value: acd

value:
I have with the help of AI create an open source method of E8 LLM code book quantization library called glq. I was interested in creating Glq
as a PC gamer and devops, interested in both LLMs and AI. The current high RAM prices and LLM resource usage also inspired me to write glq. A question arises could you try and squeeze more out a gaming GPU with limited VRAM size by using alternative LLM compression methods?
Glq is effective compared to other LLM quantization algorithms at between 2-bits per weight up to 4 bits per weight. The effectiveness of glq at low bits per words is due to the properties of the E8 lattice compared to linear methods.
 Glq also supports mixed precision quantization where different LLM layers uses different compression bit weight depending on how sensitive the LLM layers are to quantization. Think of mixed precision a bit like MP3 or MP4 variable bit rate encoding.
I currently develop glq using g7e AWS spot instances to keep the cost more reasonable.
Glq uses vllm
4 bit Key value cache by E8 was inspired by NexusQuant. I try and squeeze in about four times as much Key value cache as normally would fit by BF16 in VRAM, or about two times compared to INT8.
I somehow wrongly at start picked a E8 code book size of 65536 entries instead of 4096 code book entries which better fits in GPU L1 cache. Having 65535 code book entries it turns out leads to higher LLM compression rate but at trade of of decode speed. I am trying to compensate by using Nvidia Cuda graphs and optimize the decode, currently work in progress.
To install glq in a python virtual environment on Linux with a Nvidia GPU:
pip install glq
Python PIP package
https://pypi.org/project/glq/
Glq source code.
https://github.com/cnygaard/glq
Current PC RAM Prices that inspired the library.
https://pcpartpicker.com/trends/price/memory/
https://en.wikipedia.org/wiki/E8_lattice
Eight dimensional lattice that provides optimal solution to the sphere packing problems. Think about it a bit like stacking cannon balls or stacking apples in an optimal way. Only you swap the apples for LLM weights.
Picture of an E8 lattice
https://en.wikipedia.org/wiki/E8_polytope#/media/File:E8_gra...
Credits: GLQ was inspired by E8 Quip# and Key value E8 compression was inspired by NexusQuant.
Math: The sphere packing problem in dimension 8, Maryna Viazovska
https://arxiv.org/abs/1603.04246
4bpw glq Quantization of Gemma 4 E4b-instruction tuned
https://huggingface.co/xv0y5ncu/Gemma-4-E4B-it-GLQ-4bpw
3.5bpw mixed precision quantization of SmolLM3
https://huggingface.co/xv0y5ncu/SmolLM3-3B-GLQ-3.5bpw
Docker image of glq on Nvidia GPU with Nvidia container toolkit.
docker run --rm --gpus all \
    -v "$HOME/.cache/huggingface:/cache/hf" \
    ghcr.io/cnygaard/glq-env:0.5.0 \
    python -c '
import glq.hf_integration, torch                      # registers GLQ with HF
from transformers import AutoModelForCausalLM, AutoTokenizer
mid = "xv0y5ncu/SmolLM3-3B-GLQ-3.5bpw"
tok = AutoTokenizer.from_pretrained(mid)
model = AutoModelForCausalLM.from_pretrained(
    mid, device_map="cuda", torch_dtype=torch.float16)
ids = tok("The capital of France is", return_tensors="pt").to("cuda")
print(tok.decode(model.generate(*ids, max_new_tokens=20)[0],
                 skip_special_tokens=True))
'
Currently work in progress on glq in getting the decode speed up and supporting more LLM model architectures.
Open question, Does glq work on Nvidia DGX spark and gaming Nvidia hardware such as 4070-5090?

value: Show HN: Glq LLM quantization using E8 lattice

author: acd


value: cadamsdotcom

value:
Reading Hacker News (and Lobsters) via RSS is great but staring at comment and article loading screens isn’t. You lose hours in limbo. Should you read less? No! Let’s make it more efficient!
I vibecoded offlinerss to gain efficiency reading HN & Lobsters’ RSS feeds. It fetches the original feed and emits 2 items per original feed item. It emits one for the article, pumped through a “reader mode” plugin to format it for readability in NetNewsWire, and another for the comments, also reformatted for readability.
To use it, deploy it yourself and choose a secret. It runs on Vercel free tier with everything tuned to a userbase of 1 person per deployment. If you supply the wrong secret, it will 404. But with the right secret your news reader can load the (very heavy) feed from wherever you are in the world.
I enjoyed vibecoding this, back and forth with Claude, tuning it to not overload the free services it uses.
The engineering tradeoffs are myriad. Cache tuning? Jitter? Etags? Reformat comment pages, or shove original markup into the feed? JS in the feed, or pure html5? Claude Code happily runs experiments, provides recommendations, then obliges and builds - all so I can read tech news more efficiently! We truly live in the future.
It was vibecoded. It does its job. If you want to read HN & Lobsters offline, maybe it works for you too!

value: Show HN: Hacker News and Lobsters RSS, repackaged for offline reading

author: cadamsdotcom


value: awacs

value: I'm a long time ruby and rails developer living under the never ending fear of "rails is dead" every month, for the last 15 years or so. Does anyone know the feeling? There are a few aggregators and viewers out there, but I've wanted to build something polished and useful for viewing the HN data, so here it is, my take on the concept. Open and free.<p>I'm looking to add a bit more utilitarian functionality, a configurable monthly emailer, direct job links, etc, in the future. Hope you find useful.

value: Show HN: A trend and monthly viewer of the monthly Ask HN: Who's Hiring?

author: awacs


value: Show HN: Dataroom – a Pi and self-hosted research harness on low-budget GPU


value: micktor

value: Use at your own risk :)

value: Show HN: QR Boarding Pass Generator++

author: micktor

story_text: Use at your own risk :)

title: Show HN: QR Boarding Pass Generator++


value: chaidhat

value: Show HN: Going from 1+1=2 to Quantum Mechanics

author: chaidhat


value: kanacki

value:
on any ubuntu curl -fsSL https://icomnewtechnologies.com/proof/proof_install.sh -o ~/proof.sh
bash ~/proof.sh

value: Show HN: I reduced LLM inference GPU calls by 94% using semantic routing

author: kanacki


value: snowbirdsong

value:
I built an GEO audit that checks your site for 20+ GEO issues and gives you my newly named GEO Rank™ score — a score like in CWV that shows exactly how prepared your site is to AI search.
There is currently no tool that really does a GEO audit (afaik). I feel like I really have something a bit special that fills a need.
It's not "everything", but it's an huge timesaver for a good 20+ factors and it will always be free to scan a single page. For someone who doesn't know how to or doesn't want to look at code or crawl, it can really save time.
For quality control purposes there is a 24 hour turnaround on processing, so thank you for your patience and trust.
For reference, I'm an unemployed in SEO, marketing, and content. I thought of the idea from trying to do my own site audits to learn.

value: Show HN: I Built an AEO/Geo Website Audit Tool

author: snowbirdsong


value: kiltdev

value: Show HN: Built a MySQL GUI that visualizes schemas as interactive ER diagrams

author: kiltdev


value: garymiklos

value: Show HN: NoSleepAgent – keep your MacBook awake until your agents finish

author: garymiklos


value: FuriosaStudio

value: Show HN: Free in-browser post-production calculators, no signup

author: FuriosaStudio


value: EddieLomax

value: Show HN: Figure – produce printable STL files via LLM and OpenSCAD

author: EddieLomax


value: egesabanci

value: Show HN: Ported Cerebras REAP to MLX – Prune MoE Experts on a MacBook

author: egesabanci


value: intrepidsoldier

value: Show HN: Native Markdown Reader for macOS

author: intrepidsoldier


value:
We’ve been using background Claude loops a lot recently, and we would wake up to PRs that didn’t solve the problem we wanted, made on assumptions that were wrong. Furthermore, the tests that the agents wrote were usually tautological, and didn’t test for intent. We wanted an agent that took all the context a company has, and writes tests that check for product correctness as well.
For example, we work in reg tech, so bugs aren’t always technical. What we often see is things like insider trading alerts that should’ve fired that didn’t. We wanted an agent that turns laws and regulations into tests.
For now, users can upload PDF, MD, TXT, and DOCX files, but we’re planning integrations like Slack, Notion, Linear, and Zoom in the future.
We’re early on, so we would love to know what you all think!

value: Show HN: NUA an agent that tests for product correctness


value: dillondesilva

value:
Hi folks,
I got curious about how genomics foundation models work and wrote an article explaining how they are trained + can be used.
Feel free to use the following as learning resources if you wish to jump into ML for comp bio stuff, it may help:
- Code: https://github.com/dillondesilva/nt-promoter-region-classifi...
- Article/Tutorial: https://substack.com/@dillondesilva/note/p-199596906?utm_sou...
- Demo: https://nt-promoter-region-classification.vercel.app/

value: Show HN: Playing with genomics foundation models | Tutorial/Explainer article

author: dillondesilva


value: Show HN: Transposify–change Spotify song key from your menubar for singing


value: This tool auto capture your submission & use Spaced Repetition algo (which fits with memory curve theory) to show you when to review. 100% free chrome extension, tremendous improvement<p>Give a star  if you like! I use it myself every day and it had been very helpful

value: Show HN: LeetCode EasyRepeat – Anki for LeetCode


value: sparkleMing

value: Show HN: Memex – A local-first AI journal that keeps everything as Markdown

author: sparkleMing


value: huhuhang

value: Linux Journey has helped millions of people learn Linux over the years. Now you can read lessons and complete quizzes directly on your iPhone and iPad. Free, open source, and actively maintained.

value: Show HN: Linux Journey for iOS

author: huhuhang

title: Show HN: Linux Journey for iOS


value: aayd

value:
I first came across the paper “Optimal Bounds for Open Addressing Without Reordering” through a Quanta Magazine YouTube video a few months back. I went looking for an official implementation and couldn’t find one, so I decided to try implementing the paper's Elastic Hashing and Funnel Hashing in Rust.
To that end, I build opthash, a Rust library providing ElasticHashMap and FunnelHashMap implementations (and more recently HashSet variants). They are at API parity with std::collections::HashMap and HashSet.
Initially, the data layout was a relatively straightforward implementation of the paper, with levels and buckets represented as nested structs that each managed their own allocation. Later, I moved to a flatter arena layout with one allocation for the backing control/data regions, and smaller descriptor structs holding pointers and metadata for each level. That ended up being noticeably faster. The intuition I went for is to arrange control bytes contiguously to maximize cache locality, since majority of instructions for probing was done on the control bytes.
Most the low-level details is inspired by hashbrown/SwissTable, such as 7-bit control bytes, SIMD scans over groups of control bytes, power-of-two sizing, test cases, and foldhash as the default hasher. hashbrown is included in the benchmarks as the performance ceiling, and std::HashMap is the baseline.
I also added Python bindings as a learning exercise. I aimed for parity with Python dict and set, but I quickly realized crossing through PyO3 adds more overhead than expected...
I would gladly appreciate feedback, especially about hash table construction, PyO3 bindings, or benchmarking methodology. I have learned a lot about Rust's language features (and crossing into unsafe territory) from this project, and I'm sure there are still many things to improve.

value: Show HN: Opthash – Rust implementations of Elastic and Funnel hashing

author: aayd


value: jrecyclebin

value: Hi - have wanted this for months but searches keep coming up empty. For having agents create and connect to local test VMs - build me a Windows VM, try out this script/software on it, give me back results. The agent can create VMs in Hyper-V and manage them through RDP. Runs on Windows, Mac and Linux. Strictly Claude API at the moment.<p>Would love to branch out to other VM hosts, remote desktop protocols and LLMs. Thanks for checking it out!

value: Show HN: Jabsco – agent harness that works remotely through RDP

author: jrecyclebin


value: jibaoproxy

value: Show HN: See the JA3 TLS fingerprint your scraper sends to Cloudflare

author: jibaoproxy


value: adyashakti

value: Show HN: Viveka: filter LLM output against a Lean-verified Advaita Vedanta model

author: adyashakti


value: show hn: leave an anonymous voice message for strangers


value: Sharanxxxx

value: Show HN: Tkcore AI – A multi-model workspace with custom knowledge grounding

author: Sharanxxxx


value: sujalmeena

value: Show HN: ContextBridge – Local-first AI reading sidebar using Ollama

author: sujalmeena


value: adithagrawaal

value: Show HN: SnapToCode – Screenshot any UI and get clean Tailwind code

author: adithagrawaal


value:
Hi all,
I'm playing round with Assist, testing different LLM's, tools, etc.
What i was missing from HA is a card which shows the past conversations, including processing times and such.
After a bit of experimenting i got a working PoC and then expanded on it.
Current features:
Features:
- Shows Assist pipeline debug runs end-to-end (STT → intent → TTS) with timings and status.
- Browse recent runs, select a run, and inspect each stage’s inputs/outputs.
- Raw JSON events viewer for the full payload.
- Live “thinking” stream while a run is in progress (useful for diagnosing slow/failing runs).
- audio visualization modes for TTS playback (waveform/spectrum/meter/glow/“Ulysse31”).
I would love some feedback from other HA users =)
Repo: https://github.com/brantje/ha-cards

value: Show HN: Assist Debug Card for Home Assistant


value:
Hey HN, I’m Vignesh, solo dev.
Handler is a Mac app for Codex and OpenCode that adds a review layer while the agent is generating code.
Every edit comes with a short explanation: what changed, why it changed, and what it touches. If one edit needs more context, you can open a side chat on just that change and ask follow-ups without derailing the main agent run.
The goal is to build a mental model as the code is generated, instead of waiting until the end and reviewing one giant diff cold.
It’s the same idea that makes stacked PRs easier to review: smaller, understandable units. Handler applies that at AI generation time, before the change turns into one giant diff.
This year I mostly stopped writing code by hand. I drive agents now, and I’m faster for it.
But a few months in I noticed a problem. The agent would come back with a 400-line change, tests green, diff looked reasonable, and after the first few chunks I’d pretty much lose the mental model. At that point I wasn’t really reviewing anymore. I was skimming the shape of the change and moving on.
I know that’s not the ideal way to drive an agent. But I also don’t want to slow the whole thing down and manually inspect every line like it’s 2022. The whole point of using these tools is speed.
So the bottleneck stopped being writing code. It became understanding the code fast enough to stay in control of my own project.
Handler is what I built to fix that for myself:
- Every edit the agent proposes comes with a plain explanation of what that specific change does and why.
- The explanation is attached to the edit, so you build context incrementally instead of reading one huge summary at the end.
- You can pull any single edit into a side chat and ask “why this approach?”, “what else does this affect?”, or “redo this part (soon)” without blowing up the main agent context.
- You go edit by edit and accept or reject, instead of staring at one wall of diff and hoping.
- It runs on your existing Codex and OpenCode setups, with worktrees so parallel runs don’t collide.
- It also has a built-in terminal that feels closer to a Chrome DevTools console than a plain terminal: command output is easier to inspect, the agent can read the terminal state, and there’s a native JSON viewer/builder for working with structured data without copy-pasting into another tool.
What it’s not: a review bot like CodeRabbit or Greptile. I use those, and they catch real bugs. But they review the code after the fact.
Handler points earlier in the workflow. It helps you review while the agent is producing the change, so you can keep the mental model instead of trying to reconstruct it later from a finished PR.
I’ve been using it daily and can’t go back to merging agent changes blind. If you’ve felt the same problem with large AI-generated diffs, I’d love for you to try it and tell me where it falls over.

value: Show HN: Review-First AI IDE, Built on Codex and OpenCode


value: mrroryflint

value: Show HN: Eyeball

author: mrroryflint

title: Show HN: Eyeball


value: Show HN: CPU-only fact-check, summarize, explain, translate anything


value: logic-designer

value: have now added totorials and improoved avr/arduino c emulation

value: Show HN: Logic Designer – Digital Logic SIM Tool

author: logic-designer


value: harshanacz

value: Show HN: Synapse – 2.9MB Mac app with screenshot, clipboard, Keep Awake and more

author: harshanacz


value: psyonity

value:
I've built a quick and dirty concept that shows the new built-in (since Chrome 148) prompt api in action. It offloads the messages to random other people that are visiting the site.
Ever since I saw the prompt api I thought this was a risk, considering there is no accept, agree or any dialog to download or use the api. It's inspired by the post from https://www.thatprivacyguy.com/blog/chrome-silent-nano-insta...

value: Show HN: PoC to use the Chrome Prompt API on other people's machine

author: psyonity


value: dariubs

value:
The website is a Hugo static site, fully hosted on GitHub Pages.Source code & curation is here:
https://github.com/best-of-ai/best-of-ai
Anyone can contribute new tools — just open a PR. We add high-quality AI tools anytime if they’re genuinely useful.
The list is regularly maintained with a focus on quality over quantity.

value: Show HN: Best of AI – Handpicked and Curated Open-Source List of AI Tools

author: dariubs


value: idiocache

value: Show HN: Whirligig

author: idiocache

title: Show HN: Whirligig


value: lincketheo

value: Show HN: Numstore – a single file ACID database for NumPy arrays

author: lincketheo


value: captionly

value: Show HN: I built auto-captions with face-tracking reframe for vertical video

author: captionly


value: badfatcat

value: Show HN: Rootprint – Self-hosted log search built with Svelte, Hono and Quickwit

author: badfatcat


value: aagosh

value: Logsonic fills gap in the local-first log analytics space -  when installing Elasticsearch is too much and vim/ripgrep is too little.<p>LogSonic is a Desktop-First Log Analytics application which runs on Windows, Mac and Linux. It runs fully offline with no external dependencies. It installs as a single self-contained binary that serves a feature-rich User interface in your local browser. The log ingestion wizard supports importing local log files (single or many at once) and automatically recognises well-known log patterns to tokenise the contents. The log search experience is blazing fast, delightful and intuitive.

value: Show HN: A desktop first local log analyzer with fast search and MCP

author: aagosh


value: brenocq

value: Show HN: Ket – a quantum circuit debugger that runs in the browser

author: brenocq


value: Show HN: HashCortX] – [AI desktop agent UI app by a vibecoder pharmacist]


value: Show HN: Humm – Share the Vibe, an app for quantifying the ambience


value: tskj

value:
Journaling in the digital world quickly becomes editing or second-guessing what to write. Freedom is bad. So I flipped it: as a side project I've been working on a simple journaling app where the page is always blank, and what you write is immutable.
It tries super hard to always keep whatever you write and never lose your words. The editor of course always stores in local storage to guard against accidental tab closes; there's a queue that lets you write offline and drains it on the backend; idempotency guarantees uniqueness and eventual consistency. As a bonus to me the developer, having immutable entries makes cross-device synchronization trivial.
You can use it without an account, but you can sign in with Google or GitHub SSO or get emailed a magic link if you want access to your writing across devices.
Entries are slightly obfuscated at rest, but not encrypted—I've been too scared of losing the master key. I'm considering adding E2EE as an option for users who understand what they're doing, but it's a hard UX problem to communicate the risk properly (you're responsible for the key and I can't help you if you lose it).
It also supports semantic search over all your previous entries: when you hit ctrl/cmd+enter to submit, a background task runs that embeds each paragraph with Hugging Face transformers + ONNX runtime and stores the results in Postgres. Did you know Postgres has built in support for querying vectors by cosine similarity? Literally an index for that!
Then I got scope creeped because I thought it was cool, so I added the same for photos: CLIP embedding does the same thing for semantic search in visual space. (works better in English, I struggled to find models that worked for multiple languages that worked with this setup)
The embeddings run locally on my server. No AI providers or anything, nothing leaves the server ever.
The app is free, but I added a $4/month to help run the server. As mentioned, just a side project, I have but a single paid user.
(The curly twirlys turned out to be a very fun generative art project, probably spent way too much time on that part.. it's not even my style! (as a median age, median gender, median weight software developer) But I thought they fit the vibe I was going for. If anyone's interested I can share the maths and the working out.)

value: Show HN: Jørnal, a journaling app where the page is always blank

author: tskj


value: franze

value: Show HN: Cable Detective Mac App – What's Plugged In

author: franze


value:
After several months of development and refinement, my mobile app, Scan2Sheet, is finally published and live on Apple Store and Play Store.
The idea for Scan2Sheet came from a problem I had myself: managing piles of paper receipts for tax deductions and expense tracking. Manually entering receipt data into spreadsheets is time-consuming, tedious, and prone to errors. On top of that, paper receipts can easily be lost, damaged, or overlooked.
With Scan2Sheet, simply take a photo of the receipt whenever making your purchases. In just a few clicks, the extracted expense data and a copy of the receipt image are automatically saved to your own Google Sheets document. There's minimal manual data entry, and no need to learn or manage another dashboard, database, or accounting system.
Here are the links to download:
- For IOS: https://apps.apple.com/us/app/scan2sheets/id6760991697
- For Android: https://play.google.com/store/apps/details?id=com.app.scan2s...
The product's landing page: https://www.scan2sheet.com/
I hope other people also find the app useful and I am happy to hear any thoughts and feedback.

value: Show HN: Scan2Sheet – Receipt Scanner to Google Sheets for easy expense tracking


value: paulbuiko

value: Show HN: Krimto – Your AI's memory as markdown in your own git

author: paulbuiko


value: dittes

value:
Hi HN,
we’re Maxim and Andreas, and we built Funnelt.
Funnelt lets you paste your website URL and automatically generate a website widget with a funnel to convert your visitors into qualified leads.
We built this because many businesses have websites that explain well what they do, but do not manage to convert visitors into actual business. Instead of manually configuring leads forms, we want to have something that instantly works.
Funnelt crawls the site, extracts the relevant information, creates a widget and lets the owner review and adjust it. You can test it with your website URL in just a minute.
We’re looking forward to your feedback!

value: Show HN: Turn a URL into a custom lead-capture funnel

author: dittes


value: billymc

value: Planning a holiday I would always google something like "weather in Barcelona in May" and every site would just show monthly averages. But I found monthly averages weren't great for getting an idea of what the weather will actually be like. So I built Wengo Travel, a free site where you can see past weather, day by day, hour by hour, for destinations around the world. It's kind of like a weather forecast app, but for past weather. Would love any feedback.

value: Show HN: Site to check actual past weather for trip planning, not just averages

author: billymc


value: PengSpirit

value: Show HN: MCP Registry – NPM-style install for MCP servers

author: PengSpirit


value: Show HN: Guestlist – know which sites will let your agent in


value: Show HN: NEXA - AI-synthesized news from 80 sources, one article per story


value: mertcikla

value: Show HN: TLD – codebase visualization and software diagramming to manage slop

author: mertcikla


value: Ravindhran

value:
Ideas, thoughts, questions about code architecture often occur to me asynchronously during my morning commute, during a run, during walks - when I am away from my desk. Something about motion and having your mental RAM free'ed up after a night's sleep.
Infact I often find the highest quality thinking and work for me happens when I am away from my desk and placed in a more mobile environment. I have been working in Robotics for the past few years with a codebase where robot behavior was buried deep in 1000s of lines of imperative code. One of the biggest contributions to the space was developing a behavior-tree/compositional-recipes style framework for writing robotic behaviors. I still remember driving to work noodling the thought about - how Javascript's promise chaining looked so elegant and what a similarly flavored robotic DSL might look like. After 2-3 design attempts, I landed on an elegant architecture in writing robotic behavior. New robotic skills could be developed in 40 lines of YAML code, instead of 1500 lines of intricate python.
As a side effect, the concise Skills, Recipes YAML interface is also extremely parsable by an off-the-shelf LLM - we got VLA-style robotic motion without any model training. Incredible to see.
If I think backwards about my process - I dare say that all of the core breakthroughs ideas - late-binding of resource, declarative langague, javascript style promises - were all separate ideas that all came during walks, discussions (with other engineers, with LLMs), during drives, some in the morning shower. Almost every idea that wrote down sitting at my desk - I either re-wrote, re-factored or deleted outright.
There is an order of magnitude difference in the quality & value of work I produce, when it is accompanied with deep thinking and brainstorming. Most of the work I produced directly sitting at my desk - would qualify as things that did not require/get deep thought. Don't get me wrong - most of my day is spent at the desk. Sitting at my desk is great for executing on something that I already know, however to develop new directions I always need to mull the problem and go do something else. Then at some point the computations in the brain seem to timeout and yield an interesting question or thought.
My broad thesis is this: Executing on an idea has become incredibly cheap. The differentiation or onus has shifted - to the thinking, brainstorming and exploration process.
For me that often happens - on a run, or on a long drive, morning commute. Whenever a good question/thought arises I would like to be able to immediately register, jot it down, brainstorm with a fellow engineer. This gap is where thinking fades.
Ariadne is my attempt to close that gap, for myself.
Ariadne - runs on your local workstation, on your code repo.
Dial it from anytime, anywhere & brainstorm with an informed Architect on the code repo.
Launch structured investigation tasks using your local friendly coding-agent (Claude, Claude, ..).
Refine your ideas, reframe the ideas and change the framing in a conversation.
If you arrive at a concrete idea generate an implementation brief for your coding agent with all the findings, context, problem framing.
When you reach your desk, there is an implementation brief ready to go.
Ariadne is built on Daily's Pipecat framework for voice-agents. It works incredibly well.
What I'm uncertain about:
Is this just a quirk of my mode of operation? Is this useful to anyone besides me?
Looking for:
10 developers who might be interested in trying this out and sharing thoughts or feedback - by using it in their actual workflow.
For the first few developers, I will set you with my API_KEYs.
Ariadne Demo: Implementing a feature: https://www.youtube.com/watch?v=MKwRE-1cQdI
Ariade GitHub: https://github.com/RavindhranSankar/ariadne/
Scheduling: https://calendar.app.google/xC41ED7tz9mkozdu5

value: Show HN: Ariadne – reason about your codebase on a walk, run, or commute

author: Ravindhran


value:
Hi HN — I built GridPath as I wanted something that runs like Cursor for spreadsheets - parallel workloads, reversible changes, fast, with a tool set customized for spreadsheet work and connection to multiple model providers.
It's a Tauri/Rust desktop app, free to use, just connect your Claude token or sign in with OpenAI subscription.
A few things that were interesting to figure out: you can get very close to Excel with just Univer free license, the most material missing elements are charts (existing charts kept but not displaying in the view) and pivot tables. Rust + cutting down on tools available to the model (basically just web fetch + talk to user + excel operations) improves the speed and token burn materially. SpaceX model built in 2 min 30s, compared to ~5 min for Excel plug in, for another run Claude CLI built the same model but burned 10x+ tokens (primarily many more web fetches and model iterations).
Working next on improving the agent efficiency for multi-sheet work + context compacting for longer sessions.
Repo: https://github.com/pixelsmasher13/gridpath
Site: https://gridpath.dev
Feedback welcome!

value: Show HN: GridPath – AI first desktop app to work with spreadsheets


value: pi-victor

value:
Wrote my own tool that helps me review AI Slop. Akin to Github/GitLab reviews but local and in a TUI instead.
You get full review history, branch, worktree, commit switching and supports AI agents in codex, claude, opencode and pi. You can also customize the prompts that get sent to these agent harnesses when calling the agent from the TUI.
It has an MCP as well, so you can just tell your AI agent to address the comments in review "new-review" for example, instead of running the AI agent inside of the TUI.
I've been daily driving this for a while now, while  i still need to fix a couple of things, but otherwise it's my favorite tool.

value: Show HN: Parley – code review TUI for AI code

author: pi-victor


value: MordechaiHadad

value: Show HN: Rustgate – Bypassing Python's event loop for token-aware rate limiting

author: MordechaiHadad


value: keertahacker

value: Show HN: AERF, signed receipts for AI agent actions

author: keertahacker


value: vincentping

value: Show HN: ASys – A typed binary protocol for AI agents to operate servers(no SSH)

author: vincentping


value: Show HN: I built a waitlist tool with Claude as a non-technical founder


value: winewarrior

value: Show HN: I built an on-chain economy where AI agents transact autonomously

author: winewarrior


value: matdesousa

value: Show HN: I indexed 21,509 Shopify App Store listings

author: matdesousa


value: floozie

value: Show HN: A real-time lip-sync avatar so your GPU can sit in standups for you

author: floozie


value: abahgat

value: Show HN: The nearest hospital to every place on Earth in a single S2 range query

author: abahgat


value: Codegres

value:
We Vibe Coded this App to track SEO.
No API Keys. NOT AI.
We wanted to test if our SEO person was fooling us or actually working

value: Show HN: SEO Tracker (Not AI)

author: Codegres

title: Show HN: SEO Tracker (Not AI)


value: renaudpawlak

value:
Hi HN, I'm the author of the JSweet project (Java-to-TypeScript transpiler), but today I'd like to show you something new: LocalFlow.
There are two common ways to analyse your data with AI ("Talk to your Data"):
1. Use powerful frontier models on the cloud — but hand over your data and pay per token
2. Use on-premise or local models — but accept weaker results and significant hardware costs
LocalFlow proposes a third approach I call "metadata-first AI": send only the schema to the LLM (column names, types, a few stats — never the actual values), and ask it to generate code that runs locally on your full dataset (scale it to millions of rows at zero additional token cost).
I'm curious what you think :)
Live demo (drop in any CSV): https://apps.localflow.fr/demo/
GitHub: https://github.com/localflow-ai/localflow-core

value: Show HN: LocalFlow – AI data analysis where the LLM never sees your data

author: renaudpawlak


value:
Hi HN,
Circus Chief is a tool for managing coding agent sessions from a browser. It's specifically optimized for small screens. It supports Claude Code, OpenAI Codex, and Google Gemini CLI agents.
Features
Agents can operate Circus Chief itself. Agents can spawn sessions, schedule sessions, interact with the Kanban board — anything you can do in the UI, an agent can also do.
Schedule work ahead of time.
Automatically reschedule when you hit usage limits.
Configurable, chainable prompt templates.
User-defined commands - agents can run them and see the results, and so can you in the UI. Handy for local CI or routine workflow steps.
Worktree-per-session isolation, or elect to work on a specific branch.
Shared canvas - this is a place for shared artifacts that don't belong in the code. Useful for iterating on planning documents.
Bring your own provider. Use subscription auth for Anthropic, OpenAI, or Google, or point sessions at third-party providers with Anthropic- or OpenAI-compatible endpoints.
If you want to try it:

  npx circuschief

Stack: Vue 3, Express, SQLite, WebSockets. Plain JavaScript. Tailwind.
Development process
I built this almost entirely from my phone and tablet — starting with Claude Code using both Anthropic and z.ai, then adding Codex to the mix around a month ago.
It was vibe coded in the sense that I was not reviewing many individual lines of code. I did review and iterate on plans with the agents, but often stayed out of implementation details. If a plan made sense then I would usually have the agent review it a few times before just letting the agent implement without any intervention. I've enjoyed building this way, but I don't deeply understand a lot of the details of the implementation. That's bitten me exactly once so far, see this issue: https://github.com/ferrislucas/Circus-Chief/issues/944
I used Circus Chief to build Circus Chief from a very early stage. I bootstrapped with Vibe Kanban, then switched to dogfooding once Circus Chief was usable. A lot of the app has been built through the app itself.
By the numbers
2,184 agent sessions since Christmas 2025 — 1,423 were child/follow-up sessions.
Agent mix: 1,818 Claude Code sessions, 363 Codex sessions, and 3 Gemini sessions.
50,929 conversation messages across those sessions.
41 sessions (1.9%) contained strong profanity in user-authored messages.
990 sessions linked to GitHub PRs, across 685 distinct PRs, 759 branches, and 731 worktrees.
Average logged agent call: 131.3 seconds.
2,410 commits on main; 883 pull requests total — 847 merged (~96%).
Repo scale: 887 tracked files and 310K current lines of code (excludes lockfiles, fixtures, and recorded test cassettes).
Peak day: 76 commits on March 21, 2026, first at 12:49am, last at 11:57pm — one every 18 minutes for 23 hours.
Busiest merge day: 28 pull requests shipped — New Year's Day, 2026.
Largest PR by diff: 140K insertions across 92 files — replacing mock Claude fixtures with VCR-style record/replay.
Code: https://github.com/ferrislucas/Circus-Chief
Analytics disclosure: the npm build includes PostHog for anonymous page-view analytics (session recording off, DNT respected). Disable with --no-analytics, in Settings → General, or build from source without a PostHog key.

value: Show HN: Circus Chief – Claude Code, Codex, and Gemini from Your Phone


value: asim

value: I can't tell if HN is the right kind of place for this stuff anymore since people are so advanced in their use but I thought it was interesting to leverage my existing Go microservices framework and turn it into the core of what would provide tools for an agent cli or whatever beyond that. Extensibility is key. Thought I'd share and get a conversation going.

value: Show HN: Build Your Own AI Agent CLI in 150 Lines

author: asim


value: protmaks

value: Show HN: Box-tests a self-testing app that runs in browser (DuckDB WASM)

author: protmaks


value: tfpgh

value:
Hi! This is a visualization I've always wanted but never quite found. It's a navigable map of the Wikipedia link graph structure, with search and shortest-path finding.
Offline, I parsed the May 2026 English Wikipedia full-text dump into a directed graph, used cuGraph on a GPU to run PageRank, Leiden clustering, and ForceAtlas2 for the layout. I did some post processing to get rid of lingering overlapping nodes and rendered a tiled map of raster base images (using Skia) and JSON metadata. Tiles are bundled into PMTiles. The frontend is Deck.gl.
Everything is hosted on Cloudflare. Search and shortest-path are served by a Rust backend in CF Containers which uses Tantivy and bidirectional BFS.
Happy to answer any questions!

value: Show HN: Wikigraph – an interactive visualization of all of English Wikipedia

author: tfpgh


value: pawelsobocinski

value:
Good morning,
In April, I launched Vetkuro, an application I had been working on for a few years (3+) after hours.
It is a mobile app and web analyzer for track-day drivers - the idea is to help drivers record their sessions, verify lap times, compare laps and sectors, and understand where they are gaining or losing time using GPS, OBD II, video and other telemetry sources.
Last week, 11 people used Vetkuro at Słomczyn, a track near Warsaw, Poland, and recorded more than 40 sessions. I later learned that they had downloaded the app through word of mouth.
Professionally, I’m a software developer with 15+ years of experience, although in recent years I’ve become more of a manager than a full-time developer. Motorsport is my passion. I go to the track several times a year, and, as often happens with side projects, I started building Vetkuro for myself, partly out of curiosity, partly because I wanted to improve, and partly because I wanted to build something in a domain I care about.
The app is intended for drivers of cars, motorcycles, go-karts and similar vehicles who want to check their results, improve their driving, or simply compete with others.
The product is still early and my backlog is still substantial. It cost me a lot mentally to release it in a state that was not as polished as I wanted. But after three years of working on it after hours, keeping it in a drawer any longer felt worse than releasing something imperfect.
I’m open to any feedback/questions (especially from people who go to the track) product, technical, UX, positioning, or criticism.
regards,
Pawel

value: Show HN: Vetkuro, telemetry analysis for track-day drivers

author: pawelsobocinski


value: sonjaqql

value:
Hey HN! Y’all are great. It is so fun to build things these days.
I wanna show off this archive that I conjured to run at home for consuming the recently releases of UFO files from the US government. This started as a Mac Mini-hosted project that I executed with my OpenClaw over Discord. After showing this to a few friends, I decided to get it online and find a catchy domain. Cloudflare was the perfect hosting choice.
There’s a lot of bonkers things out there going on, so I added human curated “Signals” - news, analysis and discussion of UFO and adjacent news. The backlog of signals was informed by the links shared between myself and my first tech boss. We have both seen things that these files help confirm.
As part of a reason to bring people back, I asked my assistant to do some digging into the data and come up with “Insights”, a dedicated section on the site that includes the responsible LLM in the byline. There a media pipeline for these insights using Remotion to generate social-media ready videos that I can upload to TT, IG, and YouTube.
I built this for fun. Mostly with Ollama-powered GLM 5.1. Runs on Cloudflare Workers, D1, R2. Keyboard navigation within the doc viewer is blazing fast. OpenClaw is my CMS.
Eventually, I hope to find some passive revenue through ethical ads if I get enough traffic. I think there is an audience for this. Right now, this is helpful with sharing the WTFs (and psyops) of the world with friends.
Hit me up with questions!
Stay rad, HN!

value: Show HN: A searchable archive of declassified UAP/UFO files, news, and analysis

author: sonjaqql


value: inventivetalent

value: Show HN: Laimen - An Unintrusive Reminder App

author: inventivetalent


value: gidam

value: Show HN: Mdrone – a microtonal drone instrument in the browser

author: gidam


value:
Hey HN,
We recently built Clipto. It’s a tool that lets you search over terabytes of video, audio, and images on your computer, without relying on the cloud.
Motivation: we probably all had this similar experience, we know a moment exists in a video or audio, but finding it takes hours scrubbing the timeline. You can send all the media to process in the cloud, but it’s slow, expensive and raises privacy concerns. So we decided to build our own on-device media search engine.
How it works (high level):
1. We ingest video, audio, image; normalize formats via ffmpeg; run content analysis to downsample the frames for deeper understanding.
2. A local ASR pipeline (optimized Whisper) transcribes speech into text and speakers are identified; faces are detected and if known, person id created; a vision model (optimized Qwen3.5) runs on the downsampled frames to detect scenes, actions, objects, OCR and visual descriptions.
3. A graph data structure ties everything together into a searchable memory.
4. At runtime, user’s query and intention are understood by a lightweight local language model. Graph search conducted to retrieve all the matching clip candidates and reranking is done by a reranking model.
5. All the processes are done on your computer, without touching our servers.
Right now, it runs best on Apple Silicon Macs with 24GB+ memory, but we are working on broader support as well as an API/MCP for other agents to call.
We’d love to hear your feedback. Feel free to ask anything!

value: Show HN: Clipto-fully local, natural language search over terabytes of media


value: lucamark

value:
Hi Developers,
I'm Luca, the creator of Modeloop. I've spent the last 18 months building, from scratch, a model-based design tool and today I'm finally opening the Open Beta.
Modeloop is a tool designed to generate code and deploy on embedded systems. The core idea behind this product is to create a vertical solution to design, test and iterate on the model faster, leveraging the modern software practices like Git. For this reason, Modeloop avoids vendor lock-in by saving model data as readable JSON rather than proprietary formats, making model reviews significantly easier.
At its core, Modeloop is conceived with a developer-first mindset, focusing on delivering an optimal user experience. This approach comes from my personal experience working in the robotics and automotive industries where I've experienced firsthand the frustration of fighting with tool configurations. The software we use should be built to accelerate innovation, not spend all day setting the right parameters to make the tool work. This is why it is engineered to prioritize developer happiness by automating the complex under-the-hood operations, resulting in a cleaner UI/UX. There is still a lot to do, though.
Modeloop supports a comprehensive library of standard blocks and also Finite State Machines (FSM) for advanced diagram modeling. Within the engine, a mathematical consistency checker runs automatically, blocking code generation if any defined contracts in the model exhibit mathematical inconsistencies.
Furthermore, Modeloop features an integrated test harness that allows developers to test their models directly within the UI, supporting MIL (Model-in-the-Loop), SIL (Software-in-the-Loop), and PIL (Processor-in-the-Loop) simulations. This built-in Testing & Validation suite accelerates the production of testing and code generation artifacts proving that verifying model logic isn't a separate project, but an intrinsic part of the design process that speeds up the V-model workflow.
As a solo-founder project, I don't yet have all the certifications of the industry giants. There are surely some edge-case code generation bugs I haven't hunted down yet. But the core engine is solid, fast and, honestly, a joy to use. There's a lot left to polish — my roadmap for the coming months is packed with improvements. Maybe too many, haha.
But… yes, the tool is in Beta. And I'd be thrilled to hear your feedback and take your criticism, however brutal it may be — in fact, I invite you to technically tear my design choices apart.
I'll be here in the comments all day to respond, but if you'd rather, you can DM me on Instagram (@_lucamark) or via mail (lucamarkdev@modeloop.app).
Enjoy,
Luca Marchionna
P.s.: For the HN community, I've prepared a promo code to unlock functionalities through the Pro Plan. Once registered, please insert the promo code HN_PRO_2026 .

value: Show HN: Modeloop – A modern model-based design tool

author: lucamark


value: zyoraclub

value: Show HN: We built an LLM inference engine in pure Python – no PyTorch, no Triton

author: zyoraclub


value: Show HN: Browser-based video trimmer powered by ffmpeg.wasm


value: veroz

value:
Check out the playground: https://www.brepjs.dev/playground
Github: https://github.com/andymai/brepjs
This project evolved out of another open source project of mine (https://gridfinitylayouttool.com/designer) where I wanted to offer a great (and free) tool to generate models for 3D printing.
Its strengths are in parametric parts and architecture. Think OpenSCAD, but in familiar Typescript rather than a custom DSL. It's also based on b-rep topology so shapes are exact mathematical boundaries, measurements are precise, and STEP export is fully supported.

value: Show HN: brepjs is an open source programmatic CAD library thats runs on web

author: veroz


value: zpusmani

value: Show HN: LocalSheets, a single-file spreadsheet with a local-only AI panel

author: zpusmani


value: qranalytica

value: Test your visual estimation skills on a blank canvas.

value: Show HN: Eyeball

author: qranalytica

title: Show HN: Eyeball


value: I know vibe coding is controversial. I wanted to give it a try so over the last ~4 weeks I tried vibe coding a blender/houdini inspired node based 3d geneartion app in my spare time. The original goal was to try to generate great looking 3d environments from relatively small data. Most games download megs or gigs of data and that's no good for web based things.<p>If you're an AI skeptic still, maybe seeing more concretely what's possible today might convince you otherwise? I'm not making any claim the code is good, though I'm also not claiming is bad. I had fun giving it a try. I was pretty blown away how far we got (We being the LLM and myself). Like many projects I also realized, it's too much work to finish and likely too few people would use it. Maybe it would inspire someone more motivated to do something along similar lines though.

value: Show HN: Sedon – node based 3D generation


value: opstan

value: Please limit title to 80 characters. This has 81 after our software transforms it:<p>Show HN: Opstan-an open source PoW blockchain with a decentralized social network<p>(You can submit now, then edit the title once the post is up—just please don't put back any clickbait.)

value: Show HN: Opstan, a decentralized social network on a PoW blockchain

author: opstan


value: paralleliq

value: Show HN: Piqc – GPU waste scanner for LLM inference clusters

author: paralleliq


value: tmolley

value:
Just had our tool published in nature comms: https://www.nature.com/articles/s41467-026-73648-2
If anyone else has dealt with the pain of trying to make tons of PCR primers and have half of them fail, maybe you'll appreciate this!
We were inspired when one of my grad students bought a GAPDH primer that failed and I was like "Why the heck are we constantly remaking primers for such common genes"

value: Show HN: I aggregated every rt-PCR primer published into a single database

author: tmolley


value: Show HN: Opaque – A header-only C++ anti-analysis library


value: apitman

value: Show HN: DropLock – E2EE secret sharing web app with no backend

author: apitman


value: loganboyd

value: Show HN: i — An experimental tensor DSL/compiler with explicit scheduling

author: loganboyd


value: deesix

value:
MySQL has limited extensibility via plugins and components. We created a fork of MySQL with a PostgreSQL-like extension framework (VillageSQL).
Until now, all extension development was done in C++ but we know LOTS of PostgreSQL extension is done in Rust via pgrx etc.
We built a Rust SDK that allows you to natively extend MySQL with custom types and functions and a subset of the PostgreSQL extension hooks.
Steps:
cargo install cargo-vsql
cargo install cargo-generate
cargo generate --git https://github.com/villagesql/vsql-extension-template-rust
The actual code looks like:
use villagesql::{InValue, VdfReturn};
fn my_func(args: &[InValue]) -> VdfReturn {
    match args.first() {
        Some(InValue::String(s)) => VdfReturn::string(s.to_uppercase()),
        Some(InValue::Null) | None => VdfReturn::null(),
        _ => VdfReturn::error("my_func: expected a STRING argument"),
    }
}
villagesql::extension! {
    funcs: [
        villagesql::func!(my_func, "my_func", [villagesql::Type::String] -> villagesql::Type::String),
    ]
}
Feedback welcome!

value: Show HN: Extend MySQL with Rust

author: deesix

title: Show HN: Extend MySQL with Rust


value: Hiskias

value: Show HN: Stop Babysitting Your Agents

author: Hiskias

title: Show HN: Stop Babysitting Your Agents


value: hemezh

value: Show HN: Claude Code plugin for deep multi-agent code reviews

author: hemezh


value:
Hi!
After months of building, we are now opening up Terse for beta/early access and made our repo public.
Terse is an Open Source (SU License) typescript first Zapier/n8n alternative built to work with Claude Code from the ground up.
We found that UI Workflow builders aren’t great for complex tasks and that developers (and now Sales Engineers!) much prefer staying in IDE’s + Claude Code + terminal. In addition, AI struggles at building complex GUI based workflows since it isn’t native code.
After integrating your tools, Terse will trigger a codegen and give you a strongly types SDK of you workspace. Every Slack Channel, Github Repo etc.. will have a corresponding type. Invalid jobs simply won’t compile.
In our beta, you can:
- Integrate tools and created a typed SDK of your Org.
- Create jobs directly in your Cli/IDE with our Typescript SDK.
- Trigger jobs with our in-house integration: Slack, Github, Linear etc… or our typed Webhook trigger
- Deploy jobs serverlessly (we use Modal to host all jobs in their own sandbox).
- Use our Skill to create, debug and improve your workflows with ease.
- Use our AI Gateway (TerseAgent) to access your orgs workspace content. (Heavy ACL/guardrails built in).
- Monitor all of your worklows directly with our cli or our web app. The web app also provides some lightweight Airflow-esque features such as manually triggering + re-running jobs.
We also have our Self-hosted option (Docker image) that allows you to use our product for free locally. We strip out the modal support and run jobs in child processes on your machine. Great to try the product without having to worry about integrating tools to a 3rd party. For more info about our hosting options, see: https://docs.useterse.ai/hosting.
Would love to hear feedback from the community. We are super early and we appreciate you giving us a shot.

value: Show HN: Terse, TypeScript First Workflow Builder


value: sachou

value:
I built this simple Chrome extension to always see how much I can pay myself based on my Stripe income. So now when I open my Stripe dashboard, I always see how much I can pay myself.
How it works is pretty simple.
You create a read-only Stripe API key (this key stays on your laptop), the widget gets the last 3 months of your revenue to calculate an average, and then you can specify your monthly expenses and adjust a tax and buffer %.
Then you get a nice card that shows you how much you can pay yourself this month.
It's fully open source under an MIT license. Please let me know if you have any feedback, and feel free to submit a PR.

value: Show HN: A Stripe widget that tells you how much you can safely pay yourself

author: sachou


value: felixzeller

value:
Hi everyone, I am Felix, a famliy doctor from ZH, Switzerland.
A couple of month ago I started this little project called
shii • haa, a breathing app that uses the phone`s microphone
for live biofeedback
My prior work in emergency medicine and intensive care was
closesly linked to breathing, mostly in critical situations...
and let me to reevaluate my own way of breathing. over time
one question popped into my mind: can medical knowledge and
biofeedback make an app actually promote self-awareness instead
of attaching your goals to the award system of the app.
it combines signal processing, a breathing state machine and ML.
The state machine follows inhale, exhale and transitions in the
mic signal. A quality layer rejects noisy or ambiguous windows
before signals are used for feedback. All processing is done
on-device, no speech or raw audio is uploaded.
What I'm trying to avoid is turning breathing into another score
or game. The app gives feedback on rhythm, depth and regularity,
but the point is more "notice what you are doing" than "perform
well".
I'd be interested in feedback, especially from people who have
worked on signal processing, health UX, or Android/iOS audio
issues.

value: Show HN: Live breath detection and biofeedback from a phone microphone

author: felixzeller


value: Show HN: Distance Ruler

title: Show HN: Distance Ruler


value: uonr

value:
Hi!
This is an infinite canvas note-taking tool where notes are laid out in a non-Euclidean, hyperbolic geometric space. As you drag and navigate through the view, you’ll experience a unique fluid distortion that naturally leverages your brain's spatial memory.
I’ve been obsessed with the concept of space in HCI for years. Many modern UI patterns are essentially workarounds for the lack of screen real estate. While researching zoom-based UIs a while back, I stumbled upon old HCI papers that used the Poincaré disk model of the hyperbolic plane to organize data. It elegantly projects an infinite space into a finite disk, keeping everything contextually visible.
I wanted to build an experimental app around this concept years ago, but the non-Euclidean math was a significant roadblock. Recently, I decided to give it a shot with the help of LLMs. It turns out that LLMs can handle the mathematical heavy lifting quite well, specifically in designing the coordinate systems and optimization algorithms, provided that you guide them with a solid architectural design.
This is still an experimental demo, but I hope it leaves an impression. I’d love to know if you find this paradigm practical for organizing your thoughts.

value: Show HN: Infinite canvas notes in the non-Euclidean Poincaré disk

author: uonr


value: soorajsanker

value: Show HN: MemexAI – we gave AI agents a "dreaming" phase to consolidate memory

author: soorajsanker


value: sarah-robiin

value: Show HN: Touch Grass, Virtually

author: sarah-robiin

title: Show HN: Touch Grass, Virtually


value: sahin

value: Show HN: Form an LLC or C-Corp from Claude/Cursor via MCP

author: sahin


value: acoye

value:
Hello there HN
I experimented with agentic coding recently and I felt the need to track more contextual data by project.
Also I felt the need to be able to go beyond the 1D chat to communicate with agents.
So I created a local document memory, that is discoverable by agents themselves.
The CLI is designed to be easy to pick up by agents.
It allows humans to collaborate too by reading / searching / editing documents in the store.
I have a Mac native GUI in the review process, I hope it will show up in the App Store soon.
You can try it easily, instructions here: https://metabrain.eu/
Here is the GitHub https://github.com/OpenCow42/metaBrain
The project is also an experiment for me to build some swift project truly cross platform (Mac / Linux / Windows)
It is open-sourced with the same license as LevelDB that I wrapped in swift to do this project.
The agents (and humans) can retrieve content quickly with a search, allowing to re-injecting specific knowledge in a specific context during agentic work.
It’s funny, I’ve thought of "inference rule base" as something of a derelict idea of the old functional expert systems.
Now that I start working with agents I feel more and more the need to go pick previously working solutions dynamically in such a base.
I’d be happy to get feedback.
Product fit wise, would this be useful to you or is this just me who is happy with it ?
Finally I had fun with the compression of documents, it tries ZSTD quick, if it does not compress the data by more than 10 percent it stores data uncompressed, else it does a ZSTD level 9 compression on the data. I picked up this trick form OpenZFS.
Thanks

value: Show HN: MetaBrain – A local document memory for AI agents

author: acoye


value: patrickmds

value:
I've been experimenting with ways to increase AI adoption for non-technical people. Basically, all companies are pushing for AI because it's all over the news and they feel left behind but most people have no clue where to start.
I think 90% of people (ie non coders) are sufficiently well served by using cowork instead of claude code or something similar. If we can get people from sales, customer support, marketing, etc to collaborate with skills and cowork to form a company brain, I think it's gold.
So I think there's opportunity for the community to share skills that work well for 1000s of use cases. However, it's currently quite hard to find good skills and figure out if they're worth it.
Gstack has had immense success because of Gary's reach and credibility. Can something like Claudinho.xyz host skills built by the community? What are your thoughts / concerns?

value: Show HN: I built a way to find and install Claude skills

author: patrickmds


value: lyxell

value: Show HN: Hop – JSX for Rust

author: lyxell

title: Show HN: Hop – JSX for Rust


value: Show HN: Bookeeper,A modern desktop app for tracking your books&reading progress


value: scottfits

value: Show HN: Tailor Your Resume to each role with AI

author: scottfits


value: shikhar

value:
Hi HN, I'm one of the founders of s2.dev. RePlaya (https://github.com/s2-streamstore/replaya) is a self-hosted browser session replay tool using rrweb (https://github.com/rrweb-io/rrweb).
It occurred to me that a durable stream per session would be a much neater architectural foundation for much of what you'd want from such a tool. As a unique feature, it also made live tailing straightforward because the player can read from the same stream the recorder is appending to.
The alternative architecture is likely an ingest firehose which is then indexed, with associated complexity and latency. You'd have to string together multiple data systems like a message queue, a metadata database, and blob storage and/or an OLAP database.
Here the only dependency is S2, which has an open source version you can self-host called s2-lite (https://news.ycombinator.com/item?id=46708055).
How it works:
- one S2 stream per browser session
- large rrweb events (like a full snapshot) get framed across multiple binary S2 records and reassembled on read
- active sessions are tailed with an S2 read session, and bridged to the browser over SSE
- session listing relies on stream names encoding reverse timestamps, as S2 returns a lexicographic order listing
- relying on fencing tokens so a stopped session can't be written to again by a late recorder
- retention and GC are handled via S2 stream config, so no background job needed
Curious to hear from folks on the tool or the stream-per-session model!

value: Show HN: RePlaya – self-hosted browser session replay with live tailing

author: shikhar


value: simantakDabhade

value:
Hey Everyone!
So I get to spend most of my day tweaking and playing around with really powerful search engines at TinyFish (which is so awesome). I’ve recently been super fascinated by the idea of using a search engine recursively to build datasets.
Been playing around with Exa’s WebSets product quite a bit and realized it was mainly focused on prospecting, and it creates datasets with a lot of missing data.
So we built a fully open source project, that can build and update datasets on any topic.
Datasets I have generated so far,
“All products that Starbucks sells on amazon, with their price and if they are in stock”,
“All theme parks in California, with ticket prices” ,
“All YC companies that are currently hiring for eng roles with their hiring page link”

  Would love for yall’s to try it out, and drop your thoughts, stars and feedback. Thanks!

value: Show HN: Open-source general-purpose alternative to Exa Websets

author: simantakDabhade


value: raphjacksun

value: Show HN: TidyPress – Git-native CLI from Markdown to a static site you own

author: raphjacksun


value: kykan

value:
Built this for researchers and personal convenience: Zotero is market leader research extension but it's expensive and sucks, and we think ours is better.
Bioscript runs against the DOM directly on PubMed, Scholar, or any journal page (no copy pasting). Extracts methodology, findings, figure context, exposes a Q&A interface, and lets you query across your saved library in aggregate.
19 users in. Would love feedback from anyone doing serious lit review work.

value: Show HN: Convenient Chrome Extension for Research

author: kykan


value:
Hi!
This is embedding each company into 2 dimensions based on its details, so companies doing similar things land near each other.
A map is then derived based on clusterings of industries.

value: Show HN: Map of 5000 YC Startups

title: Show HN: Map of 5000 YC Startups


value: lateos-ai

value: Show HN: Lateos/NPM-scan – open-source NPM supply chain scanner, v0.18.3

author: lateos-ai


value: pranabsarkar

value: Show HN: icantmarket – A verified help exchange for devs who can't market

author: pranabsarkar


value: rapiz

value: Show HN: 100cc - Roll your own Claude in 100 lines

author: rapiz


value: froglang

value: Claude and I started building FROG in an effort to stop burning through Anthropic credit so quickly. That was the only reason I honestly needed at the time, but as the language grew and features actually worked together, the language itself quickly became the reason to continue. FROG enables me to write tooling in little to no time using LLMs and have the LLM assist in the debugging process via FROG's "agentic hooks". What I've honestly found most eye-opening is how LLMs hook into the debugging process! It has been the difference between tools that got written and ones that were passed over.

value: Show HN: Claude wrote me a language, now I don't know what to do with it

author: froglang


value: nathell

value: Show HN: Edsger – A handwritten Clojure REPL for the reMarkable 2

author: nathell


value: nabhasablue

value: Show HN: SwitchSearch – A tiny extension that makes you less dependent on Google

author: nabhasablue


value: pennystudio-li

value: Still in active development. Completely vibe coded but not AI slob I hope, but hate comments are welcomed. Constructive comments are better. Thanks.

value: Show HN: A Bay Area theme monopoly style game

author: pennystudio-li


value: DominikKoch

value:
Hello HN, I'm Dominik the founder of Notra (https://www.usenotra.com) we recently built an AI Chat into our app and for that built a few custom components.
One of them being our loader, I really liked the idea of integrating our company name into it so I made a component out of it and small blog post ^^

value: Show HN: Building an Unique Braille Loader for My AI Startup

author: DominikKoch


value: ThanosAkr

value: Show HN: Oneconfig – Set up any dev envs with one command

author: ThanosAkr


value: jacobgold

value:
At my last job I spent a year building an agentic coding platform used by hundreds of thousands of people. Along the way I tried building a hosting service on OpenClaw, and also ran Hermes myself for a while. Both projects have some great feature ideas, but when I tried to use them for real work they failed more often than not, and their security models worried me. I just couldn't see either one becoming something I'd trust enough for myself/friends/family. After a lot of exploration I realized that what I really wanted all along was to create automations using the coding agent I already work in every day. It turned out coding agents were the best tool for automating anything, not just code, as long as they had the right environment and tools to work with.
I also spent 20 years leading Linux infrastructure and distributed systems teams. Anyone who's written service daemons knows that most of what we think of as "always on" is really just wake up, do some work, and go back to sleep, which is an efficient pattern to use and reason about. Cron has worked this way for decades.
So I built Clor, a CLI that lets your coding agent create "claws", which are background agents that automate anything on a schedule and run on your laptop, Mac mini, or a VM.
A claw can be defined and shared as a single CLAW.md file, which contains a bit of metadata (name, schedule, personality, etc.) and one or more ordered tasks. Each task is a real agent run with full tool use, or a plain bash step. Anything you can ask your agent to do once, a claw can do repeatedly. One of my claws tidies my inbox every few minutes, labeling obvious spam, rescuing legit email that got mislabeled, and starring threads I owe a reply to, etc. It's way smarter than Gmail's filters because it actually reads my mail instead of just matching rules.
Installing is the usual command on Linux/macOS in the terminal: curl -fsSL https://clor.com/install.sh | bash. That will set up the CLI, a small scheduling daemon, and a skill that you can run from your agent, /claws in Claude Code or $claws in Codex.

value: Show HN: Clor – give your agent claws

author: jacobgold

title: Show HN: Clor – give your agent claws


value: Show HN: Jolli AI – Local-First AI Memory for Claude Code, Codex, and Gemini CLI


value: I made a website that lets you filter World Cup 2026 matches that you're interested in watching, and add their schedules to your calendar. It's free, of course.

value: Show HN: Filter World Cup matches and add them to your calendar


value: rasulkireev

value: Show HN: I built a tool that add advanced searching to GitHub's Lists

author: rasulkireev


value: jonnyasmar

value:
Fun weekend project just to test out 4.8 against a pretty vanilla setup.
Started out with a simple prompt, "build a temu league of legends, web-only with online, room-based multiplayer".
It built it... fully functional in one shot! Then I went kinda ham and started iterating on every aspect little by little. I made it spin up subagents to each focus on designing a character. Spun up subagents to focus on designing abilities and their SFX/VFX. Did a few passes over the map, mobs, minions, etc.
Then I put Ultracode Workflows to task and, across a handful of prompts, had it optimize performance, balance, and a variety of other things. Workflows is insane btw...
I also used /goal pretty heavily as well. I'd sit and play and make note of like 10-15 tweaks, bug fixes, etc at a time and just let it go to town.
4.8 is a one shot machine... 5.5 ain't doin this...
Anyways, figured I'd share. Happy to answer any questions in the comments!
Try it out solo (with bots) or with friends! https://lmaomoba.com
Stack
- Web: React/TypeScript
- Game: Canvas
- Server: PartyKit
- Harness: Claude Code
- Model: Opus 4.8
- IDE: atrium (getatrium.dev)

value: Show HN: LMAO – Temu League of Legends, Built with Opus 4.8

author: jonnyasmar


value:
Hey HN,
I'm a solo developer based in Zeeland, The Netherlands.  I've been building Odeva, a property management system for holiday parks, vacation rentals, and campgrounds. It's a headless-first tool that's built specifically for the small-to-mid independent operators that legacy PMS vendors ignore. Still deciding on open-sourcing the project.
The problem: Most park management software was built 10+ years ago, designed for enterprise procurement, not for the receptionist or park manager who might not need all the bells and whistles. A 50-unit holiday park ends up paying €15K-70K/year across their PMS, channel manager, payment processing, owner portal, guest app, accounting integrations, and the manual labor of making it all work together. Small parks just eat the cost or cobble together spreadsheets. The result is that no PMS wants to help the little guys, and you end up with a package that is too expensive for them.
What I've built so far (alpha since May 2026, in production with early users):
- Planning board with drag-and-drop, visual availability, group reservations
- Mollie + Stripe payments with automatic refunds
- Guest portal for self-service check-in/out
- Owner settlements and revenue reporting
- Night register export for Dutch municipality compliance
- App marketplace with public/authorized API keys, webhooks, and a public GraphQL API
- MCP endpoint so AI agents can discover and interact with the API
- Sales channels management (Booking.com, Airbnb sync groundwork is done, but no organizations are currently testing this)
- Stay rules, pricing overrides, option/reservation lifecycle
The API is public and documented. There's a WordPress plugin for parks that run on WP, and a drop-in JS widget for anything else. The admin is multilingual (EN/NL/DE). There's a basic web editor to get you started quickly as well.
One nerdy thing I'm particularly proud of: I open-sourced a Tax Conformance Kit (https://codeberg.org/odeva/tax-conformance-kit) for Dutch tourist tax. Tourist tax rules are municipality-level, change frequently, and nobody can explain them consistently.
The stack is Ruby/Rails API, Astro website on Cloudflare Workers, deployed via Kamal to a Tailscale network. So far I had no issues with feature creep, and I think this was the right choice. I might migrate to Bunny.net soon.
If it weren't obvious, I was kind of inspired by Shopify's stack. I have worked on platinum-level Shopify apps before, and got to learn about the internals at Shopify while doing so. I think they do a pretty good job there! Shopify handles similar issues well by letting you start small, and having you choose Apps, details etc. on the go. That way you can go vertical for any niche feature you need. Similarly, they provide metafields that you can design yourself, so I do not need to setup ~200 amenities.
My main motivator was that me building something I think this industry needs. It was a challenge to see when I would hit a wall. Currently that wall is a lack of testers :)
I'd love feedback from anyone who's built booking/reservation systems, dealt with hospitality software, or has opinions on headless PMS architecture. Also happy to talk about the tax conformance approach. I think the "legal rules as testable data" pattern has applications beyond tourist tax, but I might be biased.
Regarding features, there's a long long TODO.md, but my ears are always open for voices!
Site: https://www.odeva.app
API docs: https://www.odeva.app/docs/api/
Tax Conformance Kit: https://codeberg.org/odeva/tax-conformance-kit

value: Show HN: Odeva Booking – A unified PMS for holiday parks and campgrounds


value: bhark

value:
This sits inside Balladic, which my team and I have been bootstrapping over the past year. You're welcome to check it out if you're interested, but I think the part most of you would be interested in is the on-the-fly generated narration UI's. This is more of a conceptual flyover than a technical one, but ask if you're interested in the behind-the-scenes, and ye shall receive.
Sort of true to the name, Balladic, we generate a new Narrative page for all users every night, as well as ballad/project-specific narratives for every single ballad. The presentation aims at something like a book chapter - what's hot today, how did the past week go, so on and so forth.
It's driven by a series of back-and-forth calls between various open-weights models, along with some classic algorithmic parsing, compression and that sort of thing (tokens are pricy). Roughly, it goes like this:
1. Data synthesis: parse changelogs, comments (anonymised of course), all kinds of activity. Split it, morph it, stretch it - until we can synthesize a clean informational tincture. Essentially dragging out the between-the-lines.
2. Fact-checking: pass that to a fact-checker with MCP access. This guy goes through all statements that could be understood as representing a fact, and uses mcp.balladic.com/mcp to probe and query. It then appends its verdict to the original synthesis doc it was passed.
3. Compilation: the final doc including the fact-checking appendix gets some further treatment, and is then passed to our UI renderer. This is our own twist on @json-render (which does a very nice job by the way).
Behind the scenes, there's a custom memory bank with some nice tricks to prevent hallucinations and cancerous growths. Happy to explain more about that bit if anyone's interested.
All LLM work runs on European GPU's, and we use a mixture of Mistral and chinese open-weight models.
Brought up a demo without auth to show it off here - hope there's some inspiration to catch.

value: Show HN: Dynamically Generated Fluid UI's

author: bhark


value: subairui

value: Show HN: Name2Tree – Turn any name into a deterministic tree

author: subairui


value: ProductivePhys

value:
One of the harder AI citation failures is quite simple: the identifier is real, but the citation is still fake. The DOI resolves, but to a different paper - not the paper the citation claims it is.
Topaz et al. reported their findings on citation hallucination in May in The Lancet. They scanned 2.5 million PubMed Central articles and estimated that 1 in 277 contained a fabricated citation. Some of their examples were this exact pattern: real identifier, fabricated title.
I originally built Scholar Sidekick as a formatter for my own use as a clinician-educator preparing talks, articles, etc. After reading the Topaz paper, I added a verifier to catch the most common pattern they found: a real identifier attached to the wrong paper.
My tool resolves the identifier, and then compares the title in your reference with the returned metadata (i.e. does this DOI, PMID, or arXiv ID actually point to the right paper?). It does not attempt to judge whether the cited paper actually supports the claim you make in your text. That still needs judgment, preferably human judgment.
I ran 350 previously unseen citations through the API once each in a test. It correctly identified all 37 fabricated references, but wrongly flagged 5 of 285 real references: 1.8% (95% CI 0.8–4.0%). (Plain similarity comparison, without the optional LLM screening - I would expect the LLM to rescue some of those borderline cases. A handful of citations returned no result on upstream timeouts and weren't scorable either way.) The test suite, results and failures are public, so you do not have to take my word for it. You can check them yourself.
The web version is free and anonymous. The REST API and MCP server use a RapidAPI key, with a free rate-limited tier and paid tiers above that. The MCP server is on npm, Smithery and Glama, and the Obsidian plugin is in the community store. Chrome/Firefox/Edge browser extensions in their stores as well.
I'm very open to feedback and look forward to hearing from anyone who tries it - what works? What fails? Thanks in advance.

value: Show HN: Scholar Sidekick – citation verifier for the "real DOI, wrong paper"

author: ProductivePhys


value: timhigins

value:
Repo: https://github.com/getpaseo/paseo
Homepage: https://paseo.sh/
Discord: https://discord.gg/jz8T2uahpH

value: Show HN: Paseo – Beautiful open-source coding agent interface

author: timhigins


value: seanwatters

value:
Aiming to be a batteries-included, integrated (converged?) web server / CMS / application framework, with support for straightforward multi-tenant deployments out-of-the-box.<p>* Storage implemented atop LMDB
* CLI, API and App servers written in Rust
* Guest code execution sandboxed using wasmtime
* Authentication extends the OPAQUE protocol
* Efficient log indexing/querying via tantivy
* Automatic TLS via Let's Encrypt

value: Show HN: Ordinary and Ordinaryd v0.6.0

author: seanwatters

title: Show HN: Ordinary and Ordinaryd v0.6.0


value: Show HN: Reloops – Open-Source Frame.io Alternative for AI Agents and Teams


value: alex-onecard

value:
Hey HN, I released my app Junco today to the iOS app store. Junco turns your newsletters emails and RSS feeds into short 2-5 minute podcast style episodes. You can listen to them while walking, commuting, showering, etc.
You can connect your gmail account to have them auto generated each day or use the email we give you. You also have the option to follow RSS feeds in the app "discover" section. Gmail access is read-only for only the senders you approve. This was one of the biggest hurdles as it requires a CASA level 2 security audit which was quite tedious and expensive ($750!!) but it was worth it for peace of mind.
Its free to try with a 3 day trial and then $5/month thereafter. My goal with this was not to replace reading but to help me follow the newsletters I already subscribe to daily and enable me to consume more diverse content that I don't have the time to read. Each episode includes a reader view back to the source article for those wanting further reading.
Would love any and all feedback on this, especially to those who have a lot of newsletter subscriptions. I'm happy to discuss any and all of the technical details of this application: railway, fastapi, swift, cloudflare, app store review process etc.

value: Show HN: Junco, turn newsletters into short audio episodes

author: alex-onecard


value: Hi HN! I made this to see if voice + super fast inference could make it feel like you were speaking things into existence on your machine. In my several hours of playing with it, it feels something like magic. Technical details in the post as well. Good day!

value: Show HN: Brontosaurus, a voice-driven generative AI canvas


value: zeroecco

value: A node-level desired-state reconciler for the NVIDIA driver stack — you declare what the host should look like, nvidia-converge makes it happen

value: Show HN: Nvidia-converge – Plan/apply/rollback for Nvidia drivers on Linux

author: zeroecco


value: pietervdvn

value: Show HN: A crowdsourced map of surveillance camera's based on OSM

author: pietervdvn


value: Please join us for Willow Wisp Gaming's first stream on twitch!

value: Show HN: First time Minecraft stream on Twitch


value: bcfeen

value: I built RxCheck as a replacement for the NLM Drug Interaction API which was discontinued in January 2024. It checks for interactions between any two drugs and returns severity, mechanism, and sources as JSON. It uses the DDInter 2.0 and the ONC high-priority list with RxNorm support. This is so all brand names, generics, and identifiers are still recognized. The free tier is 100 queries per month, no credit card required.

value: Show HN: RxCheck – Replacement for the discontinued NLM drug interaction API

author: bcfeen


value: Daniel-Pan

value: Show HN: SeaTicket – AI agent that resolve issues from GitHub, email and forums

author: Daniel-Pan


value:
We built this library because agent harnesses were too fragmented and we needed a simple abstraction to call multiple coding-agent SDKs.
lite-harness has one function - query()
import { query } from "@lite-harness/sdk";
for await (const message of query({
  prompt: "Fix the failing test",
  options: {
    // swap harness between: "claude-agent", "openai-agents", "pi-ai"
    harness: "openai-agents",
    model: "gpt-5.5",
  },
})) {
  console.log(message);
}

value: Show HN: LiteHarness – One SDK for Claude Agent, OpenAI Agent, Pi AI


value: QingWu

value: Turn complex PDFs into clean Markdown that people can review and AI tools can use.

value: Show HN: AI-Powered PDF to Markdown Converter

author: QingWu


value: tughvn

value:
I built another simple desktop GUI utility to track and download the latest specifications from the 3GPP.
It downloads the specifications, extracts the zip files, and saves them to a pre-designated folder.
My previous Chrome extension only supported PDFs, but this app can download specifications in Word format as well. Feel free to choose the version you need.
Figured some network/telecom engineers here might find it useful.

value: Show HN: 3GPP Spec Manager – A GUI app to track and download 3GPP specifications

author: tughvn


value: aspectop

value:
The problem : AI agents fail systematically above 10k LOC. The failure mode are same wrong file, partial completion, tool thrashing, context overflow.
Carto fixes this by giving AI agents what they are missing - Domain Map (automatic, no config), blast radius before any change, cross domain violation detection, Agents md for instant codebase context, 16+ mcp tools etc.
AI knowing what could break before it start editing  code. Feels like most tools are focus on generating code faster. Maybe the next step is helping AI understand systems better.
MIT licensed , Runs entirely local , No data leaks.
Tested on codebase like VScode, prisma, zed and more ( having over 10k+ files)
If you have any questions or patterns or ideas lets discuss. There is so much more things that can be done with this coz this thing i made is not just related to programming languages if you u see it u can use it to parse many more types of works.

value: Show HN: Carto – structural intelligence for AI coding agents (OSS)

author: aspectop


value: thinkingjimmy

value: a small Codex Skill + Automation that watches public posts for actionable Codex quota reset signals.

value: Show HN: Codex Reset Watchdog – a Skill for watching codex quota reset signals

author: thinkingjimmy


value: zagap

value: Show HN: Podlite 2.0 – a block-based markup language with typed blocks

author: zagap


value: VeilusDigital

value: Show HN: Phantom Chat – iOS messenger with NIST post-quantum encryption (PQXDH)

author: VeilusDigital


value: Julien-Au

value: Show HN: GymCoach – Self-hosted workout tracker where you bring your own LLM

author: Julien-Au


value: hboon

value:
I built a little tool that figures out who and what built a site. Just recently updated it.
e.g. https://whosbuilt.com/?domain=stripe.com

value: Show HN: Who built this website? Check any domain

author: hboon


value: Think of it as CAD software for your agent. Allows your agent to "see" what it's designing and iterate on it before it hands it back to you.

value: Show HN: Agentcad – Claude Code's favorite CAD tool


value: dschu

value: Show HN: Monophobie, a shared ASCII canvas, never draw alone

author: dschu


value: VladoIvankovic

value: Show HN: Codeep Is Now on the Mac

author: VladoIvankovic

title: Show HN: Codeep Is Now on the Mac


value: kitgw

value: Show HN: Terraform RAG - index modules, distill conventions, compose via MCP

author: kitgw


value: embedding-shape

value: Show HN: A HTML Quine Made with Nix

author: embedding-shape

title: Show HN: A HTML Quine Made with Nix


value: hlude

value: Show HN: Vivix – See inside JavaScript as it executes (open source)

author: hlude


value: erikpau

value: Show HN: Componentsystem.directory – A collection of every UI component library

author: erikpau


value: MikahDang

value:
Repo: https://github.com/skawld/skawld-agent
Homepage: https://skawld.com/

value: Show HN: Skawld – Open-source SDK for company-specific AI agents

author: MikahDang


value: jasonEinstien

value: Show HN: OpenSkynet Your AI Terminator

author: jasonEinstien

title: Show HN: OpenSkynet Your AI Terminator


value: Show HN: Ant-design/CLI – Offline CLI for Ant Design docs, lint and migration


value:
A few years ago, we (Tile.Expert, an online ceramics retailer in the EU) needed an internal tool to coordinate tasks and communicate asynchronously. Existing solutions lacked the security we required, so we built our own. It was strictly internal and unavailable to the public until recently, when we launched it as Remote.Team.
The core differentiator is verifiable end-to-end encryption. Unlike standard platforms that just use TLS and hold your data on their servers, our E2EE is client-side. You can verify that we physically cannot read your tasks or messages.
This architecture comes with strict technical trade-offs that users need to be aware of:
- Server-side search is impossible for encrypted content.
- If all participants leave an encrypted chat, the data is permanently unrecoverable.
- If you lose your device, account accessibility is compromised without backup keys.
- We intentionally omitted audio/video calling features to maintain a strict focus on asynchronous messaging, recommending external services like Zoom for real-time calls.
We are sharing this to get feedback on our approach to E2EE in a B2B task management context.

value: Show HN: Verifiable E2E encrypted task manager built by a ceramics retailer


value: steampixel

value: Show HN: A pizza configurator that re-adapts when you change your mind

author: steampixel


value: RickCraig

value: Show HN: AI Council Toolkit – open-source playbook for AI governance

author: RickCraig


value:
I created one simple place to consolidate all of Karpathy's stuff, like his essays, courses and GitHub projects.
You can browse it like a normal wiki, or ask it a question. Every answer cites the underlying source and gets saved as context graph that can build a new page, so asking a question is the same as editing the wiki.
I made it very strict about citations. Claims have to point at a real source file or the linter complains. I think it feels closer to Wikipedia than to a chatbot.
This project is not affiliated with Andrej and all material is public.
The engine I created is a template, so you can point it at any topic and build your own wiki.

value: Show HN: A self-growing wiki of Andrej Karpathy's public work


value: WouterGlorieux

value: Show HN: VNN – AI news aggregator that verifies every source live

author: WouterGlorieux


value: JCSlim

value: HN’s content has always been great, but the interface, not so much. I wanted to feel the live movement of Digg, stories reordering in real time based on rank. That quickly escalated, turning into a multi-feed blend from arXiv, Product Hunt, Ars Technica, Bleeping Computer and many more. The Hot tab combines them all based on rank without letting any single feed overpower the rest. No login needed to give it a try.

value: Show HN: RNKFlow I wanted HN but live like Digg, it became something much bigger

author: JCSlim


value: winchxyz

value: Show HN: Idea-to-build – a Claude brainstorm that pushes back, then builds

author: winchxyz


value: Show HN: Browser-based image converters (WASM) and a URL image scanner


value: kivanowbetterdb

value: Show HN: Self tuning chat exposing it's semantic and agentic cache

author: kivanowbetterdb


value: RaduUrj

value: Python PCAP analyzer

value: Show HN: Python PCAP Analyzer

author: RaduUrj

story_text: Python PCAP analyzer

title: Show HN: Python PCAP Analyzer


value: loaderchips

value: Show HN: Threshold Concepts in CS – ideas that permanently change how you think

author: loaderchips


value: carlosamg

value:
OpenSOP is an early open-source runtime/standard for executable agentic processes.
You (or your agent) define a process in YAML, and OpenSOP exposes it as a typed REST API that agents and humans can both use.
We built it because a lot of agent workflows still live in prompts, docs, or one-off scripts instead of versioned process definitions, and we wanted more control and auditability. Its under development, we are using it in production (at Coba.ai), feedback on the model, API shape, and use cases would be very useful.
We wanted to share it with the community, any feedback and comments are welcome. Especially now that Claude has released Ant https://x.com/ClaudeDevs/status/2061877343078244459 and its around the same concept.

value: Show HN: OpenSOP, We got tired of agents lying to us, so we built them a harness

author: carlosamg


value: Show HN: Overflow – compact your context window before it overflows


value: codybontecou

value: Show HN: Health.md - Apple Health → Markdown

author: codybontecou


value:
Hi HN,
I built Aura-IDE, a native desktop LLM coding harness for AI assisted software engineering.
The idea is not just “chat with your codebase.” Aura wraps models in a structured engineering loop:
repo awareness → Planner spec → Worker execution → surgical edits → validation → recovery → final receipt
The Planner reads the project and writes a spec. The Worker executes that spec with filesystem tools, diff approval, terminal validation, and recovery behavior. The goal is to make ordinary models produce better code by giving them better process, context, and tools.
The unusual part:
    Aura has been heavily dogfooded on itself. Roughly 98% of the codebase was generated, edited, or refined through Aura’s own Planner/Worker workflow under human direction. During May, visible DeepSeek usage crossed 1.1B tokens and nearly 30k API requests while improving Aura’s reliability, edit mechanics, UI, updater flow, README, demo flow, and product polish.
It is built with Python and PySide6. It supports DeepSeek, OpenAI, Anthropic, Gemini, OpenRouter, and CLI backends. It can run carefully with diff review, or faster with auto-dispatch/auto-approve.
I’d love feedback from people building coding agents, IDEs, or local/dev tools.

value: Show HN: Aura, an LLM coding harness that dogfooded itself


value: zwigglers

value: Show HN: Tired of duct-taping access control into agent prompts. Here's the fix

author: zwigglers


value: Show HN: Keen Code – a context aware CLI coding agent built by coding agents


value: dannanors

value:
Hi HN,
I’m Dan Lussier & I built a SIEM named nano. The platform took around 6 months to be fully featured (and tested, and security scanned.. many times over). I’ve been working in information security for over 20 years, and even if it sounds redundant, I always found major SIEM providers to 1, be insanely expensive and 2, often have issues (outages, inability to scale properly and still have strong capabilities / fast searches).
Around December (2025), I started down the path of creating nano, at first I was reading about some research around some new extensions released for Postgres (I’ve been using it for over a decade for various projects, so I was intrigued). So, I started creating the SIEM, I got about a week into it and realized even with the new extensions, Postgres will just not scale for SIEM-like workloads (I already knew this overall for standard psql, but the extensions added some really cool keyword concepts for speed). After that I started digging in and found Clickhouse (which I had not used prior), and decided to transition off psql > clickhouse for the logs. It made a huge difference (as expected), and really launched the full build once I saw the speed to cost ratio.
The backend is written in rust - jobs/api/search, and Clickhouse for the log database. There are a couple other core components - dragonfly for cache (redis), Postgres for metadata/user data/rules, and prometheus for health collection. Each app component can be run stateless, allowing for the ability to utilize spot instances for cost savings on any cloud provider - I spent a lot of time in the early build process deploying completely on Rackspace Spot, and it was actually incredibly stable - but the lack of capacity made it so I had to move off (sometimes could take 12+ hours before a stack would deploy completely). I go in to more detail in my release blog post if you want to see benchmarks and more information about the architecture: https://blog.nano.rs/posts/introducing-nano.
The query language should be familiar if you’ve ever utilized opensearch / splunk in the past - it’s a piped query language (nPL), I tried to keep it as familiar as possible, making it easy to jump into the platform. As far as structured (indexed) columns, there are just shy of 200 field names to map to pretty much any log source, these fields are highly indexed and when used in search should keep almost all searches <1 second to return data.
I am releasing two versions, one is the open core stack (AGPL), this contains the core components of nano, including alerts, log ingestion, search, detections, rule editor, etc. It is a full solution, while it lacks some more advanced AI features and deeper case management, for hobby/self hosting it can handle whatever you throw at it. The other is the paid-for option, these start at $19/month (hobby tier), and scale up from there to Enterprise. Each tenant is fully deployed via a deployment system, we default to hetzner for hobby tier, civo for mid tiers, and aws/gcp for pro/enterprise. I tried to bring the costs in low enough if you want a fully featured platform, even as a hobby, you can for a relatively low price. That said, the open core version still offers a ton for just spinning up and onboarding for a small lab. The install is fully containerized for open core, and should take 1-2 minutes total for the entire deployment.
Give it a shot (demo is on the landing page), and let me know your thoughts!
https://github.com/nano-rs/nano
https://nano.rs/docs
Dan

value: Show HN: Nano – open core siem built on rust and ClickHouse

author: dannanors


value: sidneydekoning

value:
Server-side tracking has been the right solution to iOS/adblocker data loss for years.
Our problem: setting it up properly requires a GTM server container, a separate cloud instance, correct trigger configuration, and a developer who knows what they're doing. Most WordPress sites never get there.
We manage tracking for 12 websites hightraffic sites at the agency i work (combined 3.9M monthly search impressions, ~370K sessions/month). After rebuilding our entire tracking stack server-side, we packaged the setup into a WordPress plugin.
How it works: - Plugin intercepts GA4/Ads/Meta events before they hit the browser - Routes them through your server to Google and Meta endpoints directly - No client-side JS dependency for conversion data
The result: we recovered 25–35% of conversion events that were previously lost to ad blockers and consent banner dismissals. So more and better data.
Technical notes: - Works alongside existing GTM web containers - Supports GA4 Measurement Protocol + Meta Conversions API - WordPress plugin, self-hosted, no third-party relay
Curious to hear what the HN crowd thinks about the server-side tracking space in general.

value: Show HN: Easy Server Side Tracking, Server-Side GTM for WordPress

author: sidneydekoning


value: ridruejo

value: Hi, we created HolaClaw.ai to make OpenClaw accessible to a wider audience by focusing on making the install process painless (just a regular .app that you drag into the Applications folder) and with secure default settings (curated set of skills, agent running inside a VM). Looking forward to your feedback!

value: Show HN: HolaClaw Desktop App for OpenClaw

author: ridruejo


value: droppableai

value:
Hi HN,
I built Droppable after seeing how difficult Shopify theme changes still are for many merchants.
Instead of digging through theme settings, editing Liquid files, or risking changes on a live store, merchants can:
- Create a session from a Shopify theme
- Open a private preview environment
- Click an element
- Describe the change in plain English
- Review the result
- Publish when ready
One thing I felt strongly about was not letting AI make changes directly to a live storefront. Every edit happens in an isolated workspace first, with support for version history and rollbacks.
Would love feedback from anyone building AI tools, visual editors, or working with Shopify.

value: Show HN: I built a Lovable-style editor for Shopify themes

author: droppableai


value: metahost

value:
YouTube is an incredible resource for MOOCs, but the platform itself is an absolute minefield of distractions.
Curatube fixes this by transforming public playlists into focused, interactive courses entirely free from the feed. Take timestamped notes side by side with the video, navigate lectures effortlessly using interactive transcripts.
Best of all, it's open source and designed to be easily self hosted!

value: Show HN: Curatube: a distraction free interface for YT playlists

author: metahost


value: beenzinozino

value: Show HN: Lint Your Markdown with ESLint

author: beenzinozino

title: Show HN: Lint Your Markdown with ESLint


value: SsgMshdPotatoes

value: Show HN: Instant DBML Schema to Database Diagram PNG Tool

author: SsgMshdPotatoes


value: vix treats conversations as a first class citizen and allows you to fork/trim anywhere, navigate back and forth in one key stroke.

value: Show HN: Conversations as a first class citizen in AI coding agent