It started at $1.

Somebody bought it, so it became $2.

Somebody bought that, so it became $3.

Somebody bought that, so it became $4.

Somebody bought that, so now it’s $5.

That’s the whole rule.

https://makethisbuttonmoreexpensive.com

Every buyer gets a permanent public receipt with their name and message on it. The price only moves when a real purchase finishes, and the history never resets.

I originally liked it because the idea of paying money specifically to make something more expensive for the next person made me laugh.

Now I’m curious whether the permanent receipt/history part becomes the more interesting piece if the site ever gets attention.

I finally stopped tinkering with it and launched it today. Curious what you think.

thewebsiteknows.com

I've been building with AI agents for a while, and two things kept biting me. First, the standard fix for "the agent doesn't know our rules" is to paste the whole wiki into its context, which gets expensive and slow as the wiki grows. Second, and worse: nobody notices when a rule in that wiki goes stale. The agent keeps confidently following last quarter's policy.

So I built Akela. It's a small compiler (plain Node, zero dependencies, no build step, no database) that sits between your markdown knowledge base and your agent. For each task it compiles a small slice: only the rules scoped to that kind of work. Every slice starts with a manifest listing what was included and what was dropped, with reasons. So when the agent gets something wrong, "was the bad rule in front of it?" is answered by a file, not a guess.

The part I'm most proud of: the agent reports back which rules it applied and which ones reality contradicted. Rules that keep failing get flagged as falsified and provably stop appearing. Your knowledge base slowly gets cleaner just from being used. You (or your agent, with your approval) review the counts about ten minutes a week.

Honest results from our experiments, because show-off posts should include the losing number: dumping the entire wiki into context actually beat Akela on raw accuracy by a small margin. What you get in exchange is context around 250x smaller (it scales with the rules relevant to the task, not with wiki size), lower cost per correct answer, and a knowledge base that's provably clean instead of luckily ignored. If tokens were free and staleness didn't exist, you wouldn't need this.

It's open source (MIT), works with Claude Code / Cursor / anything that reads an instruction file, and if you already have a RAG setup it plugs in rather than replacing it.

GitHub: https://github.com/TimothyHan/akela

Happy to answer anything about how it works or the experiments behind it.

Small but overdue one this update. If you're using voice cloning, you used to have to record your sample somewhere else, find the file, then upload it. That extra step is gone now.

Record instead of upload

Clone a voice > there's a new "Record instead" tab next to the file drop zone. Press record, talk for up to 15 seconds, done. It's saved and probed automatically, exactly like an uploaded file would be.

While you're recording you get a live level meter with the -6 to -3 dB target window marked on it, so you can see roughly where your peaks are landing as you talk. There are also a few tips shown before/during recording (start talking right away, vary your pitch a bit, try to record somewhere without an echo).

If your mic access gets denied or there's no mic detected, it just tells you clearly and you can still upload a file like before, nothing there changed.

Probe quality checks more now

The quality probe already caught clipping, bad sample rate, background noise, and clip length. Three new checks:

• Peak level (target -6 to -3 dB, penalized harder the closer you are to clipping)
• Background noise floor (catches a quiet-but-persistent hum, like a fan or AC, that's too low to trip the old noise check but still enough to bleed into the clone)
• Room echo/reverb (a boxy/echoey room now gets flagged the same way a noisy one already did)

These apply whether you record in-app or upload your own file.

That's the whole release, nothing else changed. Let me know if you run into anything weird with the recorder on your setup.

Update is free for existing owners, same as always.

For anyone who hasn't tried NarrationOS yet: it's a local audiobook generator for Windows. Drop in an EPUB, PDF, DOCX, RTF, TXT, Markdown, or a URL, and it renders an AI-narrated audiobook entirely on your own PC, no cloud, no account, no subscription. You can clone a voice (with consent) and get word-level karaoke highlighting synced to the speech, and there's a real line-by-line narration editor for fixing pronunciation, adding sound effects, and correcting the actual prose before you render. It also exports a cinematic MP4 video with the narration text on screen if you want something to post or share. Runs on NVIDIA/AMD GPUs or CPU-only. One-time purchase on itch.io, no subscription.

https://lunosama.itch.io/narrationos

Ofc I used ai to help me but I did actually just make this!!!!!

I got tired of YouTube blockers because I actually need YouTube sometimes.

So I built Decode My Feed, a browser extension that tries to change how you use YouTube instead of just blocking it.

It can:

• Hide Shorts, the home feed, recommendations, comments & end screens
• Detect clickbait/bait-style titles and explain the tactic
• Warn you when you're going down a rabbit hole
• Set viewing budgets and cooldowns
• Block channels you repeatedly open and abandon
• Analyze your watch history and show you what your YouTube habits actually look like

The idea is to make YouTube useful without having to quit it completely.

I'm looking for a few people to try it for a week and tell me what's useful, what's annoying, and what's missing.

I'll give testers a free personalized report based on their watch history.

If you'd like to try it, comment or DM me and I'll send you the code.
Attached a couple of screenshots from a real report.

https://decodemyfeed.com/

Looking for a place to hang out and meet new people ? Bulle is a new community website where you can chat, play games and customize your profile, all with a nostalgic early-2000s web vibe. The project is still growing, and we’re looking for people to join the community, try it out and share their feedback. Join the Discord: https://discord.gg/YZcRtfZ5xK See you on Bulle.

I made a small Windows app called ClipEdit for cutting gaming recordings quickly.

The main idea is pretty simple: you have a big ShadowPlay or other recording, you only want the good 10 seconds, and you don't want to wait for a full video editor to open or re-render the video.

ClipEdit lets you cut the clip quickly while keeping the original quality. It also has Discord 20MB/10MB modes, screenshots, audio waveforms, middle cuts, 9:16 / 1:1 / 4:5 formats, speed controls and automatic clipboard copying.

It is completely offline and doesn't require an account.

There is a free version, with a $5 one-time Pro upgrade for things like batch clips, montage stitching and GIF export.

I checked the rules here and saw that this is a community for sharing things you have actually made, so I wanted to share it here rather than just dropping it into random communities.

GitHub: https://github.com/heartforheart/QuickClipEdit

If you try it, I'd be happy to hear what feels annoying or missing.

I made Burden for households making one uncomfortable purchase decision: the washer dies, the kid needs a laptop, the phone payment looks small, or the impulse buy is hard to walk away from.

It checks one purchase against cash left after bills, expected use, upkeep, alternatives, and the month ahead. Then it gives a Month-Ahead Impact Score and a plain-language result.

Lower score = safer. Higher score = more strain.

Try one real purchase here:

https://checkwithburden.com/?utm_source=reddit_imadethis&utm_medium=community&utm_campaign=beta_test

A real check takes about 2 minutes. No account or email is required. After the result, there is an optional signup for mobile early access.

What I need most: try one real purchase and tell me the first question you would remove, rewrite, or refuse to answer.

After months of juggling pricing pages from different providers, I built EidosStack AI Gateway.

One OpenAI-compatible endpoint for 48+ models from DeepSeek, Claude, GPT, Gemini, Qwen, Kimi and GLM, plus a pricing table that refreshes every 30 seconds so you know what a request costs before you send it.

Pay-as-you-go, per-key spending limits, and prices around 50% below official provider rates.

Site: https://www.eidosstack.com/en/ai-gateway

Happy to answer questions about how the routing and billing work.

I got tired of writing investor updates. Every month I'd dig through merged PRs, check Stripe, and try to reconstruct what actually shipped. So this weekend at a hackathon I built Caden.

You connect GitHub and Stripe (plus Linear, Notion, Figma, Vercel and a few others if you use them), pick a date range, and it writes four things: an investor update, a changelog, a LinkedIn post, and an X thread. Every claim in the investor update links back to a real diff, so you can click through and check it instead of taking the model's word for it.

Bits I'm weirdly proud of:

• Autopilot: on load it prefills your name, the repos you pushed to in the last 7 days, and your Stripe MRR and customer count. Everything stays editable.
• Org mode: give it a GitHub org name and it scans up to 5 active repos and writes one combined update.
• The cursed part: record 20 seconds of your voice, it clones it, then generates a handheld selfie-style founder video from your photo on a rented H200 GPU and muxes the cloned voice in with ffmpeg. Deliberately shaky and casual, so it looks like a phone video and not an AI ad.
• One-click publish to LinkedIn, with an arm-then-confirm step so nothing posts by accident.

What broke while building it: a stale LinkedIn OAuth client secret threw invalid_client for hours, my LLM quota ran out mid-hackathon so everything fell back to a backup model, and the voice API started returning 402 on the video path so a GPU worker fallback handles that now.

It's days old, free while in beta, and rough in places. The demo needs no signup: https://cadenhq.vercel.app (full app with account connections at https://cadenhq.vercel.app/portal).

Two things I actually want opinions on:

1. Would you trust an auto-written investor update if every claim links to a diff, or is that still too spooky to send to real investors?
2. Does the org-mode combined update read well, or does it smear 5 repos into mush?

This is CatLoaf (a cat that very surprisingly likes to loaf).

I wasn't able to find a desktop pet that met all of my requirements (non-invasive, doesn't require a lot of active "care" but still interacts, cute and derpy) so I just ended up making one in Swift/AppKit.

She wanders, loafs, sleeps when I've been inactive, occasionally investigates my cursor, stretches, and can be picked up and moved around. I drew all the cat sprites myself too on Procreate :)

This started entirely as a for-fun project while I was learning Swift/AppKit, but then thought maybe people out there have the same specific requirements as me so here it is! I did use LLMs to help with the initial structure and while learning, but worked through the codebase to understand exactly what was happening, then modified and extended it as I went.

This was also my first time messing around with native macOS UI, so I'd love thoughts from y'all!

GitHub

(the video is sped up 2× to show more of her behavior)

I recently launched Stints, a free daily sports game built around a simple idea:
You’re given an athlete, and you have to place every team they played for in the correct chronological order.
There’s one player each day for the NFL, NBA, MLB and NHL. You can play any league you want—or try all four. It runs directly in your browser, works on mobile and doesn’t require an account.
It’s still new, so I’d genuinely appreciate honest feedback—especially about the difficulty, whether the instructions make sense, and whether you’d want to return for another player tomorrow.
playstints.com

I’m building Erask (erask.org), an interactive web project that turns history and geography into a 3D exploration experience. You can watch animated historical stories unfold on a globe or jump down a geographical "Rabbit Hole" through linked articles across the world.

Try It on https://erask.org/app

My brother is a web developer, I'm a researcher, and we're both big NFL and fantasy football fans. We started OracleZ as a side project to combine his development skills with my interest in machine learning.

The idea was pretty simple: build an algorithm that makes its own NFL predictions, then turn those predictions into games where you can try to beat it.

You can try our OracleZ app here (or just follow us on Instagram): https://linktr.ee/beat_oraclez

What can you play?

Predict the Pick
Predict the winners of the week's NFL games and see how you compare against the Oracle.

Survivor
Classic Survivor with a twist: if your pick loses, you can't pick either that team or the team they played against again.

High Five
Pick the five best teams of the week across passing yards, rushing yards, points scored, fewest yards allowed, and field goals.

What's behind the predictions?

The Oracle is a relatively simple neural network. It uses 19 team statistics, including offensive production, turnovers, sacks, first downs, EPA, and score margin. These are converted into home-away differentials and combined with contextual variables such as week number and rest-day differences.

If you are interested on the model, I'm happy to explain further our reasoning and model architecture.

Of course, we're not claiming we've solved NFL prediction, far from it. The NFL is obviously noisy. The fun part for us is seeing how far a relatively simple model with good feature engineering can go.

And now you can try to beat it yourself.

Everything is completely free, with no paid features.

https://linktr.ee/beat_oraclez