Summarizer

I have nearly two decades of programming experience which is mostly server side. The other day I wanted a quick desktop (Linux) program to chat with an LLM. Found out about Viciane launcher, then chalked out an extension in react (which I have never used) to chat with an LLM using OpenAI compatible API. Antigravity wrote a bare minimum working extension in a single prompt. I didn't even need to research how to write an extension for an app released only three to five months ago. I then used AI assistance to add more features and polish the UI. This was a fun weekend but I would have procrastinated forever without a coding agent.

> You don't need to carve out 2-4 hours to ramp up any more. Yes. That used to require difficult decision making: “Can I do this and how long will it take?” was a significant cognitive load and source of stress. This was especially true when it became clear something was going to take days not hours, having expended a lot of effort already. Even more frustrating was having to implement hacks due to time constraints when I knew a couple more hours would obviate that need. Now I know within a couple of minutes if something is feasible or not and decision fatigue is much lower.

10x probably means “substantial gain”. There is no universal unit of gain. However if the difference is between doing a project vs not doing is, then the gain is much more than 10x.

From one personal project, Last month: 128 files changed, 39663 insertions(+), 4439 deletions(-) Range: 8eb4f6a..HEAD Non-merge commits: 174 Date range (non-merge): 2025-12-04 → 2026-01-04 (UTC) Active days (non-merge): 30 Last 7 days: 59 files changed, 19412 insertions(+), 857 deletions(-) Range: c8df64e..HEAD Non-merge commits: 67 Date range (non-merge): 2025-12-28 → 2026-01-04 (UTC) Active days (non-merge): 8 This has a lot of non-trivial stuff in it. In fact, I'm just about done with all of the difficult features that had built up over the past couple years.

Numbers don't matter if it makes you "feel" more productive. I've started and finished way more small projects i was too lazy to start without AI. So infinitely more productive? Though I've definitely wasted some time not liking what AI generated and started a new chat.

I think it depends what you are doing. I’ve had Claude right the front end of a rust/react app and it was 10x if not x (because I just wouldn’t have attempted it). I’ve also had it write the documentation for a low level crate - work that needs to be done for the crate to be used effectively - but which I would have half-arsed because who like writing documentation? Recently I’ve been using it to write some async rust and it just shits the bed. It regularly codes the select! drop issue or otherwise completely fails to handle waiting on multiple things. My prompts have gotten quite sweary lately. It is probably 1x or worse. However, I am going to try formulating a pattern with examples to stuff in its context and we’ll see. I view the situation as a problem to be overcome, not an insurmountable failure. There may be places where an AI just can’t get it right: I wouldn’t trust it to write the clever bit tricks I’m doing elsewhere. But even there, it writes (most of) the tests and the docs. On the whole, I’m having far more fun with AI, and I am at least 2x as productive, on average. Consider that you might be stuck in a local (very bad) maximum. They certainly exist, as I’ve discovered. Try some side projects, something that has lots of existing examples in the training set. If you wanted to start a Formula 1 team, you’re going to need to know how to design a car, but there’s also a shit ton of logistics - like getting the car to the track - that an AI could just handle for you. Find boring but vital work the AI can do because, in my experience, that’s 90% of the work.

> But I would steer away from starting them. I find just the opposite. Before, starting from nothing was a huge impediment. Now you can have a working prototype and start iterating right away. If you figur e out that you've gone down the wrong path, there's little remorse in tossing it out and starting over.

As someone that only has sporadic pockets of deep time in my free time the thing that has been immensely helpful from an LLM coding point of view is mental model building. I can now much more easily get "into the flow" after being away from a codebase for a period of time by asking questions. For example, remind me where all the integration points for that API route is located. Or give me a rundown on this file. Etc.. It gets me back up to speed so much more quickly and makes me productive with limited amounts of time. It also means I don't have to try to carry this context around with me or I'll forget it.

This is exactly how I feel about it. The cognitive load of starting a new project is so small now. It's also made it very easy to switch between projects, something that took way too much headspace to do on a whim in the before times.

I have this suspicion that the people who say they have 10x productivity gains from AI might largely see improvements from a workflow change which fixes their executive dysfunction. Back in the day I never had any issue just sitting down and coding something out for 4 hours straight. So I don’t think LLMs feel quite as big for me. But I can see the feeling of offloading effort to a computer when you have trouble getting started on a sub-task being a good trick to keep your brain engaged. I’ve personally seen LLMs be huge time savers on specific bugs, for writing tests, and writing boilerplate code. They’re huge for working in new frameworks that roughly map to one you already know. But for the nitty gritty that ends up being most of the work on a mature product where all of the easy stuff is already done they don’t provide as big of a multiplier.

LLMs as a body double for executive dysfunction is a great insight. I see chronic examples of corporate-sponsored executive dysfunction: striped calendars, constant pings and interruptions, emergency busywork, fire drills. It's likely that LLMs aren't creating productivity as much as they're removing starting inhibition and helping to maintain the thread through context switching. What's presented as a magical tool, which LLMs can be in the areas you mentioned, is also presented as a panacea for situations that simply don't promote good programming hygiene.

Laziness, or job search, or parenting, or health issues, or caregiving, or something else. It's not a binary stay-current-or-you're-lazy situation, it's that the entire industry is moving to shorter timelines, smaller teams, and more technical complexity for web projects simultaneously. LLMs are a huge dopamine hit for short term gains when you're spinning plates day after day. The question is what the ecosystem will look like when everybody's been using LLMs as a stopgap for an extended period of time.

I remember when Hacker News felt smaller. Threads were shorter. Context fit in your head. You could read the linked article, skim the comments, and jump in without feeling like you’d missed a prerequisite course. It probably didn’t feel special at the time, but looking back, it was simpler. The entire conversation space was manageable. If you had a thought, you could express it clearly, hit “reply,” and reasonably expect to be understood. As a single commenter, you could hold the whole discussion in your mind. From article to argument to conclusion. Or at least, it felt that way. I’m probably romanticizing it—but you know what I mean. Now, articles are denser. Domains are deeper. Threads splinter instantly. Someone cites a paper, someone else links a counter-paper, a third person references a decades-old mailing list post, and suddenly the discussion assumes years of background you may or may not have. You’re expected to know the state of the art, the historical context, the common rebuttals, the terminology, and the unwritten norms—while also being concise, charitable, and original. Every field has matured—probably for the better—but it demands deeper domain knowledge just to participate without embarrassing yourself. Over time, I found myself backing out of threads I was genuinely interested in, not because I had nothing to say, but because the cognitive load felt too high. As a solo thinker, it became harder to keep up. > AI has entered the chat. They’re far from perfect, but tools like Claude and ChatGPT gave me something I hadn’t felt in a long time: _leverage_. I can now quickly: - Summarize long articles - Recall prior art - Check whether a take is naïve or already debunked - Clarify my own thinking before posting Suddenly, the background complexity matters a lot less. I can go from “half-formed intuition” to “coherent comment” in minutes instead of abandoning the tab entirely. I can re-enter conversations I would’ve previously skipped. > Oh no, you’re outsourcing thinking—bet it’s all slop! Over the years, I’ve read thousands of great HN comments. Thoughtful ones. Careful ones. People who knew when to hedge, when to cite, when to shut up. That pattern is in my head now. With AI, I can lean on that experience. I can sanity-check tone. I can ask, “Is this fair?” or “What am I missing?” I can stress-test an argument before I inflict it on strangers. When AI suggests something wrong, I know it’s wrong. When it’s good, I recognize why. Iteration is fast. Even with back-and-forth refinement, I’m dramatically more effective at expressing what I already think. The goal hasn’t changed: contribute something useful to the discussion. The bar is still high. But now I have a ladder instead of a sheer wall. There’s mental space for curiosity again. My head isn’t constantly overloaded with “did I miss context?”, “is this a known bad take?”, or “will this derail into pedantry?” I can offload that checking to AI and focus on the _idea_. That leaves room to explore. To ask better questions. To write comments that connect ideas instead of defensively hedging every sentence. To participate for the joy of thinking in public again. It was never about typing comments fast, or winning arguments. It was about engaging with interesting people on interesting problems. Writing was just the interface. And with today’s tools, that interface is finally lighter again. AI really has made commenting on Hacker News fun again.

I agree with this. I've been able to tackle projects I've been wanting to for ages with LLMs because they let me focus on abstractions first and get over the friction of starting the project. Once I get my footing, I can use them to generate more and more specialized code and ultimately get to a place where the code is good.