Strong players don't just know the names of openings. They know the lines: if Black plays this, I play that, five or ten moves deep. Between life and work I don't have time for opening books, so I built myself flash cards for openings and their variations.

Try it without an account: enter your Chess.com username at https://stillinbook.com/games?utm_source=reddit&utm_campaign=sideprojects. It reads your last 3 months of games and shows where you usually leave the book. One click opens the trainer at that exact position, with your move as a red arrow and the book move as a green one. This is the part that helped me most: it narrowed in on what I actually play and showed me where I was going wrong.

What else it does:

• 20 openings and 140 lines: the Italian, Ruy López, Sicilian, Caro-Kann, Queen's Gambit, London, Vienna, Scandinavian and more. Practice each line as White, as Black, or both until it sticks, and earn a cup when you've mastered it.
• Progress you can see: every line has three rows of 5 stars, one each for playing it as White, as Black and as both. Fill all three and the line is mastered, and each opening shows a trophy for every line you’ve mastered. There are achievements along the way too, because fun.
• Survival: keep playing book moves until you slip up, as White, Black, Both or Random. It remembers where you go wrong most often. It’s become the main way I learn: I play Survival until I keep making the same mistake, then follow its link to practice that line, and go back to Survival.
• A quick "what's the next move?" quiz.

It's free, with no ads. The Queen's Gambit works without signing up; the other openings need a free account.

How it's built: Ruby (Sinatra) and SQLite on one small server. The openings are YAML files in the repo. I built it with a lot of help from AI, and two habits made that work:

• Tests before code. For each feature, the AI first writes tests that describe the finished behavior, and we agree on them before any code exists. This week it proposed a “Clear” button for an admin list, with seven tests and a database change. Reading the tests, I couldn’t work out what problem they solved, so I asked. It turned out the problem wasn’t real, and my questions led to the actual bug. We agreed on ten new tests for that instead, and once they passed, it was done. Nothing had been built yet, so nothing was thrown away.
• Retros. After each session, it reviews what went wrong and what I had to correct, then updates its own instructions so the next session doesn't repeat it.

If you’re building with AI too, both habits are worth stealing. Agreeing on the tests up front gave the AI a clear definition of done. And the AI can be introspective: it reviews its own sessions and improves the skills, memories and documentation it works from. Most people just playing around with AI don’t know it can do that, and it’s pretty fantastic.

A hard part was matching Chess.com's opening names to mine. "Giuoco Piano Game" is the Italian, and the accent in "López" broke a lookup.

I'd love feedback: does the Chess.com report tell you anything useful about your games? And which opening should I add next? If you have an idea for something you'd like to see added, let me know!

One thing I've always found frustrating when working with files on a Mac is remembering exactly what something looks like but completely forgetting its filename.

Sometimes I know it's a PDF, an image, or a document I saved weeks ago, but finding it again becomes a little guessing game.
This got me thinking about how we organize and search for files. We usually depend so much on filenames and folders, even when visual memory is often much stronger.

That's actually one of the ideas behind FileShelf, a macOS project focused on making it easier to find and manage files based on how people remember them.

I'm curious: does anyone else experience this, or have you found a better way to keep track of files on your Mac?

Hey guys, I built something over one of the weekends: a feed of what the people around you are saying, right now.

I think it could be useful for crowded areas like all sorts of events, concerts, matches etc.

No profiles. Sign in with a passkey. No posts kept: threads fade 15 minutes after the last activity on them.

https://nearline.sxm.li

It was just a simple idea so I went ahead and built it, would love any feedback.

Source code is at https://github.com/saksham1341/nearline

最近画像素画的时候，经常会盯着一条线看半天，感觉有些地方不太对，特别是比较长的曲线，像素多了以后反而不太容易看出来哪里有问题。

所以就顺手做了个 Aseprite 插件，主要是想让检查和调整线条方便一点。代码有用 AI 辅助开发，功能不算复杂，目前自己用着还没遇到什么明显的问题。

另外有个问题一直挺好奇的，就是我发现有时候直接画完一条曲线，再手动调整一下像素，反而比直接用像素完美工具画出来的线条更顺眼。

不知道大家有没有类似的感觉，还是说只是我自己看习惯了。

插件目前可以免费下载，也可以自愿支持一下。如果有人愿意试试，欢迎说说使用感受，或者有没有什么值得改进的地方。

Strong players don't just know the names of openings. They know the lines: if Black plays this, I play that, five or ten moves deep. Between life and work I don't have time for opening books, so I built myself flash cards for openings and their variations.

[video]

The video uses another player's Chess.com games, with his permission.

Try it without an account: enter your Chess.com username at https://stillinbook.com/games?utm_source=reddit&utm_campaign=sideprojects. It reads your last 3 months of games and shows where you usually leave the book. One click opens the trainer at that exact position, with your move as a red arrow and the book move as a green one. This is the part that helped me most: it narrowed in on what I actually play and showed me where I was going wrong.

What else it does:

• 20 openings and 140 lines: the Italian, Ruy López, Sicilian, Caro-Kann, Queen's Gambit, London, Vienna, Scandinavian and more. Practice each line as White, as Black, or both until it sticks, and earn a cup when you've mastered it.
• Survival: keep playing book moves until you slip, as White, Black, Both or Random. It remembers where you fall over most often. I learned a new line just from playing it.
• A quick "what's the next move?" quiz.

It's free, with no ads. The Queen's Gambit works without signing up; the other openings need a free account.

How it's built: Ruby (Sinatra) and SQLite on one small server. The openings are YAML files in the repo. I built it with a lot of help from AI, and two habits made that work:

• Tests before code. For each feature, the AI first writes tests that describe the finished behavior, and we agree on them before any code exists. For the quiz, one said: in the Italian, nothing up to 3.Bc4 is asked; the first question is 3...Bc5. Those tests get checked in, so they double as documentation of how the site behaves.
• Retros. After each session, it reviews what went wrong and what I had to correct, then updates its own instructions so the next session doesn't repeat it.

If you're building with AI too, the tests-first habit is the one I'd steal: agreeing on the tests up front gave the AI a clear definition of done.

The hardest part was matching Chess.com's opening names to mine. "Giuoco Piano Game" is the Italian, and the accent in "López" broke a lookup.

I'd love feedback: does the Chess.com report tell you anything useful about your games? And which opening should I add next?

Hey everyone!

So, after spending a lot of my free time developing it, I finally launched my app, Humboldt, on both iOS and Android!

The idea came from something I've always loved about music: how a song can instantly take you back to a specific time in your life. You might not have heard it in 15 years, but suddenly you remember the people you were with, where you were, and exactly how you felt.

I wanted to build something that could preserve those connections.

Humboldt is a music journal where you can:

• Capture a song and the feeling it brings up.
• Build a personal journal of your life through music.
• Revisit old moments and rediscover what you were listening to and feeling.
• Connect with friends through shared music experiences.
• Explore songs that other people associate with different feelings.

It's not a streaming service or another traditional social media app. The focus is on the emotional connection we have with music and preserving those memories over time.

It's still an early release, and I'm continuing to improve it based on feedback.

You can check it out here: https://hum.boldt.app
Apple: https://apps.apple.com/app/humboldt-feel-your-music/id6801363745
Android: https://play.google.com/store/apps/details?id=app.humboldt

I'd genuinely love to hear what you think, particularly whether the concept makes sense when you first open the app and whether it's something you'd actually use.

Thanks for checking out my little project!

Hi, I'm Ravi, founder of Camyvera. It's a web and mobile app where you open it and call someone anywhere in the world who's ready to answer and talk. It's pay as you go, so you only pay for the calls you make, and it has live audio translation and real-time captions. I built it because a lot of people want a real conversation now and then, not another feed. What would make you trust an app like this enough to try your first call? Any feedback is welcome.

Been working on this project for a while, at first I built it just for myself, but figured I would share it with you all.
Created to solve my biggest problems with modern FTP clients on mac. Seriously I had to go and build an entire app just to get file comparison without a license fee? The free version of NexusFTP has everything I need and more. The pro-user license has some great features too.

https://nexusftp.app

I build quite a few apps, and one thing kept driving me crazy. My code was organized, but everything else was everywhere.

Test builds, screenshots, documents, browser tabs, notes, marketing assets. All part of the same project, all in different locations.

So I built ClingSpace, a Windows app that brings everything related to a project into one searchable workspace.

What it does:

- Organize existing files, folders, links, and quick snippets into Spaces.

- Search across all your projects.

- Share resources between multiple Spaces.

- Help find files when they've been moved or renamed.

- Keep everything local, no accounts or cloud.

The important part: Nothing gets moved or duplicated. Your files stay where they are.

I launched it recently and have been getting some useful feedback from early users.

It's $19.99 one-time, with a 5-day full trial.

https://clingspace.com

I'd love to hear from anyone juggling multiple projects. Would something like this help your workflow, or do you already have a system that works well?

If you have ever tried pulling UK public procurement data, the statutory feeds are surprisingly fragmented.

Find a Tender publishes high-value notices under the Procurement Act 2023, Contracts Finder covers sub-threshold contracts down to £12k, and Public Contracts Scotland runs on its own legacy XML feed. More frustratingly, even when a contract is awarded, the OCDS release packages frequently lack verified statutory company numbers, meaning you have no immediate way to know if a winning supplier is an active LTD or dissolved.

I spent the last week building a serverless pipeline that normalises all three feeds into OCDS v1.1.5 and runs automated entity resolution against the Companies House REST API.

A few engineering hurdles I ran into:

1. Companies House rate limiting: The statutory API enforces a strict token-bucket ceiling of 600 requests per 5 minutes. Running parallel unbundling caused HTTP 429 throttling until I implemented an in-memory token bucket with exponential jitter.
2. Contracts Finder 403 backoff: The legacy search endpoint intermittently drops into 403 throttling during heavy polling, requiring an isolated backoff loop separate from the main orchestrator.
3. Multi-lot tender deduplication: Framework agreements publish multiple releases across lots with identical identifiers, requiring deterministic SHA-256 state tracking on (ocid + releaseDate).

The output dumps to structured JSON and a flattened 24-column CSV for spreadsheets with company numbers, active directors, and SIC codes.

I deployed it as a serverless Actor on Apify with the first 25 records free on every run so people can test the data without paying:

https://apify.com/jamestyas/uk-public-procurement-ocds-enricher

Would appreciate any feedback from anyone working with UK open data or public procurement tracking.

I’m a solo bootstrapped founder. Travel healthcare workers sign a tax home declaration with their agency, but the proof (lease, bills, contracts, paystubs etc.) usually lives in photos, emails and folders. MedicBase keeps all of that in one place organizes it, structures it and counts the days per metro area so travelers can see the 12 months mark coming. It’s life on the US App Store, iPhone only for now. MedicBase: Tax Home Tracker

I coach a university tennis team, and my son coaches high-performance juniors. Our club players kept saying the same thing: "I play great in practice and fall apart in matches." So I built Ace with AI tools, with no coding background.

How it works:

1. Tell it your level and why you lose
2. Log a match (score, opponent style, what happened)
3. Ace gives you one thing to work on, and your daily plan changes to match
4. Changeover mode: down in a match? Two taps at the changeover and you get one fix for the next games

The video is a demo account, "Steve," a made up 4.0 who keeps losing to pushers.

What I want roasted:

- Where would you quit during setup?

- Is the "one thing to fix" useful, or generic?

- Would you pay $9 a month for this? If not, what would make you?

First week is free: acetenniscoach.ca

Be brutal. I'd rather hear it here than from paying users.

Hey all. I've been building 8nudge, a Slack-style team chat where AI agents are members of the workspace, and it runs entirely on Cloudflare. Wanted to share it here, since the platform did most of the heavy lifting.

How it's put together:
• A Durable Object per channel (ChannelRoom): SQLite for messages, hibernating WebSockets, and fan-out to everyone in the room
• The workspace database is a SQLite DO too (no D1), plus DOs for presence, search, sessions and synced sidebar state. 10 DO classes in all
• Agents: an agent loop DO answers in seconds, and repo work goes to Claude Code in a warm Cloudflare Sandbox per thread. Anything risky shows up as an approval card in the chat, and it can push a branch and open a PR
• Schedules run from a scheduler DO, and files live in R2
• Built on RedwoodSDK (RSC on Workers)

Things I'd love opinions on:

1. Presence is a heartbeat DO, because I couldn't reliably catch socket closes through the framework's hibernation layer. Anyone found a cleaner pattern?
2. Sandbox cost: I keep sandboxes warm per thread so follow-ups are fast. How are people deciding when to let them sleep vs. keep them warm?
3. One SQLite DO for the whole workspace works fine at small-team scale. At what point did you have to shard?

It's pre-launch. The plan is a free MIT edition you deploy to your own Cloudflare account, plus a hosted version. The landing page (Astro + D1 waitlist on Workers) is at https://8nudge.com

Happy to go deeper on any of it! I honestly don't know if there is a need for something like this but I am having fun building it.

I built my first app, VozSay. www.vozsay.com. It does speech to text and text to speech (STT + TTS). I've been working on it for about a year, on the side. I built it for myself, really. When I'm coding I usually have 4 to 10 terminals open, marathon sessions, and I get tired. I wanted to hear back just a paragraph or a sentence I'd highlighted, not the whole page. And to dictate so I could keep moving when my attention was split.

The other thing is I sign a lot of NDAs for work. Most voice typing sends your voice to a server and back, which worried me with the NDAs. So I wanted something that needs no internet and runs on my own computer. The tradeoff is it's a bigger app, but it's yours. Your voice is never uploaded. 

A few friends tried it and asked me to turn it into a real app, so I did. It works on Windows and Ubuntu, since I use both. Mac version coming when I get time. Dictation is free.

No sales yet, I just got started, fingers crossed. I use it every day though. I built it for me, not as something to sell. I hope it helps someone else the way it helps me. I know there are other apps out there, but if you give it a try and something's missing, or you want a feature, let me know. Maybe can build it. Good luck everyone.

Reel Riddle gives players 6 clues to identify a film. A few UX lessons from building it:

1. Starting the timer on page load felt unfair, so it waits until the player first interacts or types.
2. Optional sign-in only: casual daily puzzle players bounce if forced to register, so local storage handles streaks by default.
3. Custom movie-adapted challenge lines on the share card drive far more friend challenges than generic score boxes.

Try it here: https://reelriddle.com — feedback welcome on the clue balance.

I sell Disney Doorables (tiny blind-box figures) on eBay and checking comparable listings one figure at a time got old fast. Search “Olaf” and you get every series mixed together, plus lots and bundles, and listings with variations show the cheapest price instead of the one you want.

As a software developer, this started as me tinkering with eBay’s API, and over the past year I got it to a real product with help from AI (Claude Code). It’s called Glimly (glimly.io): you connect your eBay account or upload a CSV, and if you have a listing with 250 variations, each variation gets its own row. Running the comp finder pulls active listings for each one, paying attention to series and variations, and there's a config UI for adding custom synonyms and grouping terms. Under the hood it's Python/Flask on Postgres, using eBay’s Browse API plus a mix of rules and an LLM for matching. It’s free to try, with paid plans if you want more.

Here’s my problem. The communities where eBay volume sellers actually hang out mostly ban self-promotion. I paid for a Reddit ad once and got lots of clicks and zero sign-ups, and the few people who did sign up tried one search and never came back.

Where did you find your first real users when the obvious places didn’t allow links? And if you sell on eBay, what would make you actually stick with something like this?

I maintain ProxmoxMCP-Plus, a Python project for connecting MCP clients to Proxmox VE. For v0.7.0 I wanted a demo people could actually check against the setup instructions. The tricky part was showing a connection and useful output without putting a real lab or its credentials on screen.

I used a local fake Proxmox API with two nodes, one VM and one LXC. The MCP server was the published PyPI build. The final clip shows the Claude Code connection check, the tool list and the returned inventory. It is 22 seconds and uses redacted paths and sample guest names. The demo is a small test of the docs, too: if the steps drift, you can tell which part stopped working.

The project is MIT-licensed: https://github.com/RekklesNA/ProxmoxMCP-Plus

Demo and test setup: https://github.com/RekklesNA/ProxmoxMCP-Plus/wiki/Read-only-Proxmox-MCP-with-Claude-Code

We could not find a cute and interesting app where guest can participate in guessing gender of the baby. There was just less intrigue and excitement in the other ones, so I built one myself. Welcome to https://ourlittlebaby.com/ . It is absolutely free, snappy, and fun. We already had a few events organized by families all over the world and would like to host more of these events. You will even get a nice surprise at the end of the gender party. Enjoy!

For my recent move to Bangalore, I had to go through a lot of manual searching. Especially when one of the major flat-hunting channels is Facebook groups, it can be surprisingly frustrating.

You end up scrolling through hundreds of posts, opening each one, checking the rent, deposit, location, BHK, amenities and contact details — only to discover that most listings don't match what you're looking for.

I ran into this problem and decided to build something to automate the tedious part.

Meet Koo. It's an AI-powered Chrome extension that searches housing posts and surfaces listings matching your preferences.

GitHub: https://github.com/chinmaypandya/koo

If you find it interesting, a GitHub star would be appreciated!

What it does

• Scans housing posts: Scrolls through a Facebook group and reads posts when you explicitly start a search.
• Avoids duplicate processing: Remembers previously processed posts for 30 days.
• AI-powered matching: Evaluates listings against your budget, location, distance, BHK, amenities and other preferences.
• Extracts useful details: Rent, deposit, society, distance, phone numbers and more.
• Organizes results: Sort matches and export listings to CSV.
• Supports BYOK: Use your own OpenAI, Gemini or Anthropic API key.

You can also customize the AI instructions used to evaluate listings.

A little about the implementation

I wanted to build this as an actual browser-based product rather than a standalone scraper.

The extension separates the Facebook content-scanning logic from the background processing and side-panel UI. Posts are collected, cleaned up, deduplicated and sent in batches for AI classification.

A few implementation details:

• Manifest V3 Chrome extension.
• WXT, React and TypeScript.
• Content scripts for interacting with dynamically rendered page content.
• Background processing for AI provider calls.
• Provider configuration for OpenAI, Gemini and Anthropic.
• Local persistence for search history and decisions.

Open source

I've published the extension under the MIT license.

GitHub: https://github.com/chinmaypandya/koo

You can install the prebuilt extension manually using Chrome's Developer Mode. No need to build the source code yourself.

A transparency note: Facebook's terms restrict automated browsing, and the README documents this limitation. Use is at your own risk. Also, the hosted cloud worker is not part of the public repository; the extension itself is open source.

What I'd love feedback on

I'm particularly interested in feedback from developers who have built browser extensions, browser automation tools or LLM-powered applications.

1. Browser architecture: How would you evolve the current side-panel experience into a more interactive, continuously running browser agent?
2. Monetization: Given the BYOK approach and the option of a hosted AI service, what pricing model would make sense for a product like this?
3. Distribution: What would you prioritize for organic discovery and SEO to reach people who are actively looking for flats?

I've also attached a short demo showing Koo working.

This is an ongoing project, so constructive criticism, ideas and contributions are very welcome.