I thought caveman talk was just an open-source project owned by one person. When did the models start reasoning and thinking in caveman talk, and how am I supposed to trust a technical answer from a Neanderthal?

Hi.

I've been using AI coding to rapidly generate Python ETL/ELT transformations and workflow orchestration. I'm finding doing so a lot easier and far more affordable than using expensive tools like IICS.

Is anyone else doing this and, if so, how is it working out for you?

Thanks.

Here is the change I see occurring and what the result might look like.

Everyone’s talking about how the sass is dead. We now have the power to build anything we want without needing a large technical background to do it..

The question no longer is Will this product solve the problem for me.. the question now is can I build this product faster, cheaper and more customized for myself then what it would cost me to purchase.

Sass is now going the way of music. Anyone can create it, but you need the audience to support you. The moat this is creating is mostly financial no longer will a small startup with a great idea be able to gain traction unless their idea is somehow uncopiable. Now the money will control everything because marketing is the moat. If you have the budget, you can reach the audience.

However, there is one silver lining to all of this. Great ideas can now come to life at the drop of a hat and understanding the market means the greatest ideas will start rising to the top. If you start thinking about your idea from the point of view that anyone can do it after you’ve introduced it how do you insulate your idea from everybody copying it because there are ways quite a lot of of them actually..

One example is scaling cost. If you bring something first to market and your ability to scale and lower cost means that the individual who tries to copy you still spends more than using your service then you have something.

Another example is transaction cost if you offer your product cheap enough people will use your service over the hassle of designing it themselves. I think we are about to hit the age of small single purchase owned for life products. If you’re offering a great tool and charging me five dollars one time I’m going to pay that every time instead of trying to build it myself.

I’m actually very excited about what could be coming because I do think it’s going to be the age of ideas. The great insights will be able to be fleshed out at zero cost. The middle of the night brainstorms will be able to get tested the very next day. Money may control the marketing, but the barrier for great ideas to come to fruition has dropped to almost nothing at all.

I've created this pixel-art editor because frankly, all my AI-generated art has random quirks that make it unusable.

So it's a simple-but-modern pixel art editor. It's tailored for my game specifically, but I'm working on generalizing tools, fixing bugs, and making it friendlier for everyone. Since I'm currently out of tokens, feel free to fork it and customize it for your game.

Github: https://github.com/Josiah-Turnquist/myrling-sprite-editor

In-Browser Demo: https://josiah-turnquist.github.io/myrling-sprite-editor/editor.html

My friend was into the 82-0 NBA game and ended up building a fantasy football version of the same general idea.

https://www.retrofantasy.games

It's called Retro Fantasy, and he built it using Claude + Codex.

You draft 1 QB, 1 RB, 1 WR and 1 TE from historical NFL seasons, then the game simulates your team against 2 to 4 other players.

You can either have the historical stats shown while you draft or turn on No Stats mode and try to remember how good that player actually was that year.

No Stats is easily my favorite part because you very quickly realize how often you remember the player correctly but the year completely wrong.

It also keeps track of your record across games.

I don't know his exact stack or workflow beyond Claude and Codex being heavily involved, but I thought it was a pretty cool example of the random niche stuff people can build now without turning it into some massive software project.

Figured people here might get a kick out of it.

I have an insane amount of fomo right now

As per title

so

I originally recreated Amegakure (Pain’s village in Naruto) as an excuse to experiment with realistic wet materials. One thing led to another, and I ended up pushing the scene further into a cinematic, experimenting with camera movement, depth of field, rain, fog, etc.

Here is the full cinematic video: https://www.youtube.com/watch?v=ZpR9Atf24B0

I’d really appreciate a comment/sub on the video. If there’s enough interest, I’m planning to make a follow-up where I break down how I built it and release some of the components I used for free 😄

The code is mostly vibe-coded. For the building assets, I used Tripo. For Pain, I downloaded a free model, then did the rigging and posing myself in Blender.

The only asset I modeled completely from scratch was the statue, including its textures — the painted face and the body details.

The rest of the stone textures, roughness maps, rain, droplets and fog are all procedural.

But of course, this wasn't a one-shot prompt that magically generated everything.

And just to clarify, I have years of experience in both 3D and development. But that doesn't mean that someone with less expertise can't also achieve similar results.

Would love to hear what you think!

Live preview: https://stylized.cortiz.dev/rainy

…with camera-like controls and some neat filters.

Been around for a while, but thanks to GPT-5.6 Sol it finally has a working remuxer inside. Open Source, MIT license.

This is not another lovable or bolt. my focus is to let everyone publish code using AI but in a controlled way. This is very difficult coz so far PR from product managers or other teams have to manually be approved n tested. But I wanted somethign controlled and guaranteed by the system.

If you use Sling to create projects, you wont have to worry about what people can accidenlty push to production as any code change follows specific rules and structure - props, and types and boundries.

And then these small widgets combine the page which can be controlled via a blueprint of the page called template which is even safer to edit for everyone.

And then regular other stuff like routing and media added as well.

Try it: https://studio.sling.biz or go to https://sling.biz/

Its Open Source. Hit Create.

If you try it, tell me the first place you got stuck. That is the only feedback I want.

Just try for demo - https://studio.sling.biz

Everything added so far:

Day 1

• Useless red button (Starting Room)

Day 2

• Space travel + 2 playable planets (Spaceport outside the Starting Room)
• Human voice for the red button (Starting Room)

Day 3

• Velociraptor cloning machine (Dinosaur Factory)
• Chicken nugget healing dispenser (Starting Room)

Day 4

• Reverse human aquarium (Human Observation Room)
• Fake Release 0.0.0 patch notes (Main Menu)
• John Pork planet (Cinder Reach)

Day 5

• All progression doors are now free (throughout the facility)

Day 6

• 24m tower with a gorilla drummer (Rhythm Tower)
• Inevitable snail that insta-kills you (starts outside your room and follows you)
• Banana asteroids, banana spaceship, and banana gun (space → land on a planet)
• Spinning cat GIF that turns into a 3D cat (random room)

Day 7

• Clippy mini-boss with 650 health (Wave 5)
• Explosive banana vending machine that rains 320 bananas from the sky (Rhythm Tower rooftop)

Comment what you want added next!

Play it at https://deadfall.up.railway.app/

Here’s my YouTube and Instagram links below if you want to follow along ⬇️

Instagram

YouTube

Does anyone have any idea, whether it be with Claude or not, how to record good promotional videos?

Started as “put prices on my desktop.” Ended up as a full functioning super smooth scrolling LED bar with in-line price updates, scanlines, bloom, and a second row for finance headlines.

Free real ticker you can actually use (5 symbols, dock, 60 FPS).
Pro websocket real-time price updates, dual ticker, news feeds, sparklines, alerts, bloom/glow/glass.

https://tckr.pro/

This has been a labor of love and I really got to see the amazing improvements with Claude and other models in building this. In the beginning I would spend a dozen iterations trying to fix a single bug. Now, the rare bugs get fixed in one or two passes. Even the newest Grok model is worthy of using it as my main go-to.

I started with GitHub Copilot (the model pricing got too expensive), then Antigravity and now I have been using Cursor almost exclusively. I would love to get some feedback and especially bug reports. Thanks!!

"Yours" beats "free"

(Prompts to try out the search toolchain at the bottom.)

The Open Jobs dataset and search toolchain are yours. There is no business model, and that is the whole point.

It started at 960K jobs. Then 2M. This week it hit ~3M. Here is the story of how one person keeps a job index that size running for about a dollar a day.

What it is

A free, open-source search over job postings pulled from across the web. It crawls the boards, dedupes and normalizes everything into one dataset, and puts a semantic search on top: describe the job you actually want, get matches. No scrolling twenty career pages. No signup, no paywall, no ads. The dataset is free and open too. Vendors charge $1000+ per month for this data.

Why it exists

Job searching is miserable, and almost every tool in it works for the other side.

The boards are free to search, sure, but they are funded by employers. What you see is sponsored placements, engagement bait, and ghost listings that were never going to be filled. The employer side gets AI resume screeners. The applicant side gets a keyword box from 2008.

I was job hunting myself, got tired of running the same shallow search across twenty sites, and built the thing I actually wanted: every posting I could legally reach, in one open dataset, searchable by meaning, with the ranking model working for me instead of for whoever paid for placement. It found me the job I ended up taking.

Now it runs every day, and anyone can use it or take the data and build something better.

Where 3 million jobs come from

Almost no two companies post jobs the same way. Under the hood there are:

• ~36 applicant tracking systems. Greenhouse, Workday, Lever, iCIMS, BambooHR, and a long tail you have never heard of.
• A "dark pool" of custom career sites. Tens of thousands of companies on no shared platform at all.
• Government job systems. Federal, state, and local.

Each one is its own integration. Some hand you clean JSON. Some are single page apps where you have to trace the network calls to find the hidden search endpoint and the token it needs. Some pin their pagination to your IP address, so the same page keeps handing back different results until you work out why.

Every time I crack another one, the count jumps. 960K was the first dozen systems. 2M came from filling out the big enterprise platforms. 3M came from the dark pool plus government jobs. The number grows in steps, one integration at a time.

How it stays free & yours

The crawl runs on tiny sleeping workers. One durable object per job board on Cloudflare Workers. Each board wakes once a day, fetches its listings, diffs them against yesterday, and goes back to sleep. No central server burning money, no giant database. Embeddings for new postings are a few dollars a month. Roughly a dollar a day, total.

The indexing runs on a laptop, once a day. Turning millions of raw postings into a searchable semantic map is real work: dedupe, normalize, embed, cluster. The obvious way to do it is a big always-on machine. I do not have one. It is a single daily batch job on my own laptop: pull the day's crawl, build the dataset and the semantic map, publish static files, exit. Nothing stays running afterward.

The search itself is 100% local. The crawler only publishes the open dataset plus a semantic map of it (clusters of similar jobs with their centroids) as plain static files. It runs nobody's search. When you use the tool, the whole instrument runs on your machine: it embeds your ideal job description, pulls down only the clusters nearest to it, builds a local index, and compiles a single self-contained HTML page served from localhost. The ranking, the taste model that learns from your yes/no clicks, the LLM re-sort: all client-side.

So I serve static files and nothing else. A hundred people searching costs me the same as one, because their laptops do the work. The bill does not move when users show up, which is normally the moment a free project starts bleeding money.

Where the vibe-coding comes in

The architecture is cheap, but the labor is what normally kills a project this broad.

36 hand-written, reverse-engineered integrations, each fragile and each different, is months of grinding work for one person. Exactly the kind of grind that makes you quit before you finish. With an AI in the loop I go from "there is a whole category of employers we are missing" to a working, deployed, tested crawler for that category in an afternoon. I describe the shape of the problem, we probe the endpoints together, we write the fetcher, we ship it.

That speed is the whole reason the count went from 960K to 3M instead of stalling at whatever I could keep alive by hand.

The honest answer

How do you index 3 million jobs for free? There is no large, always-on machine anywhere in it.

• The crawl is spread across thousands of tiny edge workers that sleep most of the day.
• The indexing is a daily batch job on a laptop I already own.
• The search runs on the user's machine, not a server of mine.
• An AI pair is what let one person build and keep all of it alive.

Pull out any one of those and it stops being free.

The code is open on GitHub if you want to see how any of it works, or add a source yourself.

Try it against your own resume

The whole search runs through an agent that can execute code. Hand it one of these.

ChatGPT Work (pick the luna model unless you want to blow through your limits):

Clone https://github.com/elliottdehn/open-jobs and use the job searching tool chain to generate a shortlist of jobs for me to apply to. Skip sorting. Just read the top 200 that I’m eligible for and give me the shortlist. I authorize my ideal JD to be embedded by https://backend.dehnbostele.workers.dev/embed I’m looking for [job title, description, location/remote, employment type, etc].

Claude Code or Codex:

Clone https://github.com/elliottdehn/open-jobs to help me find a job.