Demo video: <a href="https:&#x2F;&#x2F;youtu.be&#x2F;ZoQ6w73rbkY" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;ZoQ6w73rbkY</a>Someone first implemented something like this and shared it on HN
<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=44103839">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=44103839</a>...and I love it :DUnfortunately, they removed it later (no idea why). So I decided to make my own implementation.Key features:
- The pieces are selected at random, unlike the true Tetris, which uses Multi bag sampling. VERY interesting dynamic. Try it!
- The pieces don&#x27;t fall on their own. They await my instruction
- The line clears when I decide it&#x27;s time for it to clear :DEnjoy ;-)

Show HN: Reimplementation of Lazy Tetris

Show HN: Anagnorisis. A Vision for Better Information Management

Show HN: A self-hosting compiler from WHILE to WebAssembly

Over the past year I uploaded a bunch of videos to my personal channel. Most of them were short documentaries, news-style edits, or content covering current events and war. A lot of it ended up getting demonetized, age-restricted, or removed completely, usually without any clear reason or explanation.The worst part was not knowing what caused it. You upload something, it seems fine for a while, and then it disappears or gets buried. I spent days editing videos that ended up dead in the water because of things I couldn’t see coming.I started building a tool to help with this. Just something to check the content before uploading, to see if it might get flagged. That eventually became frametwo.frametwo scans your video and flags the kinds of things that might trigger platform filters. It looks at visuals, language, and metadata. It doesn&#x27;t rewrite your content or suggest edits. It just gives you a clear report, so you can decide what to do before your content gets punished.I built the analysis system myself while balancing school and work. It’s called Nextros, and it’s focused specifically on moderation risks, not general-purpose AI. I didn’t want a black box. I wanted something that helps creators understand what might go wrong, without guessing or overcorrecting.The site is at <a href="https:&#x2F;&#x2F;frametwo.com" rel="nofollow">https:&#x2F;&#x2F;frametwo.com</a>I’d appreciate any feedback. Especially from people who have run into the same issues, or have thoughts on how this could be more useful to creators.

Show HN: Frametwo – Tired of my videos getting flagged, so I built this

Hey folks, I’m the creator of WFGY — a semantic reasoning framework for LLMs.After open-sourcing it, I did a full technical and value audit — and realized this engine might be worth $8M–$17M based on AI module licensing norms. If embedded as part of a platform core, the valuation could exceed $30M.Too late to pull it back. So here it is — fully free, open-sourced under MIT.---### What does it solve?Current LLMs (even GPT-4+) lack *self-consistent reasoning*. They struggle with:- Fragmented logic across turns
- No internal loopback or self-calibration
- No modular thought units
- Weak control over abstract semantic spaceWFGY tackles this with a structured loop system operating directly *within the embedding space*, allowing:- *Self-closing semantic reasoning loops* (via Solver Loop)
- *Semantic energy control* using ∆S &#x2F; λS field quantifiers
- *Modular plug-in logic units* (BBMC &#x2F; BBPF &#x2F; BBCR)
- *Reasoning fork &amp; recomposition* (supports multiple perspectives in one session)
- *Pure prompt operation* — no model hacking, no training neededIn short: You give it a single PDF + some task framing, and the LLM behaves as if it has a “reasoning kernel” running inside.---### Why is this significant?Embedding space is typically treated as a passive encoding zone — WFGY treats it as *a programmable field*. That flips the paradigm.It enables any LLM to:- *Self-diagnose internal inconsistencies*
- *Maintain state across long chains*
- *Navigate abstract domains (philosophy, physics, causality)*
- *Restructure its own logic strategy midstream*All of this, in a fully language-native way — without fine-tuning or plugins.---### Try it:No sign-up. No SDK. No tracking.&gt; Just upload your PDF — and the reasoning engine activates.MIT licensed. Fully open. No strings attached.GitHub: github.com&#x2F;onestardao&#x2F;WFGYI eat instant noodles every day — and just open-sourced a $30M reasoning engine. 
Would love feedback or GitHub stars if you think it’s interesting.

Show HN: I open-sourced a $1M engine for closing loops in embedding space

Enter your phone number, get called in 30 seconds for a 2–3 minute AI-powered screening interview.
<a href="https:&#x2F;&#x2F;prepin.ai&#x2F;aiphonecall" rel="nofollow">https:&#x2F;&#x2F;prepin.ai&#x2F;aiphonecall</a>Current MVP scope
Right now it handles general screening questions and generates simple reports. We’re validating demand before building:Technical screening librariesATS integrationsCustom question sets per role or companyMulti-language supportWho we’re looking for
We’d love feedback from recruiters and startup founders who are (or soon will be) running hiring processes.Request for feedback
Please actually try the call first—I know it sounds gimmicky, but the voice quality will surprise you. Then let us know:Did it feel natural?Would you be comfortable being screened this way?If you hire, could you see your team using this?What needs improvement?To see the full recruiter dashboard, leave your email on the page and we’ll send you the demo.This is just an MVP to test the concept. Curious what HN thinks—future of recruiting or unnecessary automation?

Show HN: AI Phone Interviewer – get a call in 30 seconds

Input a SMILES string (or pick one molecule from the examples) and it returns up to 100k molecules closest in 3-D shape or electrostatic similarity – from 10+ billion scale databases — typically in under 5-10 s.*Why it might interest HN** Entire index lives on disk — no GPU at query-time, less than ~10 GB RAM total.
* Built from scratch (no FAISS index &#x2F; Milvus &#x2F; Pinecone).
* Index-build cost: one Nvidia T4 (~ 300USD) for one 5.5B database.
* Open to anyone, predict ADMET, export results as CSV&#x2F;SDF.Full write-up &amp; benchmarks (DUD-E, LIT-PCBA, SVS) in the pre-print:
<a href="https:&#x2F;&#x2F;chemrxiv.org&#x2F;engage&#x2F;chemrxiv&#x2F;article-details&#x2F;67250915f9980725cfcd1f6f" rel="nofollow">https:&#x2F;&#x2F;chemrxiv.org&#x2F;engage&#x2F;chemrxiv&#x2F;article-details&#x2F;6725091...</a>

Show HN: I wrote a GPU-less billion-vector DB for molecule search (live demo)

We built [FOHO](<a href="https:&#x2F;&#x2F;foreignerhome.com" rel="nofollow">https:&#x2F;&#x2F;foreignerhome.com</a>), a housing platform that helps foreigners safely rent in Korea — without scams, translation issues, or ghosting landlords.---### Why we built it:
When one of us moved to the US, he got ghosted after sending a deposit for a room. In Korea, it’s worse — most listings are in Korean, deposits are high, and many landlords don’t want foreign tenants. Foreigners are *3x more likely to face fraud* in rental markets (- StatKorea 2025).We interviewed 122 foreign residents in Korea. Two had lost their deposit. From Reddit posts to real-world landlord calls, we found the same pattern: *language barriers, legal uncertainty, no post-move-in help*.---### What FOHO does:
1. *AI-matching* based on visa type, lifestyle, move-in dates, etc.
2. *Verified listings* and optional escrow rent protection.
3. *Auto-translated lease terms*, with cultural&#x2F;legal context.
4. *Post-move-in care* (rent alerts, utility help, multilingual support).
5. *Landlord tools*: rent reminders, issue ticketing, higher yield without added hassle.---### Traction:
- 1,500+ monthly users, 1,000+ listings
- 50%+ organic traffic (up from 9% in Jan)
- Partnerships with local institutions (e.g. Korea University)
- Preparing expansion to Boston---### Tech stack:
- Next.js + MongoDB
- LangChain + Claude&#x2F;GPT for translation &amp; contract extraction
- Multilingual chatbot built on RAG with custom glossary enforcement---We’re a team of builders who’ve failed 5 times before, this time shipping daily and talking to every user. Would love feedback on:- Matching logic (should we ask for lifestyle tags or structured inputs?)
- Escrow design (would you trust it?)
- Expansion: where would this work next?Thanks HN

Show HN: FOHO – Safer rentals for foreigners in Korea with escrow and AI

I built an open-source AIOps MCP (Monitoring &amp; Control Plane) that detects anomalies in logs using Isolation Forest.It accepts logs from agents, apps, or collectors, parses and extracts features, and identifies unusual patterns in real time. Alerts can be sent to Slack, Webhooks, or PagerDuty. It’s lightweight, easy to deploy with Kubernetes &amp; Helm, and designed to plug into existing observability stacks.I built this to experiment with combining ML-based anomaly detection and flexible alerting for DevOps&#x2F;SRE teams. Most AIOps platforms are either too heavyweight or closed-source — I wanted something minimal yet effective.You can try it by running the FastAPI app locally or deploying with Helm. Contributions are welcome — I’d love feedback on features, detection accuracy, and real-world use cases!GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;kishorealliiita&#x2F;aioops-mcp-iforest">https:&#x2F;&#x2F;github.com&#x2F;kishorealliiita&#x2F;aioops-mcp-iforest</a>

Show HN: AIOps MCP – Log anomaly detection using Isolation Forest

Cheesy Mamas is a local first, multi tab code editor written in Python using PyQt6. It is designed for Linux systems and built around simplicity, transparency, and control. There is no telemetry, no sync, and no accounts. The editor runs entirely on your local machine using standard system tools and stays out of your way unless you ask for help.The editor supports multiple files open at once, persistent tab state, live dirty tracking, and a dark UI. It includes syntax highlighting for Python, C, and LaTeX. A built in run button executes Python directly, compiles C with gcc, or runs pdflatex for LaTeX files. It also includes a Bash button to launch or edit a saved shell script. There is no plugin system and no background processes. All functionality is visible and inspectable in the interface.The Git integration is the core design focus. Unlike most editors, which treat Git as a sidebar or rely on an external staging panel, Cheesy Mamas embeds Git version history directly beside each open file. When you open a file, the editor checks if it is part of a Git repository. If not, the first commit you make will automatically initialize a new Git repository in the current folder.For each file, Cheesy Mamas retrieves its individual commit history using Git log limited to that path. This history appears in a vertical sidebar next to the editing pane. Selecting a commit loads that exact version of the file from Git and performs a diff against the current working version in memory. The editor highlights changed lines and overlays revert options directly into the document view.When you click a past commit, the editor compares that version against your current working file. All changed lines are visually marked. You can click a &quot;revert line&quot; button next to any highlighted block to immediately undo that change using the older version. These changes are local until you save. This allows for a granular, low effort recovery flow without affecting unrelated files or requiring a full diff tool.Right clicking a commit provides a context menu that lets you view the full unified diff, copy the full version of that commit to your clipboard, or revert the entire file to that point. These operations use standard Git plumbing internally and do not alter other files in the repository. Cheesy Mamas does not require you to commit or stage across all files. Each file&#x27;s history and actions are isolated.The editor is single instance by default. Opening a file from the file browser or terminal reuses the existing window and opens the file in a new tab. This is handled via a relay system that passes the file path to the existing running instance.The UI is dark by default with soft gold highlights. There is no animation or decoration beyond what is needed for clarity. The editor warns on exit if any file is unsaved. Saving and Git commits are handled through dedicated buttons and keyboard shortcuts. The Bash button opens a terminal script from the config folder, or lets you write one if none exists.Cheesy Mamas was built to solve a personal problem. Most editors assume the user is syncing code to a cloud service or using Git externally. They require plugins or navigation panels to access version history and rarely show diffs in context. Cheesy Mamas was designed to treat versioning as a natural part of editing, and to bring Git history as close to the cursor as possible without overwhelming the UI.The project is fully offline, runs on Linux, and is installable via a simple shell script. It places the Python script and assets in `~&#x2F;.local&#x2F;share&#x2F;CheesyMamas`, creates a `.desktop` entry, and integrates with your application menu. You can optionally set it as the default handler for `.py`, `.c`, `.tex`, and `.sh` files by editing the desktop file and uncommenting the `MimeType` field.There is no account system and no sync. It’s a local program, designed to live where you live, and let you undo what needs undoing.

Show HN: Cheesy Mamas: Local only code editor with Git and Bash support

Needed this in my own work, anonymizing PII&#x2F;PHI and decided to build this because presidio didn&#x27;t really cut it for our use-case. Try it and maybe let me know if you have any feedback :)

Show HN: Self-host your data anonymization pipeline

Show HN: AI-SDK-Cpp – Unified C++ SDK for OpenAI, Anthropic, and More

Hi HN,I wanted to share a project I built in a strange but fun pair-programming trip with a large language model. The idea was to create my own automated &quot;First Officer&quot;—a tool that handles the tactical grunt work of finding low-hanging fruit vulnerabilities while I focus on the strategic, human-led parts of a security assessment.The result is Nightcrawler, an open-source CLI proxy built on Python &amp; mitmproxy.As you browse a target, it passively finds insecure headers, outdated JS, and JWTs, while its active scanners autonomously test every discovered link and form for XSS, SQLi, Directory Traversal, and more.The development was a real lesson in the &quot;Picard&#x2F;Riker&quot; model of human-AI collaboration. I&#x27;d give the strategic orders (&quot;We need to detect Stored XSS&quot;), and the LLM would execute the tactical implementation (and occasionally &quot;hallucinate,&quot; requiring my correction).The tool is still in beta. I&#x27;d love to get your feedback, bug reports, or ideas on what to build next.Thanks for checking it out!

Show HN: Nightcrawler – A mitmproxy-based scanner to find low-hanging fruit

We are two entrepreneurs who launched a new podcast focused on building AI tools, internally and externally. We hope you enjoy

Show HN: We launched an AI builders podcast

I&#x27;m a software engineer and keyboard enthusiast who wanted custom keycap sets but couldn&#x27;t find anything I liked. That led me to build Thockfactory, an online keycap configurator that lets anyone design and order their own custom sets.The first version launched back in April 2024, but after feedback and my own experience using it, I realized the shop and configurator needed a complete overhaul. I took down the site completely and have rebuilt almost everything since then, focusing on a better UX and a smoother ordering process.Would appreciate any feedback, bug reports, or ideas. You can try the configurator here: <a href="https:&#x2F;&#x2F;thockfactory.com" rel="nofollow">https:&#x2F;&#x2F;thockfactory.com</a>Happy to answer questions about the tech stack, manufacturing, or anything else.

Show HN: Thockfactory – An Online Configurator for Custom Keycaps Enthusiasts

Show HN: Rental bike data scraping – track any bike

I built this lightweight Vim plugin for developers who want to preview markdown without leaving their terminal environment. It uses <a href="https:&#x2F;&#x2F;github.com&#x2F;charmbracelet&#x2F;glow">https:&#x2F;&#x2F;github.com&#x2F;charmbracelet&#x2F;glow</a> to render beautiful markdown directly in a Vim split window.<pre><code> Key features:
 - Toggle preview with \mp - no need to leave Vim
 - Beautiful terminal-based rendering with syntax highlighting
 - Handles code blocks (200+ languages), tables, math equations, and task lists
 - Split window layout keeps your workflow intact by toggling with \mp

 Why I built this: I love using vim to quickly edit files, write down thoughts, and update notes. Building terminal tools can sometimes be big time commitments that take me away from other work. Claude Code helped me to quickly vibe code this integration to improve my workflow. 
</code></pre>
When I looked at other markdown plugins for vim, they required preview plugins requiring Node servers and browser switching, which breaks concentration when writing documentation. This keeps everything in the terminal where Vim users prefer to work, so they can stay in flow while building.The repo includes a demo GIF showing the plugin in action so you can see how it looks before installing. Installation is straightforward - just install glow and drop the plugin file in your Vim directory.

Show HN: Split Vim Markdown Preview – Terminal-Based Markdown Preview for Vim

Hey HN!This idea started with me not being able to buy a GPU and constantly losing to bots&#x2F;scalpers. I figured I&#x27;d use this as way to see how far I can get with &#x27;vibe-coding and designing&#x27;*.The end result was pretty far! Here are more details of behind the scenes. In a future blog post, I&#x27;ll detail behind the scenes process of building this.- The landing page is React&#x2F;Typescript&#x2F;Tailwind.css (which I&#x27;ve never used before)- The dashboard is based on Evidence.dev - which is SQL queries in Markdown + little bit of custom Javascript for chart formatting (again never used before :)- Just being able to get an idea like this in my head into existence would have taken me many months of Stack overflow&#x2F;Google research to first learn React&#x2F;Typescript&#x2F;Javascript but this took about a month (~1-2 hr a day)* &#x27;Vibe-coded&#x27; is often a misnomer i.e. people sometime think it&#x27;s a magic pill. From building this I can tell you that you can&#x27;t just will the site into existence like a genie&#x27;s wish. It still took significant effort to guide the LLM, debug when things go wrong, need to have an idea of design and taste of what to build and how to make it look good, work on many iterations. There were probably 500 iterations between the first and the final iteration.

Show HN: GPU market is absurd! So I built a dashboard of pricing/restock trends

Show HN: A Beautiful Python GUI Framework

Hi HN,I have been working on a project which can automatically convert a recipe to the tree&#x2F;graph&#x2F;tabular style notation that pops up on HN every now and then. It&#x27;s still early days but I am keen to hear about improvements I can make to the recipe presentation.For reference, the earliest example I have seen of this style of notation is from &#x27;Cooking For Engineers&#x27; (<a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=30797907">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=30797907</a>) but I have seen other, similar notations from time to time.This is my take on the notation, as well as the ability to convert recipes automatically. In the future, I would like to see it become my own personal kitchen&#x2F;recipe management system but I would first like to improve the recipe display options.It uses ChatGPT to format the recipe into a JSON tree structure, which is then rendered with CSS grid. So far it works well enough but there is definitely some recipes that are impossible to render, and of course ChatGPT will occasionally spit out less-than-useful trees. I have been using AppWrite for the backend.Curious to hear everyone&#x27;s thoughts and what people might like to see!

Show HN: I made a tool to convert recipes to an easy reading graphical notation

After getting frustrated with macOS&#x27;s Spotlight search, e.g., typing &quot;driver license&quot; doesn&#x27;t give me anything unless the file name matches exactly, I thought, why not index my entire Documents folder? This way, I can find that one PDF or image buried deep in subfolders using natural language queries.So I built SmartSearch; it uses SentenceTransformers for embeddings and FAISS for fast similarity search. Best of all, it runs locally on your computer.Github: <a href="https:&#x2F;&#x2F;github.com&#x2F;neberej&#x2F;smart-search&#x2F;">https:&#x2F;&#x2F;github.com&#x2F;neberej&#x2F;smart-search&#x2F;</a>Demo: <a href="https:&#x2F;&#x2F;github.com&#x2F;user-attachments&#x2F;assets&#x2F;aed054e0-a91f-4599-ac4c-f6fffe2a3d85">https:&#x2F;&#x2F;github.com&#x2F;user-attachments&#x2F;assets&#x2F;aed054e0-a91f-459...</a>Open to feedback!

Show HN: I built an AI-Powered semantic search for Mac

Gofer is a side-project I wrote at 15 because I was sick of these so-called CLI agents. Claude Code, Codex, Gemini CLI, they&#x27;re all wonderful if you&#x27;re coding. But for those just wanna automate their stuff, it&#x27;s a dud. Gofer solves this by being terminal-first, meant to accomplish any task a command line can. It can also watch your desktop so you can avoid waiting for downloads to finish, and can text you via. Telegram!Happy to answer any questions :D! -J

Show HN: I'm 15 and built Gofer, an AI that gets actual terminal work done

Show HN: A Ruby gem that generates a secure, unique ID for the current machine

Hi HN,I’ve been working on Prostir, a simple productivity app that helps you plan your day, capture thoughts, and build habits — without feeling overwhelmed.The idea came from personal frustration: most tools either try to do everything or feel too rigid. I wanted something calmer — a space to think, not just check things off. So I built Prostir using Swift + SwiftUI, with focus on speed, minimalism, and offline support.I’ve been building Prostir, a mindful productivity app that helps you organize your day, jot down thoughts, and build healthy habits — without getting overwhelmed.It’s already available on the App Store and has gone through a few iterations based on early feedback. The goal has always been the same: to create a calm and simple space for planning, especially for people who find traditional task managers too rigid or stressful.Prostir is free to try, and if anyone here wants to explore the premium features, I made a promo code specifically for the HN community:
 Use promo code in appstore: &quot;HACKERNEWS&quot; 
Prostir: <a href="https:&#x2F;&#x2F;apps.apple.com&#x2F;us&#x2F;app&#x2F;daily-planner-prostir&#x2F;id6535696029">https:&#x2F;&#x2F;apps.apple.com&#x2F;us&#x2F;app&#x2F;daily-planner-prostir&#x2F;id653569...</a>Would really appreciate your thoughts or impressions. Always learning from how others approach building focused, human-friendly apps.Would love your feedback or ideas — especially if you’ve built something similar or tried calming productivity tools before.Thanks for checking it out!

Show HN: Prostir – A calm productivity app to plan without burnout

Some time ago I wanted to write a MCP server in Zig but found out there&#x27;s no real JSON-RPC support in Zig, which MCP needs for communication. I ended up developing a JSON-RPC 2.0 library in Zig and more [1], which had its challenges.So I finally was able to put together a MCP server in Zig. It&#x27;s built from scratch implementing the protocol messages from the MCP JSON schema. It&#x27;s actually quite magical to have the LLM calling my MCP server [2].The work is not too bad. Most of the hard work has already been done in the JSON-RPC library.[1] <a href="https:&#x2F;&#x2F;github.com&#x2F;williamw520&#x2F;zigjr">https:&#x2F;&#x2F;github.com&#x2F;williamw520&#x2F;zigjr</a>[2] <a href="https:&#x2F;&#x2F;github.com&#x2F;williamw520&#x2F;zigjr?tab=readme-ov-file#run-the-mcp-server-example">https:&#x2F;&#x2F;github.com&#x2F;williamw520&#x2F;zigjr?tab=readme-ov-file#run-...</a>

Show HN: I rawdog a MCP server from scratch in Zig. No SDK

Show HN: An accurate implementation of Pomodoro Technique

Over the past few months, a student and I set out to explore the impact of vibe coding on web development. Somewhere along the way, we ended up building Daf·thunk, a visual workflow editor. It leverages Cloudflare’s fantastic infrastructure (Workers, D1, KV, Workflows, AI, etc.) to create surprisingly robust workflows that can be triggered manually, via HTTP requests, by email, or on a schedule.During development, we primarily used Cursor with its agent and tab modes, alongside Claude Sonnet 3.5, 3.7, 4, and Gemini 2.5 Pro. Occasionally, we switched to MAX Mode when working on or reviewing more complex changes. We tried to regularly refine our Cursor rules and began applying specific rules to different parts of the codebase (backend, frontend, database, etc.). We also indexed documentation and used it extensively in prompts. For large refactors, we often referenced previous commits to reapply patterns elsewhere in the code.Overall, we feel that prompting for small, incremental, and easy-to-review changes scales well when coding with LLMs and the results are really impressive. In this regard, Andrej Karpathy’s talk “Software Is Changing (Again)” resonates deeply. John Ousterhout’s concept of deep modules has also been a useful mental model. Our Cursor rules ask for simple APIs that hide rich internal logic, and avoid wide interfaces that mirror implementation details.Aside from frequent commits, we didn’t document our process much, as we were mainly exploring and building intuition around what works and what doesn’t. Since we chose to trust the LLM more than usual, we’ve released everything under an open source license and without warranty. As models improved, our reliance on unit tests dropped, which will probably come back to haunt us soon... contributions are welcome ;)GitHub repository:
<a href="https:&#x2F;&#x2F;github.com&#x2F;dafthunk-com&#x2F;dafthunk">https:&#x2F;&#x2F;github.com&#x2F;dafthunk-com&#x2F;dafthunk</a>Product Hunt page:
<a href="https:&#x2F;&#x2F;www.producthunt.com&#x2F;products&#x2F;dafthunk?launch=dafthunk" rel="nofollow">https:&#x2F;&#x2F;www.producthunt.com&#x2F;products&#x2F;dafthunk?launch=dafthun...</a>

Show HN: Daf·thunk – open-source Editor for Prototyping Workflows on Cloudflare

I built a tracker that automatically scrapes the White House website for new executive orders and uses GPT-4 to generate plain-English summaries.The system runs daily, finds new orders, feeds the full legal text to ChatGPT for summarization and auto-categorization, then generates individual pages and updates the main index. It even creates custom Open Graph images for social sharing.Currently tracking 158+ orders with automatic updates as new ones are signed.Features:
- AI summaries of all executive orders in plain English
- Auto-categorization by policy area (immigration, trade, AI, etc.)
- Search by keyword, date, or category
- Completely neutral
- Individual pages for each order with full text
- Auto-generated OG imagesI got tired of reading dense legal text to understand what&#x27;s actually being signed. The AI does the heavy lifting of parsing government language into readable summaries.Link: <a href="https:&#x2F;&#x2F;tonygaeta.com&#x2F;labs&#x2F;executive-orders" rel="nofollow">https:&#x2F;&#x2F;tonygaeta.com&#x2F;labs&#x2F;executive-orders</a>Tech: Next.js&#x2F;Tailwind frontend, Python scraper with BeautifulSoup, GPT-4 for summaries, automated OG image generation via headless chrome.

Show HN: AI-powered tracker of Trump executive orders

chatGPT image-1 is great but the ratio is so weird and do not respect 16:9 for example.So i made this free tool to get perfect ratio without cropping.Hope it is useful for some. Let me know

Show HN: Free tool to resize ChatGPT images to perfect 16:9

Built by an IT admin for IT admins, sysadmin.ca is a no-fluff, privacy-respecting hub of daily tools, vendor call prep templates, cheat sheets, outage trackers, and real-world sysadmin resources. It’s completely free, with zero signups and just one ad at the bottom to keep the lights on. Designed to actually help — not just talk theory. Feedback welcome!