they just copy my PR comments into their AI tool to fix the mistakes without any of the learning.
How have you set yours up that works well for you?
Take the bad result that you're getting, and pretend it's coming from an enthusiastic junior. What would you tell them to make them do this task better? Add that explanation to the agent (or explain that to the LLM and get it to add that to the agent, I have found this to work as well).
When you create a task for the LLM, get it to create a requirements document that lists all the requirements. Feed that into the review agent so it understands what the code agent was trying to do.
The LLM will do what you tell it to do. It doesn't magically understand what you want it to do. You have to tell it what to do.
I am terrified of allowing these things to complete tasks end-to-end with nothing intervening. Maybe that's why I don't run into many of these issues. I mostly delegate grunt work and manual tedium, not reasoning or design choices to the LLM. I may consult the LLM and ask for criticism, but there is no way I'm going to allow it to quietly make design decisions that I don't know about.
I use LLMs in the following ways:
1. Copy-pasting code into the web chat UI and asking for something (bugfix, add a feature, refactor, explain, review it etc), including entire source code files. A $20/mo Gemini subscription goes a long way (never been rate-limited). I only use the highest model. I often just copy-paste the entire source file between 3 backticks.
2. Cursor Tab. I do have hotkeys to enable and disable it; it's disabled most of the time otherwise it gets annoying.
3. Single-file changes directly from Cursor's AI sidebar. I only do this for simple, predictable stuff because even their auto-routing "Premium" setting is not as good as pasting stuff into Gemini 3.1 Pro.
That means I have only two $20/mo subscriptions: Gemini and Cursor.
I don't use Claude Code, it's really for people who don't know how to code. I don't use Plan Mode; I make and track the plan myself (if at all). I only tell the LLM granular tasks to execute. I don't use `claude.md` or `agents.md` or anything like that. If I don't like a particular output, I reset everything, modify my prompt and try again.
I believe this is the only way to fully leverage LLMs without losing any product quality. If you're trading off quality for "speed" (in quotes because over the long term, a low quality codebase is a massive drag on productivity) then there's no point.
Is that accurate?
What counts as “works” is the important bit, I think.
The LLM will do what you tell it to do. Manage it.
And then condensed an equal quantity of despair out of the ether via confident confabulations.
I don't miss wasting an hour on a problem in a technology I'm not familiar with, where it's not like a big conceptual thing but something I could clear up in 5 seconds if I just had an expert in the room.
It writes the code for you. Then it runs the tests. Then it runs the linter. Then it runs the static analysis tool. If any of those fail, then it rewrites the code and runs them all again.
You only look at the code once it has done all of that.
If AI is ignoring the rest of the document and doing whatever it wants then you need to improve your document-writing skills. You can ask it why it did something, that helps discover how to improve. It's a process of refinement and discovery, just like learning how to use any new tool.
I use AI in two ways. In the way you describe, and also in the text editor as AI autocomplete. It works great until it doesn't. It inserts typos all the fucking time.
Also, don't assume you know it all.