I find that most of the time, programming is just procrastination, and having the LLM there breaks through that procrastination and lets me focus on the idea I was thinking on without going into the weeds.
A lot of the time, the LLM outputs the code, I test my idea, and realize I really don't care or the idea wasn't that great, and now I can move on to something else.
I hope at some point people don't feel the need to justify using or not using LLMs. If you feel like using them, use them. If you regret doing that, delete the code and write it yourself. And vice versa - if you are in a slog and an LLM can get you out, just use it.
You have to break down the problem into manageable chunks anyway, might as well feed those into a code agent while you write it yourself. If you don't like what it did explain what it did wrong. Shouldn't take long to figure out what parts are the biggest waste of time to write yourself. Do still have to hop tools and adjust your confidence as they improve.
So ok you don't get into the weeds and you're proud of that, but also nothing you can think of wanting to do turns out to be worth doing.
Those things are wholly related. Opportunity never comes exactly the time and the way you expect. You have to be open to it, you have to be seeking out new experiences and new ideas. You have to get into the weeds and try things without being entirely sure what the outcome might be, what insight you might gain, or when that insight might become useful.
A friend of mine has a hilarious method for breaking though procrastination. His one trick is to spend money on the task/project, buy all kinds of things to make the job easier. It has to be useful but it is more about paying the unlock fee.
Github is full of half forgotten saved games waiting for money to be thrown at them.
I'm now using an LLM to write a voice note organisation application that I have been dreaming about for two decades.
I did vibe code the first version. It runs, but it is utterly unmaintainable. I'm now rewriting it using the LLM as if it were a junior or outsourced programmer (not a developer, that remains my job) and I go over every line of application code. I love it, I'm pushing out decent quality code and very focused git commits. I write every commit message myself, no LLM there. But I don't even bother checking the LLM's unit and integration tests.
I would have never gotten to this stage of my dream project without AI tooling.
Not grandparent, but I'm in the same boat. I've been dreaming for almost 10 years of building a sort of digital bullet journal. I had some feeble attempts to start, but never got to the point where I could actually use it. Last year I started again, heavily LLM assisted. After 1-2 weeks (this was before agents), I had something usable, from which I could benefit, which wanted to make me improve it more, which made me want to use it more.
By now it's grown to 100k lines of code. I've not read all of them, but I do have a high level overview of the app, I've done several refactorings to keep it maintainable.
This would not have happened without AI agents. I don't have the time, period. With AI agents, I can kickoff a task while I'm going to the park with my kids. Instead of scrolling HN, I look every now and then to what the agent is doing.
So, it's a personal pet project, I've thrown in everything and the kitchen sink. There's a telegram integration so I can submit entries via telegram, there's a chatbot integration so that I can "talk to my entries" and ask questions about what I did when). It imports weather data, Garmin data, and so on.
So yes, it's around 100k lines of code (Python, HTML, JS and CSS).
> With AI agents, I can kickoff a task while I'm going to the park with my kids. Instead of scrolling HN, I look every now and then to what the agent is doing.
How does that work? Are you running the agents on a server? Are you using gnu screen and termux? Can you respond to prompts asking for permission to e.g. run ls or grep?
I have at least two projects that I estimated to take a week or two but aren't finished after years. There might be others that just got abandoned that should be included in the count.
Then there are things that work but aren't polished enough or should really have documentation.
I can’t (due to other priorities) give consistent time to a project unless it is very important. That lack of consistency means I have to spend time re-learning what I was thinking and doing which is both inefficient and not fun. Since the projects are either experimental or not that important, I’m generally more motivated to do something else.
Over time I’ve learned to not even start such projects, but LLMs have made it easier to complete such projects by making the work faster reducing the time variable in time over importance and easing the refamiliarization problem, adding to the set of such projects I’m willing to tackle.
lack of character, distracted by other things for to long, drowning in unforeseen complexity, much slower progression than expected, bored with it, force majeure, etc
A lot of the time, the LLM outputs the code, I test my idea, and realize I really don't care or the idea wasn't that great, and now I can move on to something else.