2025년 8월 10일의 Show HN

I built a search engine for engineering blogs because I was tired of manually checking individual company blogs to find real-world production examples.

The problem: When learning a new technology, the best insights often come from how companies like Google, Meta, or Stripe actually implement it in production. But these gems are scattered across dozens of separate engineering blogs with no way to search across them.

What I built: Engineering.fyi indexes engineering blogs from ~15 companies (Google, Meta, OpenAI, Anthropic, Stripe, Uber, etc.) and makes them searchable in one place. You can filter by topic, difficulty level, and whether articles include code samples.

Technical details: - Built with Next.js, SQLite, DrizzleORM - Custom scrapers for each blog (they're all frustratingly different) - Basic tagging system using content matching (still improving this)

Current status: Core search is working. Adding new blogs weekly as I index them.

Next features (based on early feedback): - AI summaries for quick article previews - Weekly digest of trending engineering insights - Save/bookmark articles (considering whether to add accounts)

Interesting challenges: - Each blog requires custom parsing logic (no standard format) - Building an accurate tagging system is harder than expected – started with exact matching but exploring better approaches

I'd love feedback on: - Which company engineering blogs you'd find most valuable to include - Whether AI summaries would actually be useful or just noise - How you currently discover engineering articles from these companies

I've built many interpreters over the years, and Bolt represents my attempt at building the scripting language I always wanted. This is the first public release, 0.1.0!

I've felt like the embedded scene has been moving towards safety and typing over years, with things like Python type hints, the explosive popularity of typescript, and even typing in Luau, which powers one of the largest scripted evironments in the world.

Bolt attempts to harness this directly in the lagnauge rather than as a preprocessing step, and reap benefits in terms of both safety and performance.

I intend to be publishing toys and examples of applications embedding Bolt over the coming few weeks, but be sure to check out the examples and the programming guide in the repo if you're interested!

Hello everyone!

I've created a gameboy emulator to unlock my Wayland session and wanted to share this project to everyone here!

I've been a Linux enthusiast since I was a kid. What always captivated me was the freedom to customize my system exactly the way I wanted. With Wayland, we've reached an incredible level of performance. It's like turning your operating system into a video game! I've always been fascinated by the blend of fun and the serious, technical nature of an OS. That’s what inspired me to create this project.

I started by studying Wayland, its protocol and how to build a compositor. Then I became particularly intrigued by the concept of a locker, which reminded me a bit of an escape game. That’s when I thought: how cool would it be to solve a puzzle to unlock your session, instead of just typing a password? Since I’ve worked with emulators in the past and I’m a huge Pokémon fan, the idea of building the puzzle around that game came to me instantly!

Technically, the locker code and the wayland protocol have been implemented from scratch ( using EGL and wl_keyboard_listeners ). My locker runs a version of the gbcc emulator modded by myself. This emulator waits for one precise value to be set in a given memory address.

I have modded the Pokémon game to my needs: when the password is good, I put the good value in the good memory address so the emulator knows it needs to unlock the session.

Hope you will appreciate this project!

I built llmswap to solve a problem I kept hitting in hackathons - burning through API credits while testing the same prompts repeatedly during development.

It's a simple Python package that provides a unified interface for OpenAI, Anthropic, Google Gemini, and local models (Ollama), with built-in response caching that can cut API costs by 50-90%.

Key features: - Intelligent caching with TTL and memory limits - Context-aware caching for multi-user apps - Auto-fallback between providers when one fails - Zero configuration - works with environment variables

  from llmswap import LLMClient

  client = LLMClient(cache_enabled=True)
  response = client.query("Explain quantum computing")
  # Second identical query returns from cache instantly (free)

The caching is disabled by default for security. When enabled, it's thread-safe and includes context isolation for multi-user applications.

Built this from components of a hackathon project. Already at 2.2k downloads on PyPI. Hope it helps others save on API costs during development.

GitHub: https://github.com/sreenathmmenon/llmswap PyPI: https://pypi.org/project/llmswap/

Maybe you've had this experience too: You build something you're proud of, post it on HN with your low-karma account, and... crickets. Zero votes, zero comments. That's what happened to me last Monday. I posted my coding tool (XaresAICoder - an open-source browser IDE) that I'd built with AI assistance. In my mind it was revolutionary. On HN? Completely ignored. Then I wondered: How many other potentially great projects suffer the same fate? What "hidden gems" are we missing because they come from low-karma accounts? So I built hn-gems (with help from Claude and my own XaresAICoder). It works in two stages:

Continuous scanning: Analyzes all new HN posts from accounts with <100 karma, scoring them for technical merit, originality, and problem-solving value AI curation: Every 12 hours, an LLM deep-dives into the top 10 candidates, checking GitHub repos, documentation quality, and actual utility

The result is what you see at the link - a curated list of overlooked quality posts that deserve more attention. The interesting part: I barely wrote any criteria. I just told Claude "open source good, pure commercial bad, working demos good" and let it figure out the scoring. The AI assessment varies slightly each run, which actually makes it more interesting. GitHub: https://github.com/DG1001/hn-gems

Is this useful? Do you have ideas how to improve this tool if necessary?

(And yes, my XaresAICoder that got 0 votes? The AI thinks it's actually pretty good. I'll take that as a win.)

Hey Ycombinator News community!

I'm excited to share AI Coloring Pages Generator with you all!

As a parent myself, I noticed how hard it was to find fresh, engaging coloring pages that my kids actually wanted to color. So I built this AI-powered tool that lets anyone create custom coloring pages in seconds - just describe what you want and watch the magic happen!

Whether it's "unicorn princess," "summer theme," or "cute kittens," the AI generates beautiful, printable coloring pages that are perfect for kids and adults alike. The best part? It's completely free to use!

I've already seen families, teachers, and even therapists using it to create personalized activities. There's something special about seeing a child's face light up when they get to color exactly what they imagined.

Would love to hear what you think and what kind of coloring pages you'd create!

I built a social listening agent (yes, like everyone and their grandma). along the way though I realized one of the most useful parts was just finding the right communities. so I started saving them and now i have ~70k.

then I added semantic search so you can find communities by meaning. the dataset grows as people use the platform.

how it works

- free accounts: semantic search the already saved 70k communities - paid accounts: search realtime first (keyword searches from the sources) and then run semantic search over the updated communities dataset

I also put together an agent that given a website finds relevant communities for it. example: https://www.pluggo.ai/sites/bloodtrack_au

right now it covers:

- subreddits - x communities - linkedin groups - facebook groups - discord servers - mastodon servers

next, I'd love to figure out a way to add slack workspaces but I haven't figured out a good way besides a crawler that goes around to find slack invite links? if you know a reliable source, I’m all ears

any suggestions for what other sources I should add?

Hi HN,

I built a QR code generator, NitroQR.com.

I was always a bit disappointed that "custom" QR codes usually just meant overlaying a logo in the center, which relies on error correction to cover up the data. I wanted to see if the visual information could be part of the code itself.

NitroQR lets you embed images or text messages directly into the data-holding modules of the QR code, so the entire pattern can be part of your design, not just a block in the middle.

There’s also an experimental feature I'm playing with: generating a single QR code that resolves to different URLs depending on the scanner's distance.

No sign-ups are needed, it's completely free to use. I'm working on a more advanced customizer, but the core functionality is live now.

Would love for you to try it out and hear any feedback. Thanks!

We built two live demos to illustrate the Ghost Drift Theory — a framework for modeling semantic coherence — and a new attention mechanism called GD-Attention.

• Part 1 — Semantic Energy Landscape: Visualize the unique coherence point s* and jump direction g in real time. • Part 2 — GD-Attention vs Softmax: "Softmax blends, GD-Attention selects" — explore the difference interactively.

Paper (with Zenodo DOI): [Ghost Drift Theory & GD-Attention PDF](https://zenodo.org/records/16757311) ▶ Part 1: https://gdt-semantic-energy-demo-jdgoe6gkrohleltjgvwgwq.stre... ▶ Part 2: https://gda-vs-softmax-demo-zooif4cfewrmnv85zaqymy.streamlit...

Would love feedback on clarity, use cases, and potential improvements.

Brainrot Game is a free-to-play, browser-based hub that serves up instant, meme-fueled mini-games—think Italian sharks in sneakers, Tralalero Tralala remix levels, and Tung Tung Sahur puzzle chaos—all without downloads, logins, or paywalls. Every Brainrot game runs on lightweight HTML5 technology, so you can jump straight into the action on Chromebooks, phones, or PCs at school, work, or home. Updated weekly with new viral characters and trending sound bites, Brainrot Game keeps the dopamine hits coming and the brainrot growing.

Is there any other game you want to play?

A CLI for Cloudflare D1 + Drizzle ORM that auto-discovers your config, guides you through environment and database selection, and runs local or remote migrations.

Open source python based event and session store implementation for MCP and an ASGI wrapper that enables cross-node session admission, failover, and sticky-session-free scaling. It partially solves the MCP's session and statefulness problem for scaling by using a session storage (works well for server concepts). New server requests and broken streams can be served and resumed respectively by any of the instances.

*Sampling/Elicitation/Client concepts that rely on GET streams from server are still tied to the same node.