Show HN: Atari Missile Command Game Built Using AI Gemini 2.5 Pro

Yes and no. It's very impressive, in that it would take a human with no coding knowledge a very long time to learn how to write it. It's not impressive if you know the anatomy. But it's only as good as asking the "programmer" to make those stars in the background stop running around wildly, or make it scrolling, or something. Then what. Well geez, I have no idea how this works so I better ask the AI to do that for me?

It's not really that different from taking your 2022 car to a shop to adjust your camless engine, and assuming everything's fine, but not having a clue what they did to it or how to fix it if the engine explodes the next day. You can't even prove it had something to do with what the shop did, or if they actually did anything at all. They probably don't even know what they did.

It won't stall progress for clever people who actually want to figure things out and know what they're doing. But it will certainly produce lots more garbage.

That said, the game is impressive for something stitched together by an LLM.

AI is the bulldozer for building ever bigger piles of rocks, like the pyramids. Impressive in their way, but unsustainable.

You still need paradigmatic shifts in architecture to enable delivering scale and quality from a smaller amount of materials, and it has not made a dent there, yet.

Valid point about whether AI generating piles of JavaScript might lock us into outdated tools. Isn't what you're describing though a form of advanced prompting? The ideal tool could act as a layer that takes a prompt and builds exactly what's needed to deliver the outcome, without humans or AI wrestling with traditional code. This is similar to what OpenAI initially aimed for with function calling, where AI writes and executes code in a sandbox to fulfill a prompt but it was clunky so they shifted to structured tool calling. The reason we still need program code like JavaScript, rust, assembly, ... is that current computing architectures are built for it. That’s changing, though, with initiatives from NVIDIA and other startups exploring inference as the main computational primitive, which could reduce/remove the need for conventional programming.

In my experience, AI is quite good at picking up new tools and techniques. In the sense that the models only need to be provided some documentation for how the new tool or framework works to instantly start using that new framework

Gemini in particular is really good at this

> All in all, a prompt history would be really edicational if anyone thinks about doing something similar.

As we start to develop AI first programs, I believe we will need to start connecting LLM conversations to code, not only for educational purpose but for maintenance as well. I'm currently experimenting with what I call Block-UUIDs, and they are designed to make it easy to trace LLM generated code. You can see what I mean in the link below, which contains a simple hello world example.

https://app.gitsense.com/?chat=7d09a63f-d684-4e2c-97b2-71aa1...

Something worth noting is, you can't expect the LLM to properly generate a UUID. If you ask the LLM, it'll says it can, but I don't trust it to do it correctly all the time. Since I can't trust the LLM, I instruct the LLM to use a template string, which I can replace on the server side. I've also found LLMs will not always follow instructions and will generate UUID and how I handle this is, when the LLM stops streaming, I will validate and fix if needed, any invalid UUIDs.

How I see things playing out in the future is, we will alway link to LLM conversations which will give use the Block-UUIDs generated and by looking at the code, we can see what Block-UUID was used and how it came about.

Full Disclosure: This is my tool

I've experimented with making it more explicit in one project I'm working on where 99% of it is written by AI, but the chat logs from Roo Code are way too verbose. Ideally, I could export a version of the chat with my prompts and metadata about which lines were changed, then I could commit that with the rest of the changes. I have every chat associated with changes made solely with AI in a chat folder named similarly to the commit, but the chats themselves are just impossible to read, so I haven't committed any of them.

I think putting prompts into the commit log, mixed with manual edits, would be a great way to document the evolution of LLM assisted engineering.

I wonder if there is some tool support yet that supports that.

> but who cares to be fair

i.e. who cares when the LLM starts giving up when the file is too big and confusing?

i.e. who cares when the LLM introduces bugs / flaws it isn't away of?

Would a prompt history even be useful? This is all non-deterministic. the same prompt could result in wildy different code?

> All code in a single index.html file which might not be great for human coders but who cares to be fair.

AI won't cope well as that file gets larger, or best hope that experimental diff feature is working well. I find stuff really breaks if you don't refactor it down.

Yeah that sometimes happens as LLM model didn't like the generated JSON format for some reason.

I want to start from any star and make the whole route without lifting my finger.

Your post makes it sound like you wrote it yourself.

“I had a long flight today, so in the airport I coded something”

Gemini 2.5 has enormous context and has one-shotted 1500loc programs for me.

I've added security.txt now. I appreciate the heads-up.

Well if you play longer at higher levels, you will see you need that cash and upgrades as it gets harder

Currently it's coupled. But thanks to your question, will look at decoupling it at a later time :)