kaydub

Companies are putting a ton of effort into getting to that point of having agents do the work unsupervised. Whoever gets there first is going to be the winner.

I personally don't think it's possible and I haven't written a line of code since Sept 2025.

There's an AI psychosis going on right now, especially among the execs or management class, and we all gotta nod our heads in agreement and burn through tokens.

I don't think most people care where their electricity comes from, just the price.

I've only had an EV 3 months now, but it'll never see a charging station.

I pay around $.12/kw and get 4 miles per kw. So my "energy" costs are $.03/mile. I have a Mazda cx50 as well, it gets about 20-22mpg, with the gas prices here in Seattle that's around $.30/mile. Even where gas is cheaper that's still $.20/mile. Literally 10x the cost to run a gas car vs an EV.

I'm honestly shocked at how many people have EVs and rely on charging stations. I mean, I think it's a low number, but the fact that it's more than zero is shocking to me.

I started this blog post, like a lot of my posts by stream of thought writing about a few things I've been thinking about lately. This one started out about how I've been building pretty much everything myself and then it dawned on me, I've been doing this because there's no more decent middle ground.

For most things, you either buy cheap junk or you pay exorbitant prices for decent or high end quality. So I almost always opt to DIY so that I can get quality or exacting specifications without breaking the bank.

It's probably the result of our K shaped economic recovery as well as PE invading so much of our lives, but I was wondering if anybody else feels this way or is going down the path of DIYing more and more in their everyday life?

I'd honestly argue we're actually going the complete opposite direction.

Everybody is using LLMs/AI. All the time. It's in every facet of your life. Just because you didn't input the prompt, doesn't mean you're not consuming the end product of LLMs all day, everyday, on websites like this one, reddit, tiktok, instagram, facebook, etc.

Addressing the article, if you're hyperfocused on whether people are using AI and only consider AI use a chatbot... well, you're not honestly covering all the AI use out there. And reading the other stats, it seems like this article is trying to paint a narrative. Why is the Datos stat only considering "Desktop use" for instance.

Not to mention their stats are actually astounding and DON'T show what the headline is trying to assert. 1/3 of people using AI regularly is a FUCK TON of people in a VERY short span of time to uptake a new technology.

Got distracted and didn't touch on the godot specifics.

I start the project in godot, then I talk to an agent to define my game and give details. I tell it to have a conversation with the end goal to be building a CLAUDE/AGENTS/GEMINI markdown file for future agents to help build the game.

I made a [single player top down naval game](https://www.youtube.com/watch?v=FQUTbeQ8-oA) and an online multiplayer game (that I'd like to keep to myself for now).

I mostly used free assets for the artwork. I made some myself in aseprite. I utilized LLMs a tiny amount to generate some assets, but typically those are more of a jumping off point than game ready art assets. This has been what's slowed me down the most in making games.

I use any of the 3 big frontier models; claude, chatgpt, gemini

I only use the cli tools; claude code, codex, gemini cli (which is being phased out for antigravity cli soon)

I've generally had the best luck and enjoy working with claude the most, though that may be because that's the model we use at work (from aws bedrock, we pay per token and always have). Gemini and codex have flip flopped on 2nd place, though right now I'd lean Codex.

On my personal stuff I typically use codex or gemini because those two I have subscriptions, claude I still pay per token but through anthropic API like 90% of the time and 10% of the time through bedrock.

There's no false dichotomy. You're just choosing to miss the point to argue semantics.

They have definitely built some of it in.

And yes, right now you still need the architectural and system design knowledge because the LLM will fuck that up. We'll all find out if that continues being needed in the future. From what I understand about LLMs and how they work, I doubt it, but also, yeah, I doubted it would've gotten this far when I think back 2+ years ago.

Also, maybe I should be clear, I pretty much never one-shot things. My sessions with claude or other cli tools always starts with a bit of a conversation until we converge on a good plan, claude builds the code, we discuss some more, then we iterate.

Not sure what I'm going to link to in my professional life, it's all private repos. We have a large microservice architecture in AWS. We've made major changes and the LLMs have helped every step of the way. Migrated our whole auth system from being regional, resulting in customers being limited to specific regions or managing their multiple accounts across regions, to a global authentication with data residency built into accounts so that they login to what looks like a global app now. No more uk.example.com, eu.example.com, ca.example.com and us.example.com. It's now just example.com, but data residency (and currently data processing too, but that's another thing we're working on) stays the same. This isn't some small app, this is the main product at a company with nearly a Billion in ARR.

For personal projects, only one thing could I actually show - vaicayo.com

This app was originally started pre-llm. I just wanted a centralized place for my wife and I to organize our vacations. I built out the basic crud for that a long time ago and we used it, but then llms got popular. I first integrated it into the app, now I could get it to generate vacation plans completely with the llm. It did okay.

Somewhere between 3-6 months after building out llm features claude code released or I became aware of it enough to start using it.

I rebuilt the whole thing. So what was once a spring boot app running in AWS ECS with alb + cloudfront (and yeah, some sqs+lambda python processes, s3 buckets for storage, aurora rds for db) is now a super lean apigw + lambda + dynamodb stack with a svelte frontend. I went from paying $20ish a month to $0. I also built a flutter app for android and ios that utilizes the same backend as the frontend webapp with feature parity. It's not really a production app, but it could handle it fine, it's completely cloud native and hands off to operate. And let me be clear about the rebuild, it's not a 1 for 1, I think all that I kept was the domain model.

For features, it's mostly just a crud app. You plan your vacation in it. Outside of that there's the ability to take pictures with the phone app that auto-sync (there's a bit of complexity here, the phone app only syncs pics when it's on wifi unless you change settings to allow syncing on cell network, images are cached locally with a ttl, uploads will run in the background and queue up, uploaded images automatically resize/compress and generate thumbnails from an s3 event lambda). The other more complex item is email ingestion, when I get a reservation email I forward it to the app and it automatically processes it (the only place I use an LLM in the app right now). If it can't discern what the email is or which vacation it goes to it goes in a travel inbox so the user can route it to the right vacation and object type. Oh I guess the paywall is a little complex. I don't advertise this thing but I have left user registration open if anybody ever wanted to use it. I did lock the email parsing behind a paywall and I limit photo uploads for free accounts.

So frontend, backend apis, flutter app for android and ios all built 100% by llm.

For code quality, the frontend is okay, the backend is pretty clean but could use some things split out into domains, and the flutter app has some work to do (recently found a couple code smells). But there's no issues adding features, shipping, etc. I literally finished adding some of the photo syncing features in the flutter app last night.

Other than that, I have created 5+ other personal projects that I wouldn't have without an LLM. I've made 2 godot games, a private scribbl.io clone with a few extra features that myself and my coworrkers play as a "happy hour" on fridays, tons of ci/cd build stuff and terraform (using my own personal modules, so I guess that's not 100% llm coded if you consider the modules), and then a couple other simple apps.

This isn't about distinction between literal titles. But continue missing the point.

Knowing what you're doing holistically is the chasm.

I mean, go look at the author's linkedin and github. They're a "dev" with 20 years of 1 year of experience. Not a software "engineer"

There's a big difference between the two and LLMs are increasing the chasm. The Software devs are crying out because the LLMs can already do their full job. Software engineers are happy because the LLMs are removing a large chunk of the job that's low value.

Software dev using an LLM is gonna produce "slop"

Software engineer using an LLM is going to have an increase in productivity depending on how they're using the LLM tools.

You're just witnessing "Software Developers" cry out over LLMs.

"Software Engineers" are embracing LLMs and getting shit done same as before.

This is a guy who has 20 years of 1 year of experience. His blog includes his linkedin and github, just give it a look over.

Funny, the element of ego I'm seeing are the devs that can't accept that LLMs write perfectly good code at a faster pace. It's always "slop" this or "vibe coded" that. Meanwhile I've personally shipped multiple apps and professionally we've done HUGE things in these past 6 months using LLM tools.

Just look at the author's accolades. They are very light.

I've never heard of this guy. He's "self employed"

The article lacks any real detail and it just a guy patting himself on the back.

There's always oversight, that's just something you wrongly assumed.

I accept that for every prompt of building I'm going to have 1-5 prompts of refinement.

Once the LLM tells me "Okay, it's done, everything works" I always as it to do a thorough review, I tell it to split up the work among sub-agents with each one taking on a specific responsibility (look for code smells, look for bad architecture, review the data access model, DUPLICATE CODE, testability and unit testing, etc.)

After a certain number of revisions and reviews you'll come to accept the shortcomings it comes back. Usually there will be specific design decisions you made that the LLM keeps bringing up, once the review only brings that up and maybe some other minor issues it's time to move on.

I don't overly rely on markdown files and directions. I don't rely on tooling around it either. I just don't trust the LLM when it says "all done", tests pass, and deployment works. I make it to multiple reviews and iterations even when it thinks it's done.

Yeah, v1 is sloppy, then I tell the LLM to clean it up. Every 1 prompt of building tends to require 1-5 prompts of clean up. Simple, fast, clean good code.

The chasm between "Software Developer" and "Software Engineer" is getting wider. Articles like this and the comments under it give away who is an Engineer and who is just a coder.

This is such a low value article lol

I'm not even sure what it's trying to say. It's just someone patting themselves on the back.

I've been in software for about 15 years now, so long before LLMs. But now, I won't write code without them.

When I go out to eat, I'd love to know what people's favorite dishes are so that I know what to try. This plugin I made is specifically for that. This is just a small hobby project, but I thought I'd share some details and how I built it in this modern LLM age of building software.

And although I may not write code without LLMs these days, I do (currently) write all the blog posts and create all the content myself.

My anecdotal experience isn't a benchmark. Just because I feel like something is better or different doesn't mean it actually is.

I just don't believe non-deterministic tools can actually be benchmarked. It's all hoopla to me.

I flip between models all the time. Makes little difference. Sometimes one model is faster or better than another but there's no rhyme or reason why.

I've always interchangeably used the models.

I don't look at benchmarks.

It's a non-deterministic tool. A lot of the shit going on with LLMs just doesn't make sense to me. All the tooling around like MCPs, they're all just putting stuff into context. So to me the tools aren't really robust and they make little difference.

Lots of AI psychosis going on these days. And I say that as somebody that hasn't written a line of code since Sept 2025

I'm surprised at how many businesses are using subscriptions instead of paying per token.

So you think your bespoke solution is less complex?

Custom scalers? Running prometheus, grafana, etc?

Lambda IS super simple.

These people are professional amateurs. They don't know what they don't know so they post stupid posts like this and all the other know-nothings upvote it and comment likewise.

Seriously, there's nowhere online for good software engineering discussion.

Yup!

I've been holding Hacker News in too high of esteem for too long I think. Most people on here are amateurs at best. The complaints about AWS/Cloud and LLMs are getting too loud. Did the industry pull in too many inexperienced during covid and now we're witnessing the backlash or something?

I've been doing this a long time. Running hardware, running VPS in the cloud, and running on AWS. I'll never go back to hardware/on-prem.

I honestly can't believe most of the people posting aren't engineers or they work at small companies or something. They show their lack of experience when talking about how cheap Hetzner and DO are.