value: farstill

value:
Hey all, I've built a web app for practicing spoken conversations in a language you're learning. It was driven by my own needs when I learn Korean. The main functionality includes two modes:
1. Chat with AI — you pick a situation (ordering at a café, taking a taxi, checking into a hotel) and the AI plays the other role entirely in your target language. It stays in character, adapts to what you say, and you can fail as many times as you want with nobody watching.
2. Chat with Human — for real, in-person conversations with native speakers (think traveling abroad and talking to a local). It translates the conversation in real time so both sides can actually communicate, and saves the full transcript so you can review it afterward and learn from what was said.
I'm a solo dev. The web app is live today and mobile is still being built. The app is still at early stage, I'm adding more features to it. I'd love some feedbacks, especially on what features you think are missing and what you would expect from a language learning app.
Here is a demo page where you can play with it without signing up: https://www.chattylingo.com/demo

value: Show HN: Chatty Lingo – A language practicing app

author: farstill


value: usestork

value: Show HN: Play the US President in the real current week; your timeline forks

author: usestork


value: kamrify

value:
Hi HN,
Tablething is a cross-platform, local-first database client built with Tauri. It currently connects to 13 data sources including Postgres, MySQL, SQLite, ElasticSearch, with more on the way.
Everything runs locally - nothing is sent to our servers. There are optional AI features that you can use with your own API key and data is directly sent to the provider.
I built it because I wanted a tool to save my queries, visualize the data from different sources and have agentic chat the way I wanted. It's free, and I plan to open-source the core once it's stable.
Would love any feedback: https://tablething.com

value: Show HN: Tablething – local-first database client with BYOK AI

author: kamrify


value: toluwajibodu

value:
Hey HN, I built Reyn - which I like to describe as "granola but for everything". You're probably thinking another screen capture AI tool (which is true). Same as always, the biggest question that comes up is privacy, so I'll talk about that first
1. raw screen data is never stored in the cloud
2. user controlled filters are granular to the point that you're able to configure specific apps, windows, websites, or even keywords to be discarded immediately (once again never leaving your mac) and never captured down the pipeline
I personally built it because I find it useful and always had the problem of organizing my day (not note taking or task management), as well as sharing context on things that just happened to go undocumented throughout my day. As I was building it I decided to go even further and see if I could collect useful insights and find room for improvements in my day to day workflow.
This led to the current version of Reyn and its differentiating factor being the fact that it has a proactive layer. Most tools in this space are reactive - you ask, they retrieve. Reyn surfaces insights on its own and sends a daily recap of what you worked on, what's still open, and what deserves attention. The journal feature also lets you search across basically anything you've done on your Mac.
The proactive insights work by first having you configure what your ideal workday looks like — whether that's hours worked or the type of work being done. We have a few broad categories that tasks fall under, with more customization coming.
Current integrations:
Obsidian (available now, improvements in progress)
Gmail, calendar, web search via a floating window with some agentic functionality
Notion (coming soon)
BYOK for LLM API requests (on the roadmap)
... and more
It's still early, but the journal and insights features are the strongest parts right now.
Would love some feedback especially on the privacy model. My personal take - I think with enough safeguards in place, the data aggregated about your work is fully in your control. A lot of these data sources already store your data. If you're using Notion, Claude, or just browsing a website, that data is already being stored somewhere. Reyn is just aggregating it and putting it to work for you.
Happy to answer any questions about how it works
usereyn.com (public beta)

value: Show HN: Reyn – local-first AI that journals and recalls your work

author: toluwajibodu


value: taylorplewe

value:
This is a language server I've been working on for a while now, which warns the programmer (or agent) of low browser support for web features (HTML, CSS, JavaScript) right in your editor. You can also hover over almost all web features and get its support percentage and caniuse.com link.
This project is handmade, no AI was used.
Preview images & setup instructions found in the repo README. There are VS Code and Zed extensions.

value: Show HN: Canipls – see caniuse.com global support percentages as you type

author: taylorplewe


value: Nocerg

value:
Hi HN, I wanted to share a project I've been working on recently.
I built WaylandClientKit mostly for fun and curiosity, and to explore a gap I felt existed in the Swift world which is native Wayland/Linux desktop foundations.
Not as flashy as a UI toolkit you'd build on top - more of a lower level substrate for windows, input, text input, data transfer, cursors, and preview graphics APIs. Its still early, but I'd love any feedback.

value: Show HN: WaylandClientKit – a Swift Wayland client substrate for Linux

author: Nocerg


value: notanaiagent

value:
Hey HN — I'm Julius, cofounder of Righthand. We've been building AI employees (we call them "Righthands") that actually live inside your workflow instead of waiting for prompts. Each one has a name, email address and phone number + unified memory across all communication channels. They run in their own E2B sandboxes, with a filesystem and custom CLI.
We built this because of anxiety. Everyone is anxious about something, especially at work, and we realized that a lot of the tasks people are anxious about are trivial things that we just put off. Not for any good reason, but because we just don't do them. The idea behind Righthand is that you should just be able to forward away the anxiety-driving email or call in for a summary of your to dos on your way to work.
Real customer uses from the last 3 months:
 - automated inbox triage
 - managing maintenance staff for a property in Malta
 - booking a meeting (hundreds, actually)
 - booking a doctor's appointment
 - customized daily briefs
Each one of these things was anxiety driving but it wasn't getting done because it was always lower priority than everything else.
The last two months we rebuilt the skill system from scratch (Skills V4), updated our pricing model, onboarded more customers, improved visibility into the Righthand's "brain" and onboarded a lot of customers by hand. Other things that shipped: nightly self-review (the Righthand reviews its own day and writes notes), goal requests from inside the sandbox, communication-style presets, Bedrock + Codex fallback routing for over-time personas, Parallel web search, Slack app auto-provisioning via Browser Use (yes, we literally drive api.slack.com headlessly to provision each Righthand its own app — happy to go into why).
Trial is card-free now: https://www.righthand.ai. Pricing is $99 Starter / $199 Pro - all with 1 wk free trial. Ask: would love feedback on UI / interaction paradigm. Go through the onboarding and tell us what you liked and what you hated. You won't be charged for 7 days and can easily cancel.

value: Show HN: Righthand – Autonomous AI assistants with skills, goals, and a CLI

author: notanaiagent


value: olievans

value: Show HN: Criterion Closet as a website – pull any of 1,247 films off the shelf

author: olievans


value:
Hi HN, I'm Kaushik, and I built Rocketgraph. I believe that while other spaces have caught up to the AI wave, the observability space is still lagging behind, using the same tools and dashboards that we use to analyse logs from human-written code. But now the code is written and debugged by AI, so we need to rethink how we do observability where the observer itself is an AI.
The problem that I run into is when an alert fires, I have to manually check the Grafana dashboards and write LogQL queries, which is pretty much like greping. But production usually breaks due to a schema mismatch, or a DB connection issue or a log line that I haven't seen before that's buried under millions of log lines. Much worse, the alert never fires, and I don't know when to grep
Rocketgraph fixes that. It turns your logs into patterns by fingerprinting them, then uses ML to anomaly score them by features like frequency, text similarity and other vectors. So, usually this condenses a million logs into 200-300 patterns with anomaly scores and feature vectors that your LLM can easily analyse without sending the entire firehose. This runs at specific points in time, so it's like an online anomaly detection based on logs.
Some companies do anomaly detection on metrics, but this is done for logs.
Other approaches in this space bolt an AI on top of existing Grafana dashboards, but it's the same thing as manually greping with extra steps.
Please check out the example setups to host it locally and run it on your log files. Let me know what you guys think!

value: Show HN: ML condenses billions of logs into a tiny snapshot your LLM can debug


value: moado

value: We subsidize Deepseek 4.0, MiniMax M3, and more!

value: Show HN: A free CLI coding agent, powered by ads

author: moado


value: HaxleRose

value: Show HN: Pitch-by-pitch baseball simulation app to simulate games and seasons

author: HaxleRose


value: shpran

value: This site is a free alternative to crunchbase, I use teams of AI agents to assemble and write profiles of startups, the API key is also free. Im planning on adding more profiles every day.

value: Show HN: Free Alternative to Crunchbase

author: shpran

title: Show HN: Free Alternative to Crunchbase


value: tanin

value:
Hi HNers,
I'd like to share our DOCX plugin for Cowork and Codex.
It uses 2-5x fewer tokens compared to the traditional docx skill because it doesn't write any code nor execute python/node script. It is also much more reliable.
Our DOCX plugin converts docx<->html bidirectionally. This means AI only operates on HTML. AI is excellent and very efficient when it comes to HTML.
Most libraries (if not all) support docx->html, but none supports html->docx. This is what is novel about our approach.
Here's the demo: https://drive.google.com/file/d/1UNlUJYwkNX3NiANDkLLb3UoRSms...
We've been using it in-house for redlining legal documents, and we love it. If you redline docx files, please give it a try: https://github.com/LegalRabbit-AI/legalrabbit-docx-claude-pl...

value: Show HN: Cowork/Codex DOCX plugin. Uses 2x fewer tokens than the docx skill

author: tanin


value: hnrich

value:
This is a silly idea I had a couple years ago that I just recently launched. It's a slow, globally shared word "game" (or experiment?) to find the Last Word on Earth. It starts with about 174k words on a board and anyone in the world can click a word to remove it from the board. Poof, gone. Eventually, the whole world will have decided on one word that remains (other milestone numbers are tracked as well).
I imagine it's going to take a while to get down to a single word, but once that happens, it will be recorded and a fresh board will repopulate to start again. And again and again.
There is little chance of this happening but it would be hilarious if the first final word was "why"? That would make a lot of sense.
If you have a few seconds, add a few clicks to the board to help get the number down and let's see what happens!
And if you have a few more seconds, let me know if you have any ideas or see any issues. I'd love to hear any feedback at all.

value: Show HN: Lastwordonearth.com

author: hnrich

title: Show HN: Lastwordonearth.com


value:
Hey HN,
I wanted to share an open source plugin + skills I put together that turn Claude Code into a job search assistant. The goal is to minimize the amount of time needed to find interesting and relevant jobs.
How it works:
1. Clone the repo, install the plugin, and run `/job-search`
2. Claude will ask a few questions to understand the roles you’re interested in and save your preferences locally.
3. Claude will then pull live job postings (currently, LinkedIn Jobs), compare posts against your preferences, and generate a digest of the posts that are relevant.
4. [Optionally] Claude will also run your search on a schedule (e.g., daily) to surface new posts matching your preferences over time.
Features on the roadmap:
- Skills for having Claude compare resumes to job descriptions to estimate “fit”
- Skills for having Claude recommend resume edits to better align with a given job description
Repo: https://github.com/agent-data/job-search (MIT license)
Important: the plugin uses agent-data (a tool for accessing structured web data) under the hood to pull live job postings, so you’ll need an API key to get started (no credit card required).

value: Show HN: An open source job search plugin for Claude Code


value: vinzdg

value: Show HN: I built a smart screen recording macOS

author: vinzdg


value: bootsybus

value:
It's an iOS app for the Cup.
We built what we wanted, with very careful attention paid to spoilers, player information, and great UI.
Free, no ads, no fluff, just football.
I hope you enjoy. Comments welcome here or via the app feedback mechanism.
(Apple has been fighting me on allowing $1.99 button to donate to a football ngo if you like the app. I don't work at the ngo but have their permission to collect optional donations. Otherwise I'm not affiliated with it and Apple is objecting to the donation button because I'm just a friend of the ngo. If you've won that particular edge case battle with apple please let me know!)

value: Show HN: A world cup app built by football lovers

author: bootsybus


value: Show HN: Rank scratch tickets in your state by expected value


value: idodekerobo

value:
A lot of teams are trying to figure out how to use AI collaboratively and as a team.
I built Draft to help teams with this problem.
It focuses on automatically pulling/pushing context edits to a shared (private) git repo by having Claude Code analyze your agent sessions, Slack threads, and Granola notes/transcripts.
It's human in the loop so you can verify what is being added to context.
That context can then be injected into your agents starting with Claude Code, Codex, OpenClaw, and Hermes.
Its free and open source and contains a macOS app, CLI, and skills so agents can work natively with it.
Would love to know how teams are solving this with their teams or any feedback on the project!

value: Show HN: Draft, Open Source Agent Context Sync/Collaboration

author: idodekerobo


value: I built the desktop app that detects and redacts personal data (or PII) locally without sending any text to server. It supports rule-based filtering and AI model-based redaction (eg openai privacy filter). It's open source and free. Please check out the repo and https://pii-gui.vercel.app/

value: Show HN: Local personal data redaction for any AI tools


value: gptbased

value:
gptbased joins LMArena rankings with live OpenRouter pricing. Daily snapshots.
Features:
- 8 LMArena categories: text, webdev, vision, image-gen, image-edit, and three video subsets
- "Best value" picks via Pareto frontier in (cost, Elo) space, knee of the curve
- Side-by-side compare
- Email alerts when a new model enters
- Free RapidAPI tier
What else do you want to see?

value: Show HN: Gptbased – LLM leaderboard that emails you when to switch

author: gptbased


value: Show HN: Ubercookie – A live demonstration of how websites can track you


value: dongdongbh

value: Show HN: Mindwtr – Free, open-source, local-first GTD app for all platforms

author: dongdongbh


value: kataqatsi

value: GitCredit is a git contribution graph outside of GitHub

value: Show HN: GitCredit – Contribution graph outside of GitHub

author: kataqatsi


value: Show HN: Push vs. Pull Agent Memory?

title: Show HN: Push vs. Pull Agent Memory?


value: Show HN: 150M Mandarin transcription model with real-time metadata detection


value: longtermop

value:
Every agentic system I see has the same hidden tax: the model keeps rereading the same context.
Tickets, Slack threads, docs, customer history, database notes, runbooks, logs, prior decisions. You can cache static prefixes, route to cheaper models, or set team budgets, but none of those fixes the underlying behavior: agents start most tasks trying to re-explore everything.
We built Parcle as a shared memory layer for AI agents. It ingests operational context, indexes what happened, and lets agents retrieve a small, relevant memory set for the next step instead of pasting everything back into the prompt - or worse, letting the agent go explore on it's own and burning tokens.
We started tracking our tokens consumed on tasks with and without our memory layer just with indexing of local files. In our deployments/evals, the biggest reduction we’ve seen is up to 70% lower token spend on agentic tasks, with roughly 2x faster task completion. The median was ~30% less tokens spent. The biggest savings often come from data and context-heavy workflows; when the agent needs to retrieve data and context from multiple locations and sources. The best cases so far are support, ops, research, sales, and finance workflows where the agent otherwise reloads the same account/workflow/history context again and again.
Why I think this matters now:
Pylon’s AI cost post made us ask the question:
How much are companies paying because their agents keep looking for the same context? Is this a hidden tax that memory could solve?
We built Parcle to make agents remember. The surprise was that memory does not just make agents more useful. It also cuts down on tokens consumed. Less tokens spent figuring where things are, and more time spent doing actually productive work.
- Anthropic says agents use about 4x more tokens than chat. We think this is an understatement,
- OpenAI and Anthropic both have prompt caching because repeated prompt context is expensive, but caching mostly helps when the reusable content is stable enough to hit the cache. But this doesn't resolve the fact that prompt caching is forfeited after 5min-15mins of inactivity.
- “Lost in the Middle” and Chroma’s “context rot” work both point at the same issue: more context is not the same thing as usable memory.
- The context-engineering crowd seems to be converging on this: the hard part is deciding what the model should see at each step.
Parcle is our attempt at making that operational: memory outside the model, selected into context only when useful.
I’d love feedback from people running real agents in production:
1. Where are your tokens actually going: repeated input context, tool traces, retries, output, evals, or something else?
2. Have prompt caching and model routing been enough?
3. What would you need to trust an external memory layer inside an agent loop?

value: Show HN: We cut >60% of tokens from agentic tasks by removing repeated context

author: longtermop


value: modulusme

value: Show HN: I built a tool which turns any website into promo video in minutes

author: modulusme


value: mvkel

value:
I’m building Attagram: a small printer that lives in the kitchen and prints a daily paper digest for kids.
The idea came from an emerging family dynamic I kept noticing. My daughters (A, 9 and J, 8) are becoming increasingly independent, but as parents, we hold an enormous amount of invisible state in our heads and phones: what day a project is due, who needs cleats, what's for lunch, which kid has library day, what chores need to happen before screens, how many days until the camping trip, what Grandma wanted them to know, what changed after school, etc.
Kids live downstream of that system, and their experience of it is repetitive nagging:
"Brush your teeth."
"Pack your folder."
"Don't forget your cleats."
"Don’t forget your water bottle."
"Did you pack your cleats?"
"Please pack your cleats."
Even if the tone is kind, the repetition makes it feel like a nag. And all of the information is trapped behind screens, which isn't great if you're trying to limit your kids' screen time, all while trying to give them more ownership in the process.
Attagram tries solve for that. It turns that invisible family state into a small daily artifact a kid can own.
Every morning, the printer wakes up and prints a parent-curated morning edition newspaper. It has sections like: today’s plan, a todo list, a countdown to an event, a joke, a riddle, a note from a grandparent, and lots more. It's something kids can tear off, pin to their bulletin board, shove in their pocket, or punch through a spike.
All of this is managed through, yes, an app. BUT! The app is for the parents. Its job is to be the best in the world at turning family logistics, rituals, and affection into a screen-free paper experience. The paper remains the hero, and how a kid experiences Attagram.
Technically, Attagram is pretty simple. It uses off-the-shelf parts to connect to a cloud service so daily digests can be generated and printed at scheduled times. It also allows trusted family members to send one-off notes as needed. The magic is in the experience overall and how it feels to hold the paper in your hands.
This is my first hardware project, and as a software person, I have really appreciated (and respected) how much there is to learn. It's a lot of work to make sure this product is perfect on day one, because there's no easy way to update hardware. Software is so forgiving!
We have a nationwide private beta program in homes now, and the feedback has been really positive. More than one family has told me that their kids park themselves in front of the printer each morning, waiting for it to print at the scheduled time. I'm planning to ship a few more units for free to really ensure we're getting all the input we can before going into more scaled production. If you think you'd be interested in one, drop me a line at myke@halfcorp.co.
Our modest plan is to reach 100 paid reservations before scaling manufacturing, partly to test whether strangers actually want this enough to pay rather than just say "cute idea." https://www.attagram.com/order
I’d value HN's experience on:
1. Industrial design: what stands out as being "bad design" in the current iteration? Also, if this is something you'd want to work on, I'd love to chat!
2. Mechanical engineering: what are the best ways to "harden" a device like this so it's reliable, but easy to manufacture. Also, if this is something you'd want to work on, I'd love to chat!
3. Manufacturing: when do you engage with a contract manufacturer in China? What do you try to avoid? Also, if this is something you'd want to work on, I'd love to chat!
4. HN Parents: is this something you could see yourself buying, or it just cute? If the former, but you wouldn't pre-order, why not?

value: Show HN: Attagram, a tiny printer that gives kids a magical daily digest

author: mvkel


value: Show HN: Automatically Validate Python Packages


value: sakuraiben

value: Show HN: Memharness – Bi-temporal memory for AI agents, in one SQLite file

author: sakuraiben


value: drgath

value:
yuiblog.com was Yahoo's blog for YUI (Yahoo User Interface library) and one of the earliest places "frontend engineering" got taken seriously as its own discipline. It was home to early explorations on JS patterns, performance, accessibility, and design systems, years before any of that was mainstream. It featured over 1,000 posts from dozens of authors, including Douglas Crockford, Nicholas Zakas, Steve Souders, & Stoyan Stefanov.
Sadly, Yahoo did as Yahoo does, and killed the blog sometime in the 2010s. Upon realizing what the web lost, I scraped everything off the Wayback Machine in 2020, before it eventually disappeared from there as well. The scraped HTML was badly mangled, with broken layouts, missing assets, bad links, and garbled post bodies from years of archive.org's own transformations. Reassembling it by hand looked like weeks or months of effort I'd never realistically get around to. So, there it sat in a zip file collecting dust for years, waiting for a spark.
What eventually got it unstuck was the epiphany that I could treat an LLM as the cleanup crew, instead of doing it by hand. Duh. At that point, weeks of effort turned into hours. So, I fed it the archive, had the model identify and isolate actual article content from the chrome, normalize the markup into markdown, fix internal links to a consistent structure, then spot-checked a sample against the original archive snapshots rather than reviewing all 1,000+ by hand. It's not pixel-perfect to 2008-era yuiblog, but it's readable, browsable, and most importantly, the content is intact. The only new content I added was the "Over the Years" section, to commemorate the effort from the community. Github repo is at https://github.com/derek/yuiblog.
While the library itself is long dead (RIP), these explorations into "F2E" as we called it can now live on. If you remember reading this stuff in the 2000s, or you're curious what frontend engineering writing looked like before "frontend engineering" was a cool job title, take a look.

value: Show HN: I revived yuiblog.com, Yahoo's defunct front end engineering blog

author: drgath


value: ericlbuehler

value:
Hey all!
I'm the maintainer of mistral.rs. I just landed support for OpenAI-compatible Agent Skills via a /v1/skills endpoint, and it works with local open models.
Until now Skills have basically been locked to closed models, and with the ability to have private, local intelligence becoming increasingly important, but this feature allows you to do XYZ with local models.
It's fully compatible with OpenAI's /v1/skills API, so you can drop mistral.rs into your existing code with minimal difficulty.
We support the accompanying tools too: /v1/files or input_file for attaching files to your prompts, and mistral.rs also allows models to send generated files
back using the OpenAI-compatible method.
It's also easier than ever to try mistral.rs: we are including prebuilt binaries for NVIDIA CUDA, Apple Silicon, and CPU!
# Linux/Mac
> curl --proto '=https' --tlsv1.2 -sSf https://raw.githubusercontent.com/EricLBuehler/mistral.rs/ma... | sh
# Windows
> irm https://raw.githubusercontent.com/EricLBuehler/mistral.rs/ma... | iex
Then:
mistralrs serve --agent --isq 4 -m google/gemma-4-E4B-it
Super excited for you to try this out and any feedback! Do you have any suggestions for what you would like to see in the next releases?
Check out the GitHub: https://github.com/EricLBuehler/mistral.rs
Docs & Quickstart: https://ericlbuehler.github.io/mistral.rs/

value: Show HN: Run Agent Skills with mistral.rs v0.8.10: /v1/skills support and more

author: ericlbuehler


value:
Hello HN,
AutomatiQ is an open-source reverse-engineering AI agent, that can write requests-based(no browser) automation/scraper scripts on its own, all we have to do is, to normally browse the website once.
This makes it a lot easier to create and maintain the scripts. This is not a completely autonomous agent, you can pause, talk, guide the agent on its RE path.
Despite the limitations of this approach, up to 60%-90% of websites can be automated/scraped with just raw requests and TLS-spoofing(links to sources provided in the blog)
The tool successfully ran against popular websites like, bookmyshow, makemytrip. And to test it in the open, it was able to produce scraper solutions for 2 problems posted on r/webscraping in a single try.
As the scripts provided by the tool are requests-based, you can expect a 10-100x speed increase, and reduction of 5-7x memory footprint in your existing browser-based automations and scraper workflows.
Github: https://github.com/StoneSteel27/AutomatiQ
Blog for verbose explanation and techincal implementation details: https://shiny-sushi-116.notion.site/automatiq
Demo video of using Automatiq on bookmyshow website to get current running movies, showtimes, seat layout of a particular screen: https://www.youtube.com/watch?v=OfMvAQP5pkM
Thanks for your time, hope you have a great day/night ahead :)

value: Show HN: Automatiq - generate webscrapers/automations by browsing any website


value:
Hi HN, I'm Matt, CTO at STUDIO HAZE in Seoul. I've wanted to build a programming language for twenty years, ever since Ruby got me wondering what a small language out of Korea might look like. Today I'm opening the repo for the first time, as Topaz v5.2.
Topaz reads like Python or TypeScript, runs on a reference interpreter (topaz run), and builds a self-contained native binary by lowering to Rust, then handing off to the Rust toolchain (topaz build).

  function factorial(n: int) -> int {
      if n < 2 { return 1 }
      return n * factorial(n - 1)
  }
  print("10! = {factorial(10)}")
  // 10! = 3628800

The idea: application logic should have a small, fixed surface with one obvious way to write each thing, and the compiler does the hard part underneath. Writing glue in Python and TS, I kept re-making the same policy decisions — errors, absence, cleanup. Topaz decides those once: Result for recoverable failure, optionals for absence, defer for cleanup.
Identifiers are Unicode from the lexer up, with no implicit normalization — names compare by scalar sequence, so what you typed is what matches. Deliberate, not an oversight: NFC and NFD forms aren't silently merged, and the module resolver rejects imports that would collide under NFC/NFD or case folding.

  function 인사하기(이름: string) -> string {
      return "안녕하세요, {이름}님!"
  }
  print(인사하기("토파즈"))
  // 안녕하세요, 토파즈님!

sql, sh, and path strings are tagged templates: interpolations stay structurally separate from the literal text, so a value is never spliced into the query as raw SQL. Below, a classic injection attempt; the printed value is the template's structure, not a concatenated string:

  let user = "'; DROP TABLE t; --"
  let q = sql"SELECT * FROM t WHERE name = {user}"
  print("{q}")
  // <sql template, 2 part(s), 1 interpolation(s)>

To be clear on scope: this is a representation, not a database driver — there's no query-execution or parameter-binding layer yet. Injection is impossible by construction at this layer; a driver that consumes the value safely is future work.
Why compile through Rust instead of C or LLVM? I'm not trying to replace Rust — if you want to write Rust, write Rust. It's just a good thing to land on: I inherit its memory safety and a mature backend for free, the build is reproducible, and the binary needs no Topaz runtime. Topaz is what you write; Rust is what it becomes.
Every fixture runs through both the interpreter and the compiler, and their stdout and exit status must agree; the moment they diverge, a test goes red. Both engines share the same runtime value model, so agreement is structural, not coincidental. cargo test --workspace is green at 635 tests. CI runs on Linux, macOS, and Windows, and every commit clears clippy -D warnings and cargo fmt --check.
Implementation notes:

  - Whole toolchain (lexer, parser, checker, interpreter, emitter) is
    pure Rust, zero crates.io dependencies, forbid(unsafe_code).
  - The module resolver rejects path collisions from platform-specific
    case folding or normalization, keeping imports unambiguous across OSes.

Some history, since opening at v5.2 looks odd: v1 was a Lisp dialect (now separate), v2 a Python-like surface, v3 and v4 an internal tool we ran next to Rust in our products. v5.2 is the first version I'm comfortable showing.
The honest catch: it's early, with basically no ecosystem yet. The topaz binary runs, checks, and emits on its own, but topaz build shells out to cargo, so that command needs a working Rust toolchain. This is not "easy Rust." It's a small application surface that happens to compile through Rust.
Docs at https://topaz.ooo. License Apache-2.0. Try it with:

  topaz run examples/hello.tpz
  topaz build examples/hello.tpz --out-dir out --run

I'd love feedback on the diagnostics, the generated Rust, the module semantics, and Unicode edge cases. Please tear into it.

value: Show HN: Topaz – A small application language that compiles through Rust


value: Show HN: Deck-IR – render .pptx to HTML in pure JavaScript, no LibreOffice


value: mattfaltyn

value: Show HN: Data Control Center: Local-first workbench for DuckDB and data files

author: mattfaltyn


value: bsampera

value:
I work at a startup that makes martial arts gym software (MAAT). We handle the memberships of students so gym owners don't have to, using a payment system and a database. As we get more gyms we get more support tasks: subscription problems, membership updates, data exports...
The way we solve it now is a "tree of llms.txt". An llms.txt normally references what info is available on a website or docs — we use the same idea internally to organize the info the agent needs. The agent starts from a folder and navigates down:
.
├── llms.txt        # references each folder at this level
├── stripe/         # info.md: how our stripe account is structured
├── firestore/      # info.md: how the schema looks
└── support/
    ├── info.md     # how to resolve support tasks
    ├── runbooks/   # one file per task, with its own llms.txt
    │   ├── cancel-subscription.md
    │   ├── export-gym-data.md
    │   └── fix-membership-mismatch.md
    └── logs/       # one file per day, every task the agent resolved
Copy
With this we can steer the agent much better and create a new runbook every time a new support task comes.
You can add in every integration what the agent should and should not touch. The gcontext prompts make sure any guardrail is meticulously followed.

value: Show HN: Gcontext – a tree of llms.txt files to steer agents on support tasks

author: bsampera


value: tanelpoder

value:
Here's something I've been using for eBPF program profiling & optimization purposes and just published it as it has made my "performance nerd life" easier.
This is a tool for profiling eBPF programs themselves, probe->kernel activity, interactions with shared hash maps, etc.
Since eBPF programs are pieces of machine code residing in (kernel) address space, you could profile them with standard perf just like any other kernel function. However, perf alone won't show you other useful metrics like number of executions and average eBPF program runtime, like bpftop does. Also, I want an easy way to map CPU samples to original source code lines, where possible.
I wanted to unify both approaches, display the bpftop-style call count & probe latency, with the ability to drill down inside where the eBPF program spends most of it's time.

value: Show HN: Profiler and Runtime Reporter for eBPF programs (brr)

author: tanelpoder


value: modinfo

value: Show HN: Gimji – local-first project notes with tasks, boards, and calendars

author: modinfo


value:
Bonscape is visual canvas for interacting with AI chats, designed for visual thinkers.
It aims to move beyond linear chat interfaces, providing a multidimensional experience for marketers, content writers, researchers, product managers, founders, and job seekers.

value: Show HN: Bonscape – Whiteboard for AI Chats


value: hiteshsundraaa

value: Show HN: A dbt-first semantic assumption check for SQL changes

author: hiteshsundraaa


value: zoooey

value: Show HN: Minimal OG Image Maker

author: zoooey

title: Show HN: Minimal OG Image Maker


value: pramodbiligiri

value:
Hi,
I've created a coding workflow plugin for my personal use. Might be of use to others. More info at: https://www.shipsmooth.net.
The workflow assumes that you'll want to start with a coding plan which in turn is broken down into tasks. But both the plan and its tasks will evolve as you start generating the code (which is what I find usually happens with me).
So the plugin takes on the chore of managing all your plan/task updates and versioning, freeing you up to focus on just getting to your outcome in an iterative, interactive way.
There's a couple of opinionated bits in it: It tries to break down the plan implementation into "vertical slices" (https://en.wikipedia.org/wiki/Vertical_slice). Also, it believes in implementing the riskiest parts first, validating them, and only then finishing up the rest of the work: https://en.wikipedia.org/wiki/Spiral_model.
- Github repo: https://github.com/bitkentech/shipsmooth
- SKILL file containing the full workflow: https://github.com/bitkentech/shipsmooth/blob/releases/dist/...
The plugin does not have any specific support for one-shotting or for long-running coding tasks - although nothing in it should preclude such use cases.

value: Show HN: Shipsmooth: coding workflow plugin for iterative, solo-dev work

author: pramodbiligiri


value: Show HN: Testpick – run only the tests your Git diff can break


value: depomoty

value:
Hi HN, I built Cliptop, a clipboard history app for macOS.
Yes, it is another clipboard manager. I built it because I wanted one that felt fast from the keyboard, stayed local, handled more than plain text, and did not make me think too much about sensitive clipboard items.
The main things I focused on:
* Keyboard-first search and paste
* Local clipboard history for text, links, code, images, files, colors, and design layers (e.g. Figma)
* Quick actions like paste as plain text, color format conversion, image crop, background removal, and Markdown conversion
* Pinboards for saving items and keeping things organised
* Ignored apps for password managers and other sensitive sources
* An option to remove an ignored item after one paste, so a password/token is not left sitting as the active clipboard item to be sent accidentally in a chat
* Native macOS app, around 10 MB and < 100mb memory usage when active
The UI can open from a shortcut, the menu bar, or the top edge/notch area. The notch part is just an access point, not the core idea.
I’m especially interested in feedback on the privacy model, whether the sensitive-item behavior makes sense, and what would make you trust or not trust a clipboard manager.
Happy to answer any questions!

value: Show HN: Cliptop, a keyboard-first clipboard manager for macOS

author: depomoty


value: Daniel-Pan

value: Show HN: A Good Alternative to Zendesk

author: Daniel-Pan

title: Show HN: A Good Alternative to Zendesk


value: andreagrandi

value: Show HN: Meeting Notes Sync – import transcripts and AI summaries into Obsidian

author: andreagrandi


value: shadag

value:
OpenRouter's fusion is great. I built this for my own deep research queries.
Model fusion is useful for tool calls and complex prompts that require constructive criticism.
Would love feedback.

value: Show HN: open source llm fusion

author: shadag

title: Show HN: open source llm fusion


value: gwitko

value: Show HN: Conduit, Floss SSH/Mosh/SFTP Client (Android and iOS) Now on App Store

author: gwitko


value: Show HN: App-it – turn a local web project into a desktop app (no Electron)


value: Show HN: Cluely is easily detectable / detector source code


value: Sharanxxxx

value: Show HN: Causality Engine – Causal marketing attribution for e-commerce

author: Sharanxxxx


value: FahadHafeezOff

value: Show HN: Khwand – self-healing CI/CD for AI agents (GitHub App, Python-first)

author: FahadHafeezOff


value: samuria

value: Show HN: A calm browser based physics game

author: samuria


value: Show HN: We built a tool to scan used gadgets to get specs, grade and live price [video]


value: Show HN: Eggspression – shape any bird egg in 3D from four parameters


value: mgierlach-polyv

value: Show HN: Polyvia – Multimodal document retrieval over 100K+ files

author: mgierlach-polyv


value: merveceylan

value: Show HN: Glisker – First-impression feedback on your landing page (no signup)

author: merveceylan


value: bitslayer

value: A webtoy I have been building. When you zoom in, the whole earth remains visible, with higher and higher scales towards the middle.

value: Show HN: Circular Map with You in the Middle

author: bitslayer


value:
I built and released a Mac app I always wanted to exist:
Glassboard let's you draw over anything on your Mac, across every app and every screen, Khan-academy style!
Hold a keybind and draw. Release and it fades away. That's all! (well, except colors, shapes, a radial menu switcher and keybinds galore). But the basic concept is simple hold, draw, release, continue presenting without losing flow.
Made for frequent screensharers and content creators.
No more wiggling my mouse pointer at what I want to highlight while screensharing.
Try it at https://stem.ps/glassboard. It's completely free and will stay that.

value: Show HN: Glassboard – Draw over everything on your Mac, Khan-academy style


value: Show HN: Vessel – Portable app files (UI, FastAPI, SQLite) like .xlsx for tools


value: dbarabashdev

value: Show HN: Nod – Mac meeting notes that don't join the call or store audio

author: dbarabashdev


value: crosschainer

value: Show HN: S&box watch, a live index of the Source 2-powered s&box ecosystem

author: crosschainer


value: ARayOutOfBounds

value: Eng leaders lack visibility into which tools are being used to build software. This is the first scanner of its kind to provide repo-level evidence.

value: Show HN: Know which AI coding tools/MCPs/etc. are used to ship software

author: ARayOutOfBounds


value: flexorch

value: Show HN: Flexorch-audit – quality scoring and PII detection for LLM pipelines

author: flexorch


value: mfornet

value:
At Cajal (YC W26) we’re excited to share Talos (https://github.com/cajal-technologies/talos), an open source framework for formal verification of WebAssembly modules in Lean.
AI is now writing tons of the code that gets pushed to production. As code generation gets cheaper, verification becomes the bottleneck. We believe in a future where every piece of software comes with a mathematical proof that it does what its author intended - in doing so, eliminating many classes of exploits. Talos is part of the foundation for that.
Talos provides a Wasm interpreter optimized for reasoning at the binary level, together with a weakest-precondition calculus layer for proving properties about programs. Because we reason directly about WebAssembly, any language with a Wasm backend is in scope: Rust, C++, Go, C, Swift, Kotlin, Zig, C#, and many more.
To make this possible, we use Lean: a programming language and theorem prover that lets you both write software and mathematically prove that it's correct - all in one system. That's what lets Talos double as both an executable interpreter and the formal object Lean reasons about. Lean also integrates with modern AI proving tools, discharging goals automatically via both proof search and direct evaluation.
To see Talos in action check out a proof for Stein's GCD algorithm, implemented in the popular Rust crate num-integer: https://github.com/cajal-technologies/talos/blob/main/progra....
Our roadmap:
- Full Wasm coverage by first passing the official W3C testsuite, then later verifying against SpecTec (formal Wasm spec)
- Arbitrary crate verification - any Rust crate that compiles to Wasm should be in scope
- Building our proof library codelib, to make verifying increasingly complex programs tractable
We would love to hear the community’s feedback on Talos and comments on the state of formal verification right now. Contributions are also welcome!

value: Show HN: Talos – Open-source WASM interpreter for Lean

author: mfornet


value: Show HN: The Hidden Structure of the Euro System


value: ottilves

value: Show HN: Display.dev – the agent-agnostic workspace for HTML and .md artifacts

author: ottilves


value: MarkBekooy

value:
Have you been at a festival or bar and had to shout your drinks order over the loud music?
I have and it was annoying... So I developed http://shoutfordrinks.com to quickly create an order to show at the bar.

value: Show HN: Shout for Drinks – Don't scream your drinks order at festivals/bars

author: MarkBekooy


value: vforno

value: Show HN: Loomabase – Offline-first column-level CRDT sync for SQLite + Postgres

author: vforno


value: An async load testing cli with inbuilt storage for session history, and a tui for viewing stats.

value: Show HN

title: Show HN


value: ruihanli

value: Show HN: Cost-Xray – per-token cost attribution, by tool, skill, prompt and more

author: ruihanli


value: bahbahbahbah

value:
I was screwing around with trying to mash up puzzle types and reinvented what I'm calling Sudoku Word Search. It's a letter-sudoku puzzle with words hidden in the puzzle, and you have to deduce where the words are in order to solve them.
As in, the puzzle does not have a unique solution using sudoku logic alone. You must use one of two forms of hidden word logic to finish the puzzle. 1) Deduce where a word must be placed and add letters, or 2) deduce where a word may not be placed and restrict letters. To keep it more sudoku like and aid in solving, every row, column, and box has at least one letter of a found word.
In playtesting I thought it was fun, although at times very difficult for me (I'm not an expert sudoku player), so I thought I'd build it out to share.
The puzzles are generated by creating racks of 9 unique letters, finding all words that can be made with those letters, generating sample grids, finding the words in them, throwing out candidates that don't fit the word placement criteria, then carving the board by removing letters until two constraints hold: we have >=2 solutions by sudoku logic and exactly 1 solution when the word search logic is added. Overall about 60000 puzzles are generated and thrown out for every sound one.
I used Claude pretty extensively for the code, which includes:
- Puzzle generator
- Puzzle solver
- Puzzle explainer
- Static website (Cloudflare)
- Online puzzle player (local storage)
- Online static puzzle walkthrough
- Print book layouts
- PDF layouts
Overall, it's been a lot of fun to focus on for a few weeks.
https://www.sudokuwordsearch.com

value: Show HN: Sudoku Word Search," hidden words required to solve letter-sudoku

author: bahbahbahbah


value: mantyx

value: Show HN: Mantyx – Managed Agent Runtime

author: mantyx

title: Show HN: Mantyx – Managed Agent Runtime


value: amordecosmos

value: Show HN: Zedmail – transactional email API outside US jurisdiction (CASL/GDPR)

author: amordecosmos


value: realmofthemad

value: Show HN: Gerrymandle - Daily puzzle game where you redraw electoral districts

author: realmofthemad


value: cybrjoe

value: i've been dogfooding some version of this idea for a few weeks now and i'd thought i'd share my re-implementation from this weekend. basically it's a webserver that controls and unlimited amount of codex (preferred) or claude agents. it allows me to context switch more easily, as well as kick off tasks and instruct agents while i'm away from my desk. the storage is sqlite and persistent, regardless of agent status. for codex you can upload images and queue messages just like the CLI. i'm on mac so i've streamlined installation via brew, but open an issue if you have problems on another platform. hope someone finds it useful!

value: Show HN: Gorchestra – resume local AI coding sessions from your phone

author: cybrjoe


value: Show HN: TypeMorph – Browser-local JSON schema converter (80 formats, no server)


value: barrus

value: Show HN: An open-source DSL for building FHE apps without a crypto background

author: barrus


value: Show HN: RottenFiles a lightweight Windows app that auto-deletes files


value: kaandemirel

value:
Hi HN,
I built Language1 (https://language1.app), a word game where you play "reverse Taboo" against an LLM.
How it works: You are given a target word (e.g., "Apple") and a list of forbidden "taboo" words (e.g., "fruit", "red", "tree"). Your goal is to write a prompt that guides the LLM to output the exact target word, without using any of the forbidden words.
The Benchmark Goal: I am developing this project with the plan of using the gameplay data to build a benchmark dataset. The goal is to test and evaluate LLM capabilities when processing unclear prompts, metaphors, analogies, and vague explanations under semantic constraints.
Game Modes:
Single Player: Play through a pool of challenges to test your prompt precision. You compete against other players globally across attempts, solve time, and token consumption (measured via standard cl100k_base encoding). You can play instantly without registering, or sign in (one-click Google login) to submit scores to the leaderboards.
Multiplayer Races: Real-time lobbies of up to 10 players racing through 3 rounds. Note: Since the game is new, public lobbies might be empty at first, but you can create private lobbies to play with friends.
Available Models:
Anonymous users play with the default Gemma 3 Instruct model. Free registered users can choose between multiple models to test and compare reasoning styles, including Llama 3 8B, Liquid LFM 24B, Amazon Nova Micro, and Ministral 8B.
The Tech & Guardrails: The app is built with a React frontend and a Node.js/AWS Lambda backend. To keep things fair, we built a validation guard that parses input clues to block easy bypasses like letter-spacing (e.g., "A-P-P-L-E"), translations, cyphers, and base64. You have to rely purely on semantic reasoning to guide the model.
The game is completely free, has no ads, and is playable instantly in the browser.
I'd love to hear your thoughts on the gameplay and see what creative semantic tricks you use to guide the LLM!

value: Show HN: Language1 – Benchmarking LLM comprehension of vague prompts via Taboo

author: kaandemirel


value: mourner

value: SunCalc is one of my first open source projects — made the first commit 15 years ago and it had its share of wonderful uses ever since, but it's been somewhat neglected in recent years. Now that modern AI tools give me the ability to catch up on years of accumulated tech debt and user issues, I finally have the capacity to revive projects like this and keep them in excellent shape.<p>v2 is a new version that improves the calculations accuracy by 5x for the Sun and by 20x for the Moon, verified by an extensive test harness vs ground truth from US Naval Observatory, in addition to fixing a ton of issues and modernizing the distribution with ESM. Hope you enjoy it.

value: Show HN: SunCalc v2 – a tiny JavaScript library for sun and moon calculations

author: mourner


value: jeidoban

value: Show HN: Ironsmith – Generate personal native Mac apps with local LLMs

author: jeidoban


value: bashierkh

value: Show HN: NILScript – OpenAPI for agent actions, so hallucinations can't write

author: bashierkh


value: grove

value: Show HN: Use math to track distributed progress without a central coordinator

author: grove


value: yogevbentov

value: Show HN: The AI assistant I could give my non-technical friends

author: yogevbentov


value: CassiniResearch

value: Show HN: Juno – free open-source Mac dictation with live transcriptions

author: CassiniResearch


value: psnyder

value: Spun up a local Clerk emulator for testing and local developer stacks. Previously, engineers were sharing a single "preview" Clerk instance for local development, which led to a poor local dev experience for our team +Can also be used for isolated integration testing

value: Show HN: Local Clerk emulator for isolated dev environments

author: psnyder


value: argoeris

value:
We just open sourced Multiplayer: https://github.com/multiplayer-app/multiplayer
Multiplayer is a local debugging agent that captures full-stack, unsampled session data when something breaks in production and routes it to your coding agent to generate a fix. It runs on your machine, next to your coding agent. A few things that make it different from connecting a coding agent directly to your observability stack:
- Session-based collection instead of always-on(we only capture when something goes wrong)
- Nothing gets sent anywhere until we've identified a new issue worth surfacing
- Data is pre-correlated across service boundaries before it reaches the agent
- Issues are deduplicated before routing
- Includes what standard APMs strip out: request/response content and headers, release metadata, an issue summary, etc.
We wrote about why we're open sourcing now here: https://www.multiplayer.app/blog/multiplayer-is-now-open-sou...
Short version: we believe in this community, and we think the root cause of low-quality AI-generated PRs is the same data problem we're trying to solve.
Happy to answer any questions.

value: Show HN: Multiplayer – open-source local debugging agent, unsampled runtime data

author: argoeris


value: brunaxLorax

value: Show HN: Modelparams.dev: AI Model Parameters Database (UI, API, NPM)

author: brunaxLorax


value: ramoz

value: Show HN: A dead simple ADR skill workflow

author: ramoz


value: spillcoffee

value:
Hi HN,
After completing a Shopify webhook project where I got tired of triggering events manually to test edge cases, I built
https://FlurryPORT.io to help with integration testing and debugging of webhooks.
FlurryPORT is a cloud application that is always available to receive webhooks from a provider.  Prevents you from only
noticing payloads when you're listening and triggering only the happy path for your application.  A lesson I learned the
hard way with Shopify's orders/updated, not knowing the true cadence of updates from the client I was building the
application for. Now you can setup a webhook and listen to relevant traffic before writing a single line of code.
All captured request bodies and headers are encrypted at rest using AES-256-GCM; query string variables are plain text.
To aid in application design webhook captures can be selected in batches to be grouped into collections and "Copy for AI".  The
"Copy for AI" allows you to send your captures to AI to help figure out the best set of captures for your application.  There
is a best effort to scrub/redact PII from the payloads using this feature (although, it would be good to spot check).
There is a CLI (npm install -g flurryport) that can be used as a bridge to localhost.  The CLI connects via a
Personal Access Token (PAT) obtained from the account you wish to connect.  Registering of localhost can be done with a
PAT to help with setup, but access to any other account function is restricted.  Control of which webhooks arrive is controlled
within the  account issuing the PAT.
The routing model is "everything arrives" a bare target will receive everything sent to your webhook.  But, you can create transformations
and binding pairs using a JSONata predicate that scopes reshaped payloads to an endpoint target; not limited to localhost.  If, nothing matches
your predicate then it is forwarded as is.
A disconnected localhost will not receive webhooks sent while disconnected; this is to mimic a real world scenario where the server is offline.
There is a live free demo found at https://flurryport.dev/try, captures live for ~1 hr, payloads are not encrypted.  But, if you like your
work there when signing up an account they will be imported and encrypted to give your account a good start.

value: Show HN: FlurryPORT – Capture and replay webhooks to localhost

author: spillcoffee


value: dipankarsarkar

value:
I am obsessed with ORMs and the simple reason was that I didn't want to keep using postgres or mysql on my local system.
Jk, The real reason has always been to enforce access policy, do easy CRUD interfaces and so on.
Now with all these agents being built, I figured they should not be making SQL calls directly (just like junior eng :P).
So i present ormAI, this is the official blurb.
OrmAI wraps your existing ORM models in a policy-enforced runtime. Your agents get typed tools for querying and writing data — while you keep control over what they can see and do. No raw SQL. No prompt injection into your database. Just safe, auditable, tenant-scoped database tools.
I did benchmark it with Text to SQL tools, and for obvious reasons this did not do badly at all.
Check it out, write more AI agents.

value: Show HN: Give Your ORM Superpowers

author: dipankarsarkar

title: Show HN: Give Your ORM Superpowers


value: primaprashant

value: Show HN: Talking to My Terminal with Local Speech-to-Text and Pi Coding Agent

author: primaprashant


value: praneethpike

value: A local folder system based AI canvas app. AI first obsidian + Notion + Miro.

value: Show HN: A local first agentic canvas workspace

author: praneethpike


value: Show HN: Oh – verbatim memory and insights of all your past vibecoding sessions


value: giandlr

value: Show HN: Markup – A private cross-service home for AI-generated HTML

author: giandlr


value: nvk

value: Show HN: 10x better performance from the Coding Harnesses with LLM-wiki

author: nvk


value: mawrtini

value: Show HN: A simpler way to synthesize user feedback

author: mawrtini


value: zeborg

value:
Hey everyone!
I've recently published KubeKosh, which is a self-hosted open-source Kubernetes lab consisting of 85+ unique practice scenarios for beginners as well as CKA, CKS, and CKAD preparation.
New scenarios can be created and contributed by fellow users in JSON format, and I've also mentioned its schema in the documentation for helping new contributors create and test their own scenarios.
To quickly try it out, you just need to run this 1 command. It spins up the entire lab in a single Docker container within ~15 seconds:
docker run -itd --name kubekosh --privileged -p 7554:80 zeborg/kubekosh:latest
I'd appreciate new scenario contributions dealing with situations which are common in production environments, and which may be new or insightful to beginners and experts alike. Please refer to README.md for screenshots and more details about the project.
Thanks for your time and attention!

value: Show HN: KubeKosh – Self-Hosted Kubernetes Playground in a Docker Container

author: zeborg


value: possiblelion

value:
just a fun hobby project to learn webrtc and p2p networking:
loads a real goldsrc .bsp map file (the same format half-life and cs 1.6 used), parses it in javascript, rebuilds the geometry for webgl with three.js, and runs a from-scratch reimplementation of valve's player movement so the surf feels right. multiplayer is peer to peer over webrtc with no game server.<p>it uses trystero, which does webrtc peer to peer and uses public relays only to introduce peers to each other, no game server in the middle. everyone in the same room name shares a session, broadcasts their position about 20 times a second, and you see each other surf.

value: Show HN: WebRTC P2P networking based Counter-Strike 1.6 on the web

author: possiblelion


value: pigno

value: Show HN: Pg-tail – tail -f for PostgreSQL

author: pigno


value: Pi extension that uses ACP (https://agentclientprotocol.com/) to connect to any Coding agent and helps you Maximize AI Credits across multiple subscriptions like Cursor, Codex, ClaudeCode, RovoDev and more

value: Show HN: Pi Extension to Maximize AI credits across Cursor, Codex, ClaudeCode


value: Show HN: Asili – open-source, privacy-first in-browser DNA PGS scoring


value: XCSme

value: Show HN: One hundred LLMs Generating a HTML/CSS Solar System

author: XCSme


value: vierliam

value:
Hey, I've built a small tool and OSS repo allowing users to view/transform/share JSONL traces.
There's also a CLI you can use to upload traces from sandboxes and/or share them with Claude/Codex for analysis.
Zero Knowledge - browser encrypted data only the user owns
Feedback welcome!

value: Show HN: Jsonl-tools – secure paste bin for agent run traces

author: vierliam


value: Show HN: Motion-contact-sheet – give a coding agent eyes for motion


value: shpran

value: crunchbase is $49 a month, which is fine if your an investor, but doesn't make sense for everyone else. So I built this website, the way it works is when u suggest a startup or flag an error, I have an internal dashboard where I can deploy AI agents to write a profile or fix the errors. These AI agents cross reference public info from across the web to find out metrics about the company.

value: Show HN: StartupWiki, a free alternative to crunchbase/pitchbook

author: shpran


value: luqtas

value: Show HN: Emacs log-mode (cheap copy of Logseq)

author: luqtas


value: imtaimoorkhan

value: Show HN: We ran 74 popular MCP servers in microVMs to see what breaks

author: imtaimoorkhan


value: kevinsschmidt

value: Show HN: Binked – A hand replayer for live poker

author: kevinsschmidt


value: frb

value: I grew tired of numerous Chrome/Playwright/Puppeteer skills and MCP plugins, which for me felt quite heavy and unstable.<p>So I built this to allow my agents to efficiently test and work with websites.

value: Show HN: Vibesurfer – a token-efficient browser for AI agents, no Chromium/CDP

author: frb


value:
Hello HN,
I built an open-source reverse-engineering AI agent, that can write requests-based(no browser) automation/scraper scripts on its own, all we have to do is, to normally browse the website once.
This makes it a lot easier to create and maintain the scripts. This is not a completely autonomous agent, you can pause, talk, guide the agent on its RE path.
Despite the limitations of this approach, up to 60%-90% of websites can be automated/scraped with just raw requests and TLS-spoofing(links to sources provided in the blog)
The tool successfully ran against popular websites like, bookmyshow, makemytrip. And to test it in the open, it was able to produce scraper solutions for 2 problems posted on r/webscraping in a single try.
As the scripts provided by the tool are requests-based, you can expect a 10-100x speed increase, and reduction of 5-7x memory footprint in your existing browser-based automations and scraper workflows.
Github: https://github.com/StoneSteel27/AutomatiQ
Blog: https://shiny-sushi-116.notion.site/automatiq
Demo video: https://www.youtube.com/watch?v=OfMvAQP5pkM

value: Show HN: I built a reverse-engineering agent for the web


value: scurnus

value: Show HN: HumansMap – Explore family dynasties, relationship, org networks

author: scurnus


value: raphjacksun

value: Show HN: TidyPress – a public interface for your repos and work

author: raphjacksun


value: amiyapatanaik

value: Show HN: Typestream – A pure pay-as-you-go voice dictation API for web apps

author: amiyapatanaik


value: JamesJulius

value:
I made this because I got frustrated sending AI copy to friends and teammates, and seeing it lose formatting and structure. I found it worked well to instead ask the LLM to summarise its thoughts into a markdown, and share that instead.
I set it up to use the same plugins as llms, so you can share tables, mermaid, LaTeX and more. It's a pastebin for the AI era.
Try it and tell me what you think! It's forever free to share public pastes, and I'm exploring team plans to organise brainstorming.

value: Show HN: Markdrop, a way to share formatted AI Markdown with friends

author: JamesJulius


value: smashini

value: Show HN: I Made OpenClaw Employable

author: smashini

title: Show HN: I Made OpenClaw Employable


value: jskull

value: I built electron-expose while working on an email client for myself and getting tired of writing the repetitive ipc bits, i tried a few libraries and nothing really clicked so i built my own.<p>It generates the main/preload/types bridge from the functions you explicitly expose with TS decorators. The goal is to just make the repetitive bits easier without any additional schema validators etc, imo those can be done in the function themselves with the library that the user chooses (Zod for example).

value: Show HN: electron-expose – Make Electron IPC boring with TypeScript decorators

author: jskull


value: oabolade

value:
I have been running into the same problems recently instrumenting my LangChain and CrewAI agent pipelines. If something goes wrong with a tool call, there was no way to way to prove what the agent did, in what order, and whether the logs have been modified. Observability platforms like LangSmith and Langfuse are great at optimizing for agent behavior, tokens and costs but they do not produce legally defensible and auditable artifacts. That's the reason why I decided to build RootSign, an SDK that instruments your CrewAI and LangGraph agents and produces cryptographic audit logs for CrewAI and LangGraph agents. RootSign adds a cryptographic hash chain to every tool call. If any record is modified after the fact, "rootsign verify" detects it.
What it does:
- SHA-256 hash chain across every Action record in a session
- Human-in-the-loop checkpoints with Approval records for certain agent actions
- PII redacted before hashing (StandardPIIConfig out of the box)
- Works with LangGraph and CrewAI — AutoGen coming soon
- Local first (Postgres + Timescale) — no cloud dependency
What it doesn't do (yet): compliance dashboard, cloud backend, policy engine, all on the roadmap.
Please try it out on the Github repo, contributions and feedback are always welcome.

value: Show HN: Tamper-evident audit logs for LangChain/Crew AI agents

author: oabolade


value: dloss

value: Show HN: Kelora – query and transform logs from the command line

author: dloss


value: gustavofior

value: Show HN: Foglamp – Open-source o11y for AI SDK

author: gustavofior


value: patriceckhart

value: Show HN: SDK for embedding zot coding agent in your Node.js applications

author: patriceckhart


value: kordlessagain

value: Show HN: A small, crazy fast hybrid search engine written in Rust

author: kordlessagain


value:
To get an AI to do a task well, you need to give it the right context and the right task description. I've had a lot of struggles working in a large codebase getting AI to follow the existing patterns and architecture.
So I started building a VS Code / Cursor extension that lets you quickly snap together sub prompts/instructions relevant to a specific task. After seeing the value of this, I realized you could make those sub prompts more customizable by using a liquid syntax engine.
That worked fine for a few days, until the original context blocks got stale as the project progressed. I wrote an MCP server that can update those blocks, creating a feedback loop. A few days later I added an amend option too, so the AI can write a log and decision record as it goes.
At this point I realized there were a lot of opportunities here: my AI isn't spending the first 5 minutes doing research, I've got better control over my context window, there's less irrelevant data leaking in from my agents.md file when I switch repos, I can write prompt groups for separate workflows, and so on.
The last blocker for me was that I actually use Claude Code and not VS Code much anymore. So I figured out how to hook into the external editor command to open a TUI directly from CC and write a prompt from there.
Now I'm happy to finally share it after spending the last 5 months perfecting it. Would love for you to try it and let me know what you think, even if its not something for you - why?
More details see GH: https://github.com/simondevries/prompt-foundry
install vscode: https://marketplace.visualstudio.com/items?itemName=sdevries...
Install OpenVsx: https://open-vsx.org/extension/sdevries/prompt-foundry

value: Show HN: writing tasks with focused context + instructions = sharper AI


value: perkovsky

value: Show HN: NGB, an open-source .NET platform for document-driven business apps

author: perkovsky


value: anthonysarkis

value: Show HN: DOS – a referee between AI agents that doesn't believe their "done"

author: anthonysarkis


value: A drop-in AI preview for furniture stores. Shoppers upload a room photo, place your products in context, and check out with more confidence.

value: Show HN: Furniture Visualizer for Retailers


value: I made this while checking model graded answer and helped me to check the odd cases by hand. Not sure if it’s useful to anyone else.<p>TL;DR: it breaks an LLM judge run into claims->evidence->verdicts and flags when a verdict is not supported by the evidence, so i can check it manually

value: Show HN: I made a small helper for checking model-graded answers


value: Kaensu

value:
For the past few years I’ve been doing something between digital archaeology and forensic anthropology, but for music formats. The hundreds of weird, half‑documented, tracker, chiptune, console, and game‑audio formats that accumulated from the 1980s through the 2000s.
Most of them were never documented. Many are awkward, many feature-incomplete. Many were one-off for, say, Amiga or Atari ST games, and at best only a couple players like UADE or NostalgicPlayer load them.
Some are just raw sound-chip register logs.
And yet they’re culturally important: they’re the DNA of the demoscene, early PC gaming, and entire ecosystems of trackers.
I wrote audio.1.sg for Detect-it-Easy that recognises files in those formats. That's over 400 retro/exotic audio with signature matching, header validation, pointer sanity checks, pattern parsing + sanity checks, chip-log decoding, format-specific heuristics. Not every one has everything (still some with just an extension detection!), but it's an ongoing project.
Some detections just had to be pretty shaky because of the simplicity of their design. ¯\(。⊿°)/¯
I've collected the attributions for each format, so it's easy to know who made what, and maybe easier to search in case of generic naming.
Try it on modland.com or your fav tracker/Speccy/Amiga/AtariST/MSX music collection, see what comes up!

value: Show HN: Digging up 40 years of tracker/chiptune formats (audio.1.sg)

author: Kaensu


value: will-yatori

value:
I think that merchants should NOT have to pay 2-3% in tx fees. TO do this I had to build a mobile app (the pay interface side) and QR codes that can run anywhere HTML does (the receiver side).
The next step is a free POS that has 0 fees to accept stablecoins from the payment app side.
Is there a market for 0 tx fees, free signup, and 0 hardware POS system for the underbanked, unbanked, and current users of traditional systems?

value: Show HN: I made a stablecoin app that works with checkout QR codes

author: will-yatori


value: jerrodcodes

value: We built an end to end knowledge system that keeps up with complex cross-repo codebases. Our intelligent context mapping system provides comprehensive knowledge bases that your team can host internally/externally or query via MCP.

value: Show HN: A knowledge engine that keeps up with AI driven code

author: jerrodcodes


value: Show HN: 1pager: Fixing the AI verbosity problem


value:
last week i was "working" on 5 things and i was completely overwhelmed to the point that i literally didn't know what to do.
i did use ai chatting apps (ChatGPT, Claude, Gemini, etc..) and explained to them what i have in my mind but they didn't help me the way i wanted to, idk but they all seem to have a setting or something that makes them act as motivational speakers when they detect that you are overwhelmed (i even tried specific prompts guiding them to not act this way, but didn't help)
so, i thought why don't i just make the tool that will fix my exact problem? and i made ToNotDo, a one-page site where you dump what's in your mind in the text area and get a list of thing NOT to do with reasons and explanation, then what's not mentioned in the list is the thing that you should work on right now.<p>you can try it at tonotdo.cc
just note that: it's a paid tool ($1 per generation), it uses ai, the result has a list of what not to do (categorized as: postpone, ignore, revisit later, drop) and a "Why This List Makes Sense" block and a "Remember" block (a personalized wise quate, i thought it's nice to have lol)

value: Show HN: ToNotDo – a tool that helps you know what NOT to do, not a todo app:)


value: nizzyabi

value:
Hey HN! We're working on https://orchid.ai/, a proactive assistant that lives in your messages and needs zero setup / configuration.
Our users are currently using Orchid in 3 main ways:
1. Automations: Orchid can integrate with your tools via MCP and run tasks however often you need to. some cool examples we've seen include: daily email & calendar digests, NBA/F1/Soccer live updates, linear tasks reminders, and email organizing.
2. One off tasks: Orchid can write your emails, coordinate meetings, book your trips, track your calories via images you send it, and even manage your socials. Since Orchid has built in memory, it knows how you like to do things, making completing tasks like this quite easy.
3. Reminders & deadlines: Orchid can pick up on reminders you give it or deadlines it picked up via your email, making things slip through the cracks much less often.
We hope Orchid can give you value and assist you in some way in your life/work.
If you have any questions about Orchid, please reach out! We'd also love your feedback if you've given it a try :)

value: Show HN: Orchid – An AI Assistant

author: nizzyabi

title: Show HN: Orchid – An AI Assistant


value: thegoodguys

value: Show HN: Myco Brain – source-traceable memory for AI agents on your own Postgres

author: thegoodguys


value: harveyhu

value: We love agent skills and use it a lot in our company. For something meant to be distilling human expertise, the human interface is quite broken.<p>So we built the best human interface for skills and open sourced it so everyone can use it and contribute. Rust app available on Mac, Windows, and Linux.

value: Show HN: Skill Studio – mine, edit, and manage Agent Skills

author: harveyhu


value: Show HN: OpenRuna–graph-linked prompts,MCP servers and agent skills


value: My take on a single feed of public web content. Start with a global feed, and filter to personalize (user prefs stored in browser localstorage, so no sign up/auth/etc.). Best effort to avoid paywalled links.

value: Show HN: Maiweb – a personalized feed of the public web


value: dmujic

value: Show HN: Agirails – Two AI agents negotiated and settled USDC payment over email

author: dmujic


value: skzv

value:
Hi all,
I recently built (and am continuing to improve) intuitivepapers.ai to help me study and understand AI research papers.
For me, it's important to build intuition for concepts, and when reading a research paper, that can take me a while. Also, papers can be unnecessarily intimidating or verbose. I also find myself having to jump around to prior papers to understand the preceding work. My motivation was to be able to read an explainer in one place that:
- explains the preceding foundations required to understand the paper
- provides intuition
- uses plain language where possible
- provides concrete implementation examples, so I can understand how the idea is actually implemented in practice
- cross references the paper against accompanying source code
I originally started building this as something for myself, but I thought others might find this helpful too.
New paper explainers are published regularly. There is a queue where you can submit and upvote papers for explaining.
At the bottom of each explainer is a feedback form where you can suggest improvements. I will incorporate these into already published explainers, but I will also incorporate the lessons into future posts as well.
Looking forward to everyone's feedback, and I hope you find this helpful!

value: Show HN: A website to understand and study AI papers

author: skzv


value:
I was annoyed by Apples post processing in the default iOS camera app so I made my own.
This is a first version using still mostly Apple preprocessing with my own preferences applied.
Future version will change the image pipeline to  use raw sensor data.

value: Show HN: A photography app with nicer colors


value: codebytrevor

value: Show HN: Turn any photo into a Fujifilm film-simulation recipe

author: codebytrevor


value: Show HN: An atlas of China's manufacturing geography


value: coderai

value: I built a platform allowing for instant access to remote computers from CLI tools like Claude, Codex, Opencode, or any other AI chat. There are mini apps for Windows (tray), Mac (menu bar), and Linux (CLI app) generating connection code, like TeamViewer. Comprehensive security, instant access, no firewall/networking configuration. Just ask your AI to do something on your machine, and it will do it flawlessly.

value: Show HN: AI Commander – TeamViewer for AI Agents, No VPN or SSH

author: coderai


value: I am building a platform that allows users to create their own FAQ AI with their own FAQ data. It runs in a static site that can be embedded into a website.<p>Link is to the GitHub pages site!

value: Show HN: In-Browser FAQ LLM

title: Show HN: In-Browser FAQ LLM


value: salterisp

value:
For many years I was feeling my skills and my time were wasted on one-off queries.
Requests were coming from everywhere, slack, teams, tickets.
At some point I decided that it would be better to build the tool
that will save me time. So after studying the last months about AI in
general and text to sql concepts more specifically I decided to build Savvina -
my daughter's name.
Privacy was my first concern building that so I worked towards that with multiple
security guardrails. Self-hosted was another security aspect and as one can see
at https://www.youtube.com/watch?v=zK-n0cM88vI it takes less than 15 minutes to
run your first question.
Community edition can be found at https://github.com/savvina-ai/savvina
and supports PostgreSQL and MySQL.
The biggest thing I learned from this journey is that semantic layer
sometimes matters more than the LLM you choose. Or that parse-time query validation is more reliable than confidence scores.
If you're tired of being the SQL middleman — or just want fast insights from your data try it on real schemas and tell me where it breaks.
File issues, start discussions.

value: Show HN: After years as data engineer, I built the tool I wish my colleagues had

author: salterisp


value: Marciok

value: Show HN: Prompt Fusion Using Dags and OpenRouter

author: Marciok


value: autobe

value:
Made typescript-go (TS v7) toolchain to make `typia` arrive in the new era.
As `ttsc` automatically detects plugin libraries, you no more need to suffer from complicate setup process. Take advantages of TypeScript compiler plugin libraries like `typia`.
It also contains its own linter library `@ttsc/lint`, that is working on the plugin system of `ttsc`. It is also to make `typia` alive.
> > If you're looking for a `vite`/`rollup`/`webpack` plugin for new TS v7, ttsc supports the way. Also, as `@ttsc/lint` is one of the plugin library of `ttsc`, re-using pre-parsed compiler ASTs, so actual computation cost is near to 0.

value: Show HN: I Made TTSC, TypeScript v7 ToolChain for Plugins Like Typia

author: autobe


value: priyanshu-mit

value: Show HN: Browser calls with live translation in the speaker's cloned voice

author: priyanshu-mit


value: amaldavid

value:
I built this because I kept generating HTML/Markdown reports from Claude Code/Codex and needed a permanent share link instead of a localhost tunnel. Pagecast is a local CLI that publishes those files to your own Cloudflare Pages account.
It supports Markdown and HTML, stable URLs, renaming, republishing to the same URL, and watch mode for continuous updates to same file. It is MIT licensed.
The main design choice is that there is no hosted Pagecast account. It uses your Cloudflare account and deploys there directly and has claude code and codex integrations as skill/hooks.
Basically it can be used as a replacement for codex sites or claude artifacts

value: Show HN: Pagecast – Publish Markdown/HTML Reports to Cloudflare Pages

author: amaldavid


value: jthorare

value:
ConnectAI connects and ingests all the data from all of the tools you currently use and makes it queryable by agents. After connecting your tools it works to build a context retrieval and memory management db. That way when your agent asks something like "what happened to the deal with ACME corp" it's not having to query against Salesforce, Gmail inboxes, Slack messages, etc and piecing together what happened and missing out on some valuable information.
Last week I posted about ConnectAI as a SaaS offering for a company brain and got some feedback that a self-hostable, fully private offering would be game changing so that's what I built. I was already thinking that it'd be hard to
https://www.npmjs.com/package/@connectai/selfhost
Install with "npx @connectai/selfhost run" and it will walk you through getting setup and connected to your company tools and any feedback is very much appreciated.

value: Show HN: Self-Hostable Company Brain

author: jthorare

title: Show HN: Self-Hostable Company Brain


value: kalashvasaniya

value: Show HN: The AI App That Does the Work

author: kalashvasaniya

title: Show HN: The AI App That Does the Work


value: sestarkman

value: Show HN: I built a daily flag quiz in honor of the World Cup

author: sestarkman


value: sonOfHades

value: SHOW HN: I built a "living proof-of-work" profile for builders

author: sonOfHades


value: buremba

value: Show HN: Open-source back end for multi-user AI agents with shared memory

author: buremba


value: dlindh

value: Show HN: AutomateOrNot – decide if you should automate a test

author: dlindh


value: jankdc

value: Show HN: bote - A fast, modern and low-memory approach to processing a big JSON

author: jankdc


value: Show HN: OSymandias – Open-source runtime for multi-agent AI systems


value: smalltorch

value:
Torum is a self-hosted, Tor-native discussion forum modeled after Hacker News. It runs entirely as a Tor hidden service, accessible only through the Tor network via a .onion address. All data is stored locally in an encrypted SQLite database, and the entire application is managed through a single interactive shell script.
Find here https://gitlab.com/here_forawhile/torum

value: Show HN: Torum – your own portable HN clone

author: smalltorch


value: turtlesoup

value: With more traffic moving off-web and into LLMs, I got curious about what traces we leave "in the weights". My design partner and I built a site in the past few weeks that checks recognition across frontier and small models. It queries many of them in parallel, clusters the responses, and tells you how strongly they recognize you. Happy to answer any questions here!

value: Show HN: Are You in the Weights?

author: turtlesoup

title: Show HN: Are You in the Weights?


value: dsstudios

value:
I've had more than six consultations with top veneer dentists in NYC, Turkey, and Mexico. All six gave me a different recommendation. Not one of them offered to show me what I'd actually look like with veneers.
So I tried ChatGPT, Gemini, and Grok. They all changed my face, and none of them let me compare options to figure out which smile I'd actually want.
So I built it myself.
Submit a photo and get back ten veneer options in under 60 seconds. Upload as many photos as you want and see how you'd look across different settings, outfits, and lighting.
This is the best preview tool I've been able to find anywhere online. I'm trying to build PhotoAI but for teeth, with the long term goal of being good enough that dentists use it with their own patients.
Please feel free to share any feedback or suggestions you might have!

value: Show HN: Veneerly – See your own face with veneers before you commit

author: dsstudios


value: sahin

value: Show HN: Clear lang – The spec is the code

author: sahin


value: chnbydigi

value:
I was building a small LLM-powered side project and forgot to account
for my system prompt tokens. 800 tokens × 2,000 requests/day × input
token rate = $340 invoice I wasn't expecting.
Built APICalculators to avoid doing this math in spreadsheets every time.
It now covers 16 calculators: LLM APIs (GPT-4o, Claude, Gemini), vector
databases (Pinecone, Qdrant, Supabase), serverless (Lambda, Cloudflare
Workers), auth providers (Clerk, Auth0), payment processors (Stripe vs
Paddle), and cloud VPS comparison.
Everything runs in the browser — no signup, no data sent anywhere.
Would love feedback on what's missing or wrong.

value: Show HN: I built a free API cost calculator after a $340 surprise invoice

author: chnbydigi


value: lylo

value: Show HN: Pagecord Spotlight – discover trending independent posts on Pagecord

author: lylo


value: HELENENDORFSKY

value: Show HN: Sycloop – An AI marketplace that closes multi-party barter loops

author: HELENENDORFSKY


value: minicliprocks

value: Show HN: I built a multiplayer dominoes game

author: minicliprocks


value:
PinLeads is a lead generation platform for finding business contacts and building prospect lists.
Search for businesses, collect contact information, filter results, export leads to CSV, or send them directly into your existing CRM and automation workflows.
Website: https://pinleads.org

value: Show HN: PinLeads

title: Show HN: PinLeads


value: seandotexe

value: With AI, it's faster than ever to ship a marketing site... but most of what gets generated is slop that was never built to be found. Plus the tools meant to catch that fall short: most SEO auditors cost money, don't play nicely with your agents, or tell you what's wrong without telling you how to actually rank for SEO and GEO (Generative Engine Optimization: being cited by AI search like ChatGPT, Perplexity, and Google AI Overviews).<p>crawlie fixes that! It's 100% free, it's local-first, it's agent-native (MCP baked in!), and every issue it finds comes with why it matters and how to fix it.

value: Show HN: Crawlie – Free open-source SEO audit tool for humans and agents

author: seandotexe


value:
Hello,
I've created this project to simplify the provisioning of Hermes on Hetzner VPS.
The goal is adopting good security defaults to deploy Hermes Agent on Ubuntu 24 LTS + Tailscale.
I've added also backups and the optional installation of Mnemosyne as light memory provider.
I'm currently working on it, any feedback is appreciated

value: Show HN: Hermzner – Provisioning an Hardened Hermes Agent on Hetzner VPS


value: leonagano

value:
I built a game where you do exactly one thing:
Press and hold a button for as long as possible
That's it

value: Show HN: Press and Hold

author: leonagano

title: Show HN: Press and Hold


value: 337+ MCP tools — weather, crypto, finance, web search, DNS, colors, AI chat, text analysis, calculators, and more. $5/500 calls, each call 1 credit.

value: Show HN: MCP tools in one server – pay-as-you-go, no subscription


value: declanjackson

value: Show HN: AA-Briefcase: a frontier knowledge work evaluation

author: declanjackson


value: khanhhuunguyen

value:
I built a UI framework named Domphy because I could not learn React although I tried many times. I mean I could not understand React code which is hidden behind multiple layers, especially when some of them use React ecosystem libs. Maybe I am an architect turned developer, so I had no foundation of programming, or I expected something clear and clean.
I just think that UI should be simple — HTML and JS are enough and just need some way to make it stateful instead of making it more complicated. My idea: just using JS objects to reflect HTML, and using functions for state. When I need to reuse a component I had one more concept — just make a partial (I call it a Patch) to add props to the main object (but native props still win). With a component-based approach you get deep nesting and exploding props, but with patches you don't. The example below:

  import { ElementNode, toState } from "@domphy/core";
  import { tooltip } from "@domphy/ui";

  const count = toState(0);

  const App = {
    div: [
      { h3: (listener) => `Count: ${count.get(listener)}` },
      {
        button: "Increment",
        onClick: () => count.set(count.get() + 1),
        $: [tooltip({ content: "Add one to the count" })],
      },
    ],
    style: { display: "flex", gap: "8px", alignItems: "center" },
  };

  const root = new ElementNode(App);
  root.render(document.getElementById("app")!);

Right now I am the only one using Domphy, for around a year, for creating SketchUp and Revit plugins in the AEC (Architecture, Engineering, Construction) industry. I created Domphy before AI code generation took off, to make code humans can read and understand clearly, but now AI can build UIs with React well, so sometimes I feel my work is meaningless. But I still use Domphy for my apps, because I feel more confident when I need to read and edit UI code when the AI gets stuck.

value: Show HN: Domphy – plain-object UI for tool apps, AI-correctable output

author: khanhhuunguyen


value: sricola

value: Show HN: Drydock – VM Sandboxes for macOS Autonomous Coding Agents

author: sricola


value: tobypadilla

value:
Hi all! I was recently doing a live stream session at Build and created the start of a tool called Flashback. I wanted a way for agents to look through the history of popular design so you could reference different trends throughout time. I didn’t finish on the stream, but I kept coming back to the idea so ended up shipping it as a GitHub pages powered Skill and human browsable web site.
I think it’s really interesting to see how design has evolved since 1900, and I learned a lot in this process.
The repo is here: https://github.com/toby/flashback
And the original stream is here: https://youtube.com/watch?v=Wn5r4uqfsGY&t=7518s

value: Show HN: Flashback – an agent skill that references 127 years of design trends

author: tobypadilla


value: Show HN: Mrs-Hybride-PQC – Hybrid Kyber1024 KEM 5-6x Faster Than HKDF-SHA256


value: caudena

value:
Hi HN,
We build agents in Elixir. We kept running into the same issue and found there is no observability for agentic systems.
We decided to take the best aspects of LangChain, LangGraph, and DeepAgents and put them into Elixir.
BeamWeaver comes with an OTP-native design and:
- agents and tool calling
- graph workflows
- checkpoints and resumable execution
- memory stores
- retries, fallbacks, interrupts, and human review
- typed streaming events
- provider adapters for OpenAI, Anthropic, Google Gemini, xAI, and Moonshot/Kimi
- fake/replay models for deterministic tests
We're also building observability on top of it through WeaveScope, which we'll release very soon.
BeamWeaver gives Elixir teams the tools needed to build advanced agentic systems without pushing the hard parts into Python services.

value: Show HN: BeamWeaver – LangChain/DeepAgents-style agents and workflows for Elixir

author: caudena


value: samuria

value: Show HN: Drift

author: samuria

title: Show HN: Drift


value: qainsights

value: Show HN: Iamspeed.dev – Fast.com Style but for LLMs

author: qainsights


value: Show HN: Building Cursor for Traders

title: Show HN: Building Cursor for Traders


value: neel-m

value:
Hey HN, I built a free tool that lets you sign and upload your iOS project binaries, and serve temporary web pages to sideload on your iPhone straight from Codex Mobile, Claude Code remote control, or any coding agent of choice. No need for VPN or simulator streaming.
The web page expires in 30-min but you can access all your builds on our dashboard.
Get started with: brew install milq-ai/tap/sqim

value: Show HN: Sqim – install your iOS builds from Codex mobile without VPN

author: neel-m


value: chadwittman

value: Used to sit around the boys and guess hoopers colleges, thought it would be fun to do with the World Cup. Is it challenging enough?

value: Show HN: Guess the World Cup players' home club

author: chadwittman


value: xytom

value: Show HN: Coding Tools MCP – Give any LLM agent the ability to code

author: xytom


value: talksik

value:
Hey folks,
So you basically send quick video / audio clips back-and-forth. And because of the mechanics, it feels conversational and actually replaces meetings (unlike Loom, which is fire and forget):
- kill standups
- kill the quick syncs or design feedback
- kill unnecessary kickoff meetings, announcements
- kill code review meetings, talk through complex things
It's helped my team move stupid fast, I'm curious what y'all think. All I will say is Loom is not great for back-and-forth, but this was built for it.
Some other things:
- keyboard-first
- supported on web, macOS, Windows (I recommend the desktop app for full features)
- supports huddles / live calls
- supports markdown, and lightweight tasks feature (for noting action items)
- supports screen share video
And there's a free tier, so you can get going with a small team.
Mobile is in progress, contact for TestFlight access.
I'll bet some of you may use it to replace slack, teams, zoom. Because it's more effective to speak through issues and resolve them without needing a meeting, and without needing walls of text in slack.

value: Show HN: Kill 80% of meetings by sending short clips back-and-forth

author: talksik


value: wibbily

value: Show HN: FLIP TABLE 2026

author: wibbily

title: Show HN: FLIP TABLE 2026


value: ankleshh

value: Show HN: Sakha – An AI employee – onboarding tool for businesses

author: ankleshh


value: Show HN: A/B testing LLM silence with one system-prompt toggle


value: tomchill

value: Show HN: Validate your idea from Reddit and TikTok

author: tomchill


value: devinjameson

value:
Hi HN,
I'm the creator of Foldkit, a TypeScript framework built on Effect and inspired by the Elm Architecture.
This page compares the same pixel art editor implemented in React and Foldkit side-by-side.
Rather than focusing on benchmarks or isolated examples, I wanted to compare what building and maintaining the same application feels like in each architecture. The comparison includes state management, UI, async operations, side effects, application structure, and testing.

value: Show HN: Foldkit vs. React, the same pixel art editor implemented in both

author: devinjameson


value: ascended

value: Show HN: Protect your Go, Arch and AUR from Malware with a free firewall

author: ascended


value: fragmede

value: Ever right click an image on your mac and then try to use pbpaste > destination.jpg and it didn't work? Or try to pbcopy < nyan.jpeg and not be able to paste it?<p>Introducing: pbi

value: Show HN: `pbi`, an image aware pbcopy/paste for macOS command line users.

author: fragmede


value: WolfOliver

value:
Hello HN,
I would like to share with you linkedrecords.com - an open source backend as a service I'm working on since some time now. You can think of it as an firebase/convex alternative with an interesting twist.
In 2018 I needed to write large software requirements/architecture documents in Google Docs. While I was annoyed by the limitations of Google Docs back then (no captions on figures, no automatic heading numbering, slow when docs are bigger,...) I was still fascinated by the real time collaboration features of it. So I've started a quest to understand how it works and I begun to implement an alternative to Google Docs.
I was convinced that this kind of real time collaboration is the future so I've given it much thought how I could make this as generic as possible so I could use it in all future tools I would build.
In the same time I was playing around with firebase (surprisingly you can not build a google docs alternative with firebase that easy as their real time collaboration does not provide merging text but rather just JSON). And back then I was also convinced that backend as a service is the right way to go. I was thinking that one of the most important reason we were still writing custom backend code is because of authorization.
I also was faced with another problem when trying to make the backend as generic as possible: relations between entities are also domain specific. E.g. A Documents can have many comments.
Luckily I was intrigued by another concept back in 2018 it was called web 3.0. Back in 2018 this had nothing to do with crypto. It was used as a term to refer to the semantic web and the resource description framework as one of its standards. There are also some RDF implementations which I could have reused but they are all XML and mostly Java based. I needed something light. Instead of implementing my own RDF product I took the idea of the RDF triplestore and came up with my own interpretation of it.
Using concepts like: triplestores and schema-on-read, I came up with a system that does not has any business logic in its backend and while working on my Google Docs alternative I felt in love with it as I've discovered some properties I did not anticipated from the get go:
- Dealing with global state in react is very easy. It feels like you use an SQL client in your browser and all queries are reactive and always up to date. When writing a query you do not have to think about authorization it's all backed in.
- Because the backend is 100% free of domain specific code you can point your single page app to any linkedrecords deployment.
- You never have to write backend code
- Its quite efficient when using AI agents
The best way to experience it, is to follow this little tutorial: https://linkedrecords.com/getting-started/
It takes a while to get a hang of it so you have to have an open mind.
I would love to read your feedback on this.

value: Show HN: Write SaaS apps where users control where their data is stored

author: WolfOliver


value: Show HN: Redteam:If you are using more than 2 coding agents


value: Show HN: I was drowning in browser tabs, so I built this


value: Show HN: Avera – a deterministic check that proves no regression was introduced


value: Show HN: One-click fork of "Everything Claude Code" onto an isolated microVM


value: Osoraku

value:
Hi HN community,
I want to share my UAV/drone database.
I made this because have been tired to be asked about who makes it, where it"s made and who using Ardupilot.
How it works: Just browse it. And if you want to put the info into your LLM, use API and CLI feature.
Important: All the information is not classfied. It is sourced from public (web-pages, news, reports) and kind contributor from a research company.
Kind feedback is very welcome!

value: Show HN: UAVs FYI – Drone database with supply chain data, API and CLI

author: Osoraku


value: ossianericson

value:
A Google Nest speaker was winning the STP root bridge election on my network and knocking out DNS every 45 seconds. Took five separate tools to find it.
I started NetSentinel one Sunday afternoon out of frustration. Thought I would be done the same evening. But I was off by about 2 months.
Every time I hit a problem that lived in yet another tool, I just added it.
Available on Windows (MS Store), macOS and Linux.
Testers with different HW are welcome.

value: Show HN: NetSentinel – a local network security scanner and connectivity monitor

author: ossianericson