value:
After months of feedback from devs juggling multiple chat tools just to break big tasks into smaller steps, we re‑imagined our workflow as a Kanban‑style Phase Board right inside your favourite IDE. The new Phase mode turns any large task into a clean sequence of PR‑sized phases you can review and commit one by one.
How it works
1. Describe the goal (Task Query) – In Phase mode, type a concise description of what you want to build or change. Example: “Add rate‑limit middleware and expose a /metrics endpoint.” Traycer treats this as the parent task.
2. Clarify intent (AI follow‑up) – Traycer may ask one or two quick questions (constraints, coding style). Answer them so the scope is crystal‑clear.
3. Auto‑generate the Phase Board – Traycer breaks the task into a sequential list of PR‑sized phases you can reorder, edit, or delete.
4. Open a phase & generate its plan – get a detailed file‑level plan: which files, functions, symbols, and tests will be touched.
5. Handoff to your coding agent – Hit Execute to send that plan straight to Cursor, Claude Code, or any agent you prefer.
6. Verify the diff – When your agent finishes, Traycer compares the diff to the plan and checks compatibility with upcoming phases, flagging any mismatches.
7. Review & commit (or tweak) – Approve and commit the phase, or adjust the plan and rerun. Then move on to the next phase.
Why it helps?
* True PR checkpoints – every phase is small enough to reason about and ship.
* No runaway prompts – only the active phase is in context, so tokens stay low and results stay focused.
* Tool-agnostic – Traycer plans and verifies; your coding agent writes code.
* Fast course-correction – if something feels off, just edit that phase and re-run.
Try it out & share feedback
Install the Traycer extension (https://traycer.ai/installation), create a new task, and the Phase Board will appear. Add a few phases, run one through, and see how the PR‑sized checkpoints feel in practice.
If you have suggestions that could make the flow smoother, drop them in the comments - every bit of feedback helps.

value: Show HN: Kanban-style Phase Board: plan → execute → verify → commit


value: pancakeguy

value:
Hi all, we're Jake, Jack and Joe, and we're building the open-source alternative to modal labs.
We think Modal's great, and wanted to use it at our previous places of work, but weren't allowed to because it was too expensive, and our data couldn't leave our cloud.
This is why we built Burla, the open-source alternative to modal.
Burla can run any python function on 1000 computers in around 1 second. It works with any container, any hardware, and can be installed with one command (currently only compatible with Google Cloud).
Would love to hear any thoughts or suggestions! We're open to chatting: https://cal.com/jakez/burla

value: Show HN: Open-Source Alternative to Modal

author: pancakeguy


value:
Hey HN. We’re the team behind Exploratory Policy—a causal-AI sandbox where policymakers, researchers, and curious citizens can test ideas before they ever hit the statute books.
What’s the problem?
Traditional policy making is reactive. By the time lawmakers regulate a new tech wave, second- and third-order effects have already locked in. We end up with brittle rules that chase yesterday’s risks.
Live demos
- Causal Graph Analysis – tweak an edge weight and see the entire system re-equilibrate.
- Chain Reaction Simulator
- AI Policy Assistant – natural-language back-and-forth with citations to the underlying model
Looking for feedback:
- Which policy domains should we add next? (We’re eyeing housing, economic impact preparedness, and open-source AI).
- Any go-to datasets we should onboard quickly?
- How can we make the uncertainty bands more intuitive for non-quants?

value: Show HN: Exploratory Policy – a policy simulation playground for complex systems


value:
Hey HN,
A couple of months ago, my brother and I built a little macOS cli app for ourselves. The idea was to remove tracking parameters from share urls from Instagram, Facebook, Google, LinkedIn, Reddit, Twitter, Tiktok, etc. Also, URL shorteners.
A bit later, after seeing a lot of "quishing" attacks here in Ireland, we ported it iOS and added support for scanning QR codes and previewing (and expanding) URLs from QR codes. This is something the iOS camera app doesn't do.
Today, we've released it on the App Store. It's completely free and also free from tracking, analytics, ads etc. It currently supports ~250 websites and apps, and about two dozen URL shorteners. We'll likely add support for more in the near future.
If you try it out, I'd appreciate any feedback.

value: Show HN: Clean Links – Free iOS app that removes tracking from URLs and QR codes


value: adriaanb

value: Show HN: 1-click AI profile scraper

author: adriaanb

title: Show HN: 1-click AI profile scraper


value: bobbiechen

value:
Hi HN! I’m Bobbie Chen, Product Manager for Fraud and Security at Stytch. Today we are launching IsAgent: a lightweight JavaScript SDK that tries to detect agentic traffic on the frontend, enabling you to build agent-friendly experiences.
You can try it out on our site at IsAgent.dev or install it via:

    npm install @stytch/is-agent (requires registration to use)

Try viewing IsAgent.dev as a human. Then try using ChatGPT Agent to view the page: "Visit IsAgent.dev, wait a few seconds, and then take a screenshot." (or, toggle the switcher at the top)
We built this because we’ve had a lot more conversations lately about "good bots" like AI agents and how to recognize and serve them better - just as we might internationalize a website or create a mobile-friendly version, can we create more agent-friendly experiences?
---
I’ll be the first to say: the detection is not perfect, and even noisy at times. We prioritized ease-of-use with a lightweight frontend-only SDK, and that means that there are limited signals we can actually use to identify agents. In the long run, I expect most "good bot" operators like Browserbase to offer the option to self-identify through web standards, which will make agent detection much more reliable.
A personal note: a couple years ago, I was a generative AI skeptic. But I’ve come around to cautious optimism: the technology is genuinely useful and different, and I think it makes sense now to try to identify AI agents and experiment with agent-ready experiences including LLMs.txt, MCP servers, and auth-on-behalf-of-end-user methods.
I’d love your feedback, especially if you:
* Are building AI tools or browser automations
* Have built out mobile, internationalized, or accessible experiences (curious on how this compares)
* Or, have opinions on the future of the Agent Experience
I’ll be around in the comments here, or feel free to email me at bchen@stytch.com !
-Bobbie
Some links:
1. IsAgent.dev - demo and docs
2. Announcement blog including thoughts from Browserbase, Orb, Freestyle Cloud, and Mintlify: https://stytch.com/blog/introducing-is-agent/

value: Show HN: IsAgent – Detect agents like ChatGPT Agent on your website

author: bobbiechen


value: Dhavidh

value: I've built a tool that empowers customers to retrieve real-time data and take direct actions on your website, all powered by ChatGPT Agent Operator and Anthropic Computer Use. No more digging around-just ask and act

value: Show HN: ChatGPT Agent for Your Website: Retrieve Live Data and Take Actions

author: Dhavidh


value: Show HN: Parsing Structured PDF and Images to JSON


value: tannertpayne

value:
I couldn't believe something like the milliondollarhomepage made $1M 20 years ago. I wanted to see if there was still some viral magic to it.
Mostly I made this as an experiment and to sharpen my skills, but would be pretty cool if it turned into something.
Let me know what you think!

value: Show HN: I recreated this viral website that made $1M

author: tannertpayne


value: alexdriedger

value:
Hi HN,
We’re Alex and Kalan, the creators of Pontoon (https://github.com/pontoon-data/Pontoon). Pontoon is an open-source data export platform that makes it really easy to create data syncs and send data to your enterprise customers. Check out our demo here: https://app.storylane.io/share/onova7c23ai6 or try it out with docker: https://pontoon-data.github.io/Pontoon/getting-started/quick...
While at our prior roles as data engineers, we’ve both felt the pain of data APIs. We either had to spend weeks building out data pipelines in house or spend a lot on ETL tools like Fivetran (https://www.fivetran.com/). However, there were a few companies that offered data syncs that would sync directly to our data warehouse (eg. Redshift, Snowflake, etc.), and when that was an option, we always chose it. This led us to wonder “Why don’t more companies offer data syncs?”. It turns out, building reliable cross-cloud data syncs is difficult. That’s why we built Pontoon.
We designed Pontoon to be:
- Easily deployed: we provide a single, self-contained Docker image for easy deployment and Docker Compose for larger workloads (https://pontoon-data.github.io/Pontoon/getting-started/quick...)
- Support modern data warehouses: we support syncing to/from Snowflake, BigQuery, Redshift, and Postgres.
- Sync cross cloud: sync from BigQuery to Redshift, Snowflake to BigQuery, Postgres to Redshift, etc.
- Developer friendly: data syncs can also be built via the API
- Open source: Pontoon is free to use by anyone
Under the hood, we use Apache Arrow (https://arrow.apache.org/) to move data between sources and destinations. Arrow is very performant - we wanted to use a library that could handle the scale of moving millions of records per minute.
In the shorter-term, there are several improvements we want to make, like:
- Adding support for DBT models to make adding data models easier
- UX improvements like better error messaging and monitoring of data syncs
- More sources and destinations (S3, GCS, Databricks, etc.)
- Improve the API for a more developer friendly experience (it’s currently tied pretty closely to the front end)
In the longer-term, we want to make data sharing as easy as possible. As data engineers, we sometimes felt like second class citizens with how we were told to get the data we needed -  “just loop through this api 1000 times”, “you probably won’t get rate limited” (we did), “we can schedule an email to send you a csv every day”. We want to change how modern data sharing is done and make it simple for everyone.
Give it a try https://github.com/pontoon-data/Pontoon. Cheers!

value: Show HN: Pontoon – Open-source customer data syncs

author: alexdriedger


value: goldsteinnick

value:
Hi HN,
I’m a solo founder who rebuilt my social app from the ground up after realizing something obvious: most “social” platforms are optimized for engagement, not real connection. Loneliness is rising, and I wanted to build something that actually helps people meet offline.
PLATO5 is a social engine (not media) with one purpose: moving people from strangers to groupchat to IRL friendships all guided by AI to reduce reluctance and friction.
Here’s how it works:
1. *Matching*
Each day, users are matched into private groups of 4, based on the Big Five personality traits, interests, and location. The AI explains the reasoning behind each match.
2. *AI-Coached Groupchat*
Once matched, you enter a chat assisted by *Zen*, our embedded AI Chat Manager. Zen suggests personalized topics, balances participation, and can ghostwrite in your tone when things feel awkward. This is all to prevent stalling conversations.
3. *Meetup Coordination*
When your group is vibing, the *Nearby* applet helps you find or create virtual/IRL events. Zen also surfaces weekly suggestions tailored to your group’s dynamic.
You’ll need to create an account to access the matching, chat, and event features but it’s live now and fully functional.
I’m not trying to build the next addictive feed. I’m trying to build tech that actually leads to friendship. PLATO5 measures success by real-world outcomes, not ad engagement.
https://plato5.us
Would love your feedback, ideas, and questions. Thanks in advance for checking it out!

value: Show HN: PLATO5 – AI-guided social engine to turn strangers into IRL friends

author: goldsteinnick


value: todsacerdoti

value: Show HN: Open source, AI chat with 1000s of MCP servers

author: todsacerdoti


value: mr-karan

value:
Hi HN,
I wanted a simple way to expose local dev servers to the internet that I could host myself, so I built Arbok. It's an open-source tunneling service that uses WireGuard for the data plane.
The server is a single Go binary that uses a userspace WireGuard implementation (`wireguard-go`), so it can run without root privileges and has no kernel dependencies, making it easy to deploy in a container.
What makes it different:

  1. Self-Hosted & Open Source:** Run it on your own domain and infrastructure. Full control, no surprises.
  2. Simple Client Experience:** A single `curl` command gets you a ready-to-use WireGuard configuration. No signup needed.
  3. Userspace WireGuard Server:** The server runs as an unprivileged user, which simplifies deployment and enhances security.

Here's how you'd use it:
```<p><pre><code>  # 1. Request a tunnel for your local service on port 3000
  $ curl https://arbok.mrkaran.dev/3000 > arbok.conf

  # The server responds with a config and your unique public URL.
  # The URL will be printed to your console, for example:
  #
  # Your app is live at: https://brave-snake-1234.arbok.mrkaran.dev

  # 2. Activate the tunnel using standard tools (requires sudo on client)
  $ sudo wg-quick up ./arbok.conf
</code></pre>
```
You can check out the code and a more detailed setup guide on GitHub: https://github.com/mr-karan/arbok
I'm still actively developing it and would love to get your feedback, feature ideas, or contributions. Let me know what you think!

value: Show HN: Arbok – Self-hosted HTTP tunnels to localhost using WireGuard

author: mr-karan


value: fistondev

value:
Hi HN I’m a developer and YouTuber, and I recently built a small tool to solve a problem I kept running into. When editing my videos, creating precise timestamps and chapter markers by hand was incredibly time‑consuming. I wanted a way to generate these automatically while still letting me refine them.
My tool uses speech analysis to detect topic changes and outputs a list of timestamps with suggested titles. You can upload or link a video, and it returns a set of chapters that you can tweak before publishing. It’s still early, but I’ve been using it on my own channel and it cut my editing time by more than half.
I’m sharing it here because I’d love feedback from other creators and developers. What features would make it more useful? Does the AI get the segments right? Feel free to try it out here: https://autotimestamps.com . I’ll be around in the comments to answer questions.
Thanks for checking it out!

value: Show HN: AI tool that generates YouTube timestamps automatically

author: fistondev


value: tamsky

value: Show HN: Promo video tool – browser-based, no timeline, no learning curve

author: tamsky


value: Show HN: The platform making SEO simpler, cheaper, and more effective


value: xinweihe

value:
Hey Xinwei and Zecheng here, we are the authors of TraceRoot (https://github.com/traceroot-ai/traceroot).
TraceRoot (https://traceroot.ai) is an open-source debugging platform that helps engineers fix production issues faster by combining structured traces, logs, source code contexts and discussions in Github PRs, issues and Slack channels, etc. with AI Agents.
At the heart are our lightweight Python (https://github.com/traceroot-ai/traceroot-sdk) and TypeScript (https://github.com/traceroot-ai/traceroot-sdk-ts) SDKs - they can hook into your app using OpenTelemetry and captures logs and traces. These are either sent to a local Jaeger (https://www.jaegertracing.io/) + SQLite backend or to our cloud backend, where we correlate them into a single view. From there, our custom agent takes over.
The agent builds a heterogeneous execution tree that merges spans, logs, and GitHub context into one internal structure. This allows it to model the control and data flow of a request across services. It then uses LLMs to reason over this tree - pruning irrelevant branches, surfacing anomalous spans, and identifying likely root causes. You can ask questions like “what caused this timeout?” or “summarize the errors in these 3 spans”, and it can trace the failure back to a specific commit, summarize the chain of events, or even propose a fix via a draft PR.
We also built a debugging UI that ties everything together - you explore traces visually, pick spans of interest, and get AI-assisted insights with full context: logs, timings, metadata, and surrounding code. Unlike most tools, TraceRoot stores long-term debugging history and builds structured context for each company - something we haven’t seen many others do in this space.
What’s live today:
- Python and TypeScript SDKs for structured logs and traces.
- AI summaries, GitHub issue generation, and PR creation.
- Debugging UI that ties everything together
TraceRoot is MIT licensed and easy to self-host (via Docker). We support both local mode (Jaeger + SQLite) and cloud mode. Inspired by OSS projects like PostHog and Supabase - core is free, enterprise features like agent mode multi-tenant and slack integration are paid.
If you find it interesting, you can see a demo video here: https://www.youtube.com/watch?v=nb-D3LM0sJM
We’d love you to try TraceRoot (https://traceroot.ai) and share any feedback. If you're interested, our code is available here: https://github.com/traceroot-ai/traceroot. If we don’t have something, let us know and we’d be happy to build it for you. We look forward to your comments!

value: Show HN: TraceRoot – Open-source agentic debugging for distributed services

author: xinweihe


value: htcni

value: Show HN:typed - Markdown app for writers, students, professionals, and creators

author: htcni


value: QuantumSpirit

value:
I've been working on this for 6 months - built a hybrid neural network that performs quantum security analysis with hardware-level performance in pure software.
Technical achievements:
• 95% detection accuracy in <10ms response time
• Bell inequality violation detection (up to 2.828 CHSH values)
• QKD channel analysis and QRNG validation
• Multi-task learning architecture
The breakthrough was combining quantum encoding with classical neural networks to achieve real-time analysis that previously required expensive quantum hardware systems.
Demo: https://celebrated-faun-feff7e.netlify.app
Looking for feedback on the technical approach and potential use cases. What do you think about using AI to democratize quantum security?

value: Show HN: AI system for quantum security analysis (rivals €500k hardware)

author: QuantumSpirit


value: adamqureshi

value:
What it is
We run a niche marketplace called Only Used Tesla. Answering dozens of buyer questions each day (“Does this VIN have FSD?”, “What’s the battery health?”) was eating our time, so we built OUT (Only-Used-Tesla AI). It’s a chat interface that:
searches our live inventory in real-time and surfaces matching cars
decodes the VIN on the fly to answer spec questions
links straight to the listing so you can keep the convo flowing while you browse
handles follow-ups like range estimates, tax-credit rules, etc.
How it works
Stack: Next.js 14 on Vercel, Vercel AI SDK for streamed chat UI
Model: GPT-4o (8k window) via OpenAI API
Retrieval
car listings + VIN metadata sit in Postgres → pgvector
embeddings with ada-002 + hybrid SQL expansion to tighten recall
Prompt: system + user query + top-k listings (JSON) → GPT-4o → markdown → user
Cost control: we truncate fields, switch to GPT-3.5-turbo for lightweight queries, and cache embeddings with a checksum on the record
The repo is private for now, but we’ll open-source the retrieval layer once it stabilises.
Why post this on HN?
We’ve built marketplaces before, but this is our first serious RAG+LLM production feature. We want brutally honest feedback on:
Search relevance – do the returned cars make sense?
Latency – first token vs. full answer feels OK to us, but we’re biased.
Prompt design / hallucinations – what edge cases break it?
On-ramp – is “no signup → chat” the right balance, or should we expose more filters first?
Tear it apart; the more it hurts, the better the next iteration will be.
Appreciate any feedback—technical, product, or brutal nit-picks. Thanks!
contact@onlyusedtesla.com . ( Adam Qureshi) Han SOLO founder. used o3 to write this so please forgive me :-)

value: Show HN

author: adamqureshi

title: Show HN


value:
my friend owns a small family shop in India with 5-6 staff. They don't use any software except custom accounting software. Last week I visited his store and saw him writing names on a wall calendar to track which staff is absent or late, for calculation of monthly wages and deduct pay for missed days.
got the idea to build him a simple offline attendance app. used claude and chatGPT to code it in about 60 minutes and published it on the appstore.
sharing here in case other small shop owners need something similar - no internet required, just tap to mark attendance and generate reports, export to csv or pdf.

value: Show HN: Friend's pen-and-calendar tracking → simple staff app


value: omojo

value:
Hi HN,
I built Tendly (https://tendly.xyz) as a way to share things-messages, files, ideas that are meant to be temporary.
Most tools today treat sharing as permanent by default. Tendly flips that: everything disappears after a short time. No accounts required. Just open, type, upload, and share. The person on the other end gets it and it vanishes after it’s seen.
Use cases: Quick, intentional messages, Ephemeral file drops, Private one-time notes, or Temporary feedback or thoughts
It’s inspired by the idea that not everything needs to be stored or remembered forever.
Would love feedback on usability, security assumptions, and whether you find this concept useful in your day-to-day work or communication.
Built with React, Supabase, Vite, Framer Motion and GitHub Actions. Open-sourcing parts of it soon.
Thanks for checking it out!

value: Show HN: Tendly – Ephemeral, privacy-first sharing for files and notes

author: omojo


value: For startups, finding great technical candidates is really hard.  It requires sifting through stacks of identical looking resumes and making complicated determinations, like “is this person a good culture fit for our organization” with limited information. So, I built a tool that uses AI agents to perform deep background research on candidates across thousands of websites like Devpost, Github, Reddit, etc to build a comprehensive understanding of who this person is before you even talk to them. Would love for ya'll to check it out and let me know what you think!

value: Show HN: Cursor for Technical Recruiting


value: milst

value:
Hey!
We're working on a React SDK + API to make it simple to build apps with natural language interfaces, where AI can interact with the components on screen on behalf of the user.
The basic setup is: Register your react components, tools, and MCP servers, and a way for users to send messages to Tambo, and let Tambo respond with text or components, calling tools when needed.
Use it to build chat apps, copilots, or completely custom AI UX.
The goal is to provide simple interfaces for common AI app features so we don't have to build them from scratch. Things like:
- thread storage/management
- streaming props into generated components
- MCP and custom tool integration
- passing component state to AI
plus some pre-built UI components to get started.
Would love feedback or contributions!

value: Show HN: Tambo – a tool for building generative UI React apps with tools/MCP

author: milst


value: rolfvanroot

value:
I recently migrated our marketing agency's work to Linear. It's been fantastic, but we immediately ran into a problem: there was no easy way to visualize our content pipeline on a calendar.
For social media, blog posts, and other content with specific publish dates, a list or board view just wasn't optimal for seeing the "flow" over a month.
To solve this, I built LinCal.app, a web app that acts as a calendar for Linear issues.
How it works:
- Log in with your Linear account
- Filter issues based on team, assignee, project, cycle, and more
- Open issues with a click in separate browser tabs (LinCal right now is a read-only app - not changing any Linear data)
- show/hide weekends/subtasks
- View issues within this filter that do not have a due date
If you are a Linear user and would appreciate a different view on your work, I'd love for you to check it out and hear your thoughts

value: Show HN: LinCal – A Calendar View for Linear Issues

author: rolfvanroot


value: willmorrison

value: I enjoy browsing GitHub's "awesome" lists – curated collections of tools, libraries, and resources for different technologies (like awesome-python, awesome-javascript, etc.). But I could not find an index of these repositories.<p>AwesomeIndex contains the actual projects within GitHub's awesome lists. Instead of manually browsing through individual repositories, you can now search across thousands of curated projects with real-time filtering by repository, category, language, and GitHub stars.

value: Show HN: AwesomeIndex – Search GitHub's "Awesome" Lists

author: willmorrison


value: jonathanlehner

value:
We originally built voice agents for sales training - basically AI role-play partners to help reps practice pitches and handle objections. Problem was even we stopped using it. Setting aside time for practice felt like overhead, and simulated scenarios never matched real conversations.
So we tried a different approach: instead of practicing fake calls, get help during real ones. Aya sits on your desktop and watches sales meetings. When someone raises an objection or asks something unexpected, it suggests responses or pulls up relevant info about their company.
The multimodal part is what makes it different - it's not just transcribing audio, but seeing your screen and understanding context from multiple inputs in real-time.
We open sourced it because the concept feels like it could work in other verticals too - education, customer support, even job interviews. But we're just one team focused on sales. Want to see what the community builds with it and where else this real-time AI assistance makes sense.
Built with Electron and LiveKit for screen recording. Runs in a transparent window so it's there but not intrusive. Still figuring out the privacy aspects of having AI watch your calls.
Try it: https://aya.miraipitch.com/ Code: https://github.com/MiraiPitch/Aya-Assistant
What do you think?

value: Show HN: Aya – Open-source AI assistant that gives live hints during sales calls

author: jonathanlehner


value: nkko

value:
I built this because digging through raw JSONL files in ~/.claude/projects became painful once I hit a few thousand messages. Claude Threads gives you a three-pane browser with vim keys (hjkl), full-text search, and collapsible tool calls.
Looking for feedback on:
- Performance with large archives (how many messages do you have?)
- Must-have keyboard shortcuts I'm missing
- Any features that would make this more useful for your workflow?
PRs welcome!

value: Show HN: Claude Threads – Browse Local Claude Code Sessions

author: nkko


value: lostmsu

value: Show HN: Pelican Arena Leaderboard

author: lostmsu

title: Show HN: Pelican Arena Leaderboard


value: ilevd

value: Show HN: List of Clojure-like projects

author: ilevd

title: Show HN: List of Clojure-like projects


value: funkaster

value:
I started this project a couple of weeks ago because I was stuck on my side project and needed some motivation. For a very long time I wanted to get back to do something useful in lisp/scheme, did a quick research and settled on CHICKEN mostly because it's relatively well maintained, fast enough, it's extremely easy to build/install and very easy to write interop to pretty much any library.
Most of the projects that I've written on the side have been using some combination of Sinatra + Sequel + Postgres/Redis/Something else + HTMX. I love the simplicity of Sinatra's API so I decided to focus on trying to have a similar experience but in scheme, trying to make it ergonomic for a scheme dev (that part might not be there yet since I'm not an experienced scheme dev).
The most fun part was the dev cycle: Emacs + NREPL + Aider (as a code reviewer & rubber ducky. For codegen it's mostly annoying but works great for documentation & refactoring).
I hope to add full SSE & WebSocket support some time this week. Anyway, hopefully this is interesting to some of you and might be a source of fun :)

value: Show HN: Schematra – Sinatra-inspired minimal web framework for Chicken Scheme

author: funkaster


value: devxiyang

value:
Hi HN,
I built a tiny, ultra-fast image cropping tool — cropimages.co. It runs fully in your browser, no uploads, no tracking, no watermark. Just drag your image in, crop what you need, and download.
Why? I was tired of clunky online tools with slow loading and annoying ads. This one loads instantly, works offline, and respects your privacy.
Built with HTML + Canvas. Ideal for quick edits without opening a big tool like Photoshop.
Would love your feedback!

value: Show HN: Crop Images Instantly – No Upload Required

author: devxiyang


value:
Hey HN,
I made a simple tool to circle-crop photos — for avatars, profile pictures, or product thumbnails. circlecropphoto.com works 100% in the browser, and never uploads your image.
Just drag and drop → crop → download.
No login. No watermark. No nonsense.
Useful for devs, designers, or anyone needing a quick circular crop.
Let me know what you think or what features you’d want added!

value: Show HN: Circle Crop Photo in 1 Click (No Upload, No Watermark)


value: Show HN: HackerTool – Small toolkit with real features and prank commands


value: Thyrdev

value:
Hi HN,
I built ReplyFast to help save time when replying to emails using AI.
You can choose the tone of your reply (formal, friendly, direct, etc.), and the AI adapts to your preferences over time.
ReplyFast offers quick suggestions or fully personalized responses.
I’d love to hear your feedback, ideas, or critiques thanks!

value: Show HN: ReplyFast Smart AI replies for faster customer messaging

author: Thyrdev


value:
Inworld TTS modeling and training codes have been open sourced now for the community: https://github.com/inworld-ai/tts, together with a detailed technical report: https://arxiv.org/abs/2507.21138.
Interested in ultra high quality TTS with very low cost to scale your application in production? Now it’s a great time to integrate: https://inworld.ai/tts

value: Show HN: Inworld TTS open sourcing and technical report


value: musbemus

value:
Hey HN. We're Mus and Isaac - creators of LightLayer.
We've been outputting a ton more code since using agentic dev tools. It's been great. But we're starting to see a new bottleneck emerge that's no longer writing the actual code: reviewing code.
We’d love to hear from folks here if they’re feeling the inertia of code reviews a lot more these days with the surge in development velocity. For us, it was the reason we decided to pivot what we were working on before, and go full-time on building a workspace aimed at bringing the code review experience up to speed for the AI era.
To be clear: we’re not an auto-commenting PR bot (e.g. CodeRabbit, Greptile, Graphite, etc.). We think those tools are helpful, and can give a solid first-pass at issues for the author to iterate on. But we think human-in-the-loop reviews are here to stay and so we’ve gone with the approach of focussing on empowering reviewers with a consolidated workspace that delivers the context and sounding board they need to review quicker without sacrificing understanding or quality.
We basically brought all of the relevant parts of Github - discussions, file tree nav, diffs, timeline events, etc. into one view that both you and our agent - Lux - can see and work off of in real-time; kind of like a live review session with a senior team member (we actually got inspo from how much quicker reviews went for us in our jobs when we did pull ppl in to do live review sessions). We designed the UI around voice for this reason - to emulate that experience.
Anways, I’ll stop yapping and let y’all try it out - just sign in, and paste in any public URL to any Github PR. Highlight code or click on comments you want Lux to pay attention to and just speak naturally. Right now, Lux will point you to relevant places in the code, explain things, and draft comment copy for you.
This is all definitely still a WIP: Lux still doesn’t have complete context of the entire codebase and there’s some bugs we’re working through wrt conversation flow (please use bug nub if any arise). And there are a ton of other features we’d want to include eventually (MCPs for Slack, Linear, etc., comments in your learned tone) But it’s enough to showcase the experience we’re targetting and hopefully still create some value for those looking for more of a delightful code review experience.
That said, would super appreciate any feedback.
Github (for issues): https://github.com/lightlayer-dev/community
Demo: https://app.lightlayer.dev/
Website: https://www.lightlayer.dev/
Happy coding!
P.s we posted here last week pre-launch without reading through the 'rules' for Show HN - sorry!

value: Show HN: Voice-First AI Code Review Workspace

author: musbemus


value: thinkagenticai

value:
We’ve published a set of open-source reference implementations on how to build production-grade Agentic AI applications on AWS.
What’s in the repo:
 • Agentic RAG, memory, and planning workflows with LangGraph & CrewAI
 • Strands-based flows with observability using OTEL & Arize
 • Evaluation with LLM-as-judge and cost/performance regressions
 • Built with Bedrock, S3, Step Functions, and more
GitHub: https://github.com/aws-samples/sample-agentic-frameworks-on-...
Would love your thoughts — feedback, issues, and stars welcome!

value: Show HN: Agentic AI Frameworks on AWS (LangGraph,Strands,CrewAI,Arize,Mem0)

author: thinkagenticai


value: Show HN: I made the thumbnail generator Mrbeast took down


value: Show HN: Windows XP in the browser, with file system, Word, media, flash


value: caaaadr

value:
github: https://github.com/abidsikder/llm-txts
I kept ad-hoc creating llm.txts in my personal LLM use for projects that don't have them so I made this to make it more automated for myself.
Hoping to see if the community finds it useful, or can recommend a better tool for this and using long context LLMs that I've missed :P

value: Show HN: LLM-txts I created for developer documentation that does not have it

author: caaaadr


value: AmjdAlhashede

value: Show HN: Proposal for a Universal Multi-Language Execution Core

author: AmjdAlhashede


value: acdev

value: Updated version now includes: layout templates, AI-powered image analysis for auto-placement, YAML-to-natural-language prompt conversion, and full English UI support.

value: Show HN: Intuitive Layout Image Generation Prompt Generator

author: acdev


value:
We’ve already demonstrated that institutional collapse—through gatekeeping, inflation, and market saturation—can be structurally prevented by design.
This protocol does not rely on authority or reputation scores. Instead, it operates autonomously through verifiable contribution and cyclical feedback.
Institutional stability is not an aspiration — it has already been achieved through structure alone, without centralized control.
The design logic and structural basis are documented here:
 https://github.com/contribution-protocol/contribution-protoc...
We’d love to hear your thoughts, experiences, or references to similar approaches.

value: Show HN: Open Contribution Protocol — No Gatekeeping, No Inflation, No Limits


value:
I built MindSafe Journal for people who want a private space to reflect and track their mental health — without cloud sync, tracking, or logins.

    100% offline

    One-click PDF export

    Works on all platforms (desktop/mobile)

    Stored in local browser only

It’s a no-login, zero-dependency mental wellness tool that just works.
Would love your feedback — I’m happy to answer any technical or UX questions.

value: Show HN: MindSafe Journal – An Offline Mental Health Privacy Journal


value:
Freezewell is an offline-first tracker for women going through egg freezing.
Built for privacy — no logins, no cloud, no tracking. It helps organize:

    Medication schedules

    Appointments

    Cycle tracking

    Notes and reminders

Everything runs entirely in-browser. Feedback welcome — happy to answer questions.

value: Show HN: Freezewell – A Private Egg Freezing Tracker (Offline App)


value: stagas

value: Show HN: A Toy Sound Generator

author: stagas

title: Show HN: A Toy Sound Generator


value: melvinzammit

value:
In the last few months I was trying to up my presence on x (twitter), mostly by sharing my app dev experiences. I quickly noticed that just about everyone shares screenshots framed with a gradient background as if they were shot on a mac.
Initially I started creating my versions with Adobe XD (I know its deprecated and all, but I love it), but this was a bottleneck. So yesterday, I decided to spend an afternoon creating this super simple tool to solve my problem. I already started using it and the process is fast.
The tool is 100% free & web based. Feel free to try it and let me know what features you need. I will be adding redact, browser & mobile mockup frames next. I want this to be a tool you use for 1 second and forget until you need it again. Any feedback is greatly welcome.

value: Show HN: I built a tool to make screenshots better

author: melvinzammit


value: valitron

value:
Hi HN,
We're trying to address a pressing problem expressed by recruiters. Candidates can now use AI tools to brute force hundreds of job applications, all tailored at scale, causing what's now being referred to as "the application avalanche". LinkedIn reported a 45% increase in applications this year alone. Recruiters are increasingly overwhelmed by this tidal wave - making it nearly impossible to know who is actually qualified. As a result, many companies are becoming reluctant to post open roles and instead rely on warm intros or internal referrals.
We built Valitron, an AI interviewer that talks to every applicant simultaneously, asks adaptive follow-up questions (not just a static script), and then ranks candidates by job suitability. It’s prompted to follow validated behavioral and competency interviewing frameworks, so it digs deeper into real skills rather than accepting rehearsed or vague answers.
Here is a demo: https://www.youtube.com/watch?v=WpCnjD7eg4Q
Unlike existing tools that just collect recorded answers for human review, Valitron both conducts the interview and scores candidates objectively. Recruiters end up spending time only with the best applicants, reducing time-to-hire from weeks to days.
We’d love feedback from the HN community on the product, the approach, and potential concerns or edge cases.
Website: https://www.valitron.ai

value: Show HN: Valitron – I built an AI that interviews and ranks job applicants

author: valitron


value: sudofoo

value: Show HN: MagicQuill – Edit Images with AI Brushes

author: sudofoo


value: Show HN: N0vaTools – A cool toolkit with many features


value: Show HN: LatentSync–Precise AI Video Lip Synchronization


value: bohemianjock

value:
Hi HN – I've been working on zp, a clipboard manager for the terminal. You can copy file contents or command output with it, and it keeps a searchable history.<p>The newest update adds peer-to-peer clipboard syncing between machines. You can sync your clipboard history across your laptop, desktop, work computer, etc. No cloud services or accounts — just direct machine-to-machine sync over your local network (or SSH if needed). It runs in the background and just works.<p>```
# Copy a file's contents to clipboard
zp notes.txt<p># Pipe output to clipboard
cat config.yml | zp<p># View searchable clipboard history
zp --logs<p># Enable P2P sync
zp --sync-enable
zp --add-peer desktop:<a href="http://192.168.1.10:8080" rel="nofollow">http://192.168.1.10:8080</a>
zp --sync-daemon
```

value: Show HN: Zp – A terminal clipboard manager with P2P sync between devices

author: bohemianjock


value: menensito

value:
As a solo founder, I often struggled with writing SEO-friendly texts for my own products, so I built this to scratch my own itch.
Right now it supports English, Spanish, and French, and I’m planning to add more languages. It also suggests specific keywords based on your product niche.
I’d love to get feedback from the HN community about:
- where it can be improved
- if the keyword suggestions make sense
- or any features you’d expect from this kind of tool
The core features are free to try, and I’m happy to answer questions or go into technical details!
Thanks for reading :)

value: Show HN: SEOtip AI tool to generate and optimize product with targeted keywords

author: menensito


value: pompomsheep

value: Show HN: I made a mobile game you can only play on the toilet

author: pompomsheep


value:
Hey HN,
I made TubeSummary, a browser extension that adds a summary and Q&A button to YouTube videos. It uses your favorite OpenAI-compatible API (OpenAI, Groq, Together, etc) so you can get quick takeaways or ask the AI about the video — right below the player.
Built it because I got tired of scrubbing through endless videos just to figure out what mattered.
It's open source, I have tested on latest Chrome and Firefox.
A quick heads up for Chrome users: since I don't have a paid Google developer account, the extension isn't on the Chrome Web Store, so you'll need to install it manually. Sorry for the extra hassle! There's a step-by-step guide in the repo if you need it.

value: Show HN: TubeSummary – YouTube gets AI summaries in the browser


value: marcusfrex

value:
Lets imagine a scenario where you're coerced whether through threats, torture, or even legal pressure to reveal the password to your secure vault.
In countries like the US, UK, and Australia, refusing to provide passwords to law enforcement can result months in prison in certain cases.
I invented a solution called Veilith ( veilith.com ) addresses this critical vulnerability with perfect deniable encryption. It supports multiple passwords, each unlocking distinct blocks of encrypted data that are indistinguishable from random noise even to experts. And have a lot of different features to protect your intellectual properties.
In high-stakes situations, simply provide a decoy password and plausibly deny the existence of anything more.
Dive deeper by reading the whitepaper, exploring the open-source code, or asking me any questions you may have.

value: Show HN: Forced to Give Your Password?

author: marcusfrex

title: Show HN: Forced to Give Your Password?


value: Saidia is an offline-first AI assistant tailored for educators, enabling them to generate questions directly from source materials.<p>Built using Electron, Ollama, and Gemma 3n, Saidia functions entirely offline and is optimised for basic hardware. It's ideal for areas with unreliable internet and power, empowering educators with powerful teaching resources where cloud-based tools are impractical or impossible.

value: Show HN: Offline-First AI Assistant for Educators


value: Show HN: Project Random – the web on shuffle


value: richinex

value: Show HN: Interactive Go concurrency patterns with WebAssembly

author: richinex


value: Devalanx

value: Show HN: must_go – Fail-fast error handling with the ‘must’ pattern in Go

author: Devalanx


value: merelysounds

value:
Hey everyone! I built Nonoverse, because I couldn't find a nonogram[1] puzzle game where the levels are not randomly generated, that works well on an iPhone and that is free and user friendly (no ads, no tracking, works offline, etc) - something that I could share with friends.
I'm a fan of Simon Tatham's Portable Puzzle Collection[2] and the list of No-Bullshit Games by Stavros[3] (thanks!) - this app is my small contribution.
While building this I prioritized UX/QOL. You can drag to select, there's undo and redo, you can switch between filling cells or flagging cells as empty, etc. I hope the result is pleasant to use and fun.
I'd love to learn what you like about the app or whether you'd improve anything - this will help me plan future updates.
Check it out and tell me what you think: https://apps.apple.com/pl/app/nonoverse-nonogram-puzzles/id6...
---
[1]: https://en.wikipedia.org/wiki/Nonogram
[2]: https://news.ycombinator.com/item?id=44691935
[3]: https://news.ycombinator.com/item?id=38429080

value: Show HN: Nonoverse – Nonogram Puzzles for iPhone and iPad

author: merelysounds


value: logicallee

value:
Claude 4 sonnet can now produce lifelike gesture animations with stick figures, this opens up a lot of UX/UI possibilities, imagine a stick figures showing you what to tap, where to go next like "come with me", I think this shows the exciting possibilities for the future.
The complete prompt was simply "animate a stick figure with several gestures, such as thinking and movement" and this was the result in one shot.
Let me know what you think below.

value: Show HN: Lifelike one shot gesture animation by Claude

author: logicallee


value: bwb

value:
Hi all, creator here :)
I launched Shepherd.com (https://shepherd.com/) on HN in 2021 and have added a ton since then! Here is the original Show HN (https://news.ycombinator.com/item?id=26871660).
What did we add?
We just shipped a monster update for bookshelves! Try the science fiction bookshelf as an example:
https://shepherd.com/bookshelf/science-fiction
You can visually explore science-fiction books in a ton of different ways.
The most recommended of all time (or by decade): https://shepherd.com/bookshelf/science-fiction
Trending science fiction books: https://shepherd.com/bookshelf/science-fiction/trending
The most recommended new sci-fi (pub in last 3 years): https://shepherd.com/bookshelf/science-fiction/new
Filter sci-fi by subgenre, topics, and more (for example this filter shows books with AI): https://shepherd.com/bookshelf/science-fiction/book-dna?topi...
Our sci-fi book recommendation lists by authors: https://shepherd.com/bookshelf/science-fiction/book-lists
And, we've got these for 3,000+ bookshelves...
Space opera: https://shepherd.com/bookshelf/space-opera
Hard science fiction: https://shepherd.com/bookshelf/hard-science-fiction
Military science fiction: https://shepherd.com/bookshelf/military-science-fiction
History: https://shepherd.com/bookshelf/history
Nonfiction: https://shepherd.com/bookshelf/nonfiction
Biology: https://shepherd.com/bookshelf/biology
World War 1: https://shepherd.com/bookshelf/world-war-1
Math: https://shepherd.com/bookshelf/math
Astrophysics: https://shepherd.com/bookshelf/astrophysics
Philosophy: https://shepherd.com/bookshelf/philosophy
Travel: https://shepherd.com/bookshelf/travel
Fantasy: https://shepherd.com/bookshelf/fantasy
Books for 8-year-olds: https://shepherd.com/bookshelf/8-year-olds
You can browse for any genre, topic, or age group in the search bar, too.
Where does the data that drives this come from?
We've done mini-interviews with 12,000+ authors to get their favorite books. We also conduct an annual survey of readers/authors to find their 3 favorite reads of the year (https://shepherd.com/bboy/2024). I'm working to bring in more reader data and expand our book database using Open Library.
What do we use to build this?
Python, Django, Heroku, Postgres, Cloudflare, NLP/ML for Wikipedia topic IDs via Wikifier (https://wikifier.org), Nielsen’s book API database (publisher data + Library of Congress data), and Cloudinary.
What's next?
I'm working to launch a full app for readers that will be like Goodreads but smarter, more personalized, and focused on private notes. I've got some early mockups here and more info:
https://building.shepherd.com/roadmap/launch-our-tbr-app-to-...
My email is ben@shepherd.com if you want to share ideas or suggestions :)
Thanks, Ben

value: Show HN: Visually explore recommended/trending sci-fi books (and other genres)

author: bwb


value: vocenellanotte

value:
Hi HN,
I'm a solo indie developer and I built Minecrack, a lightweight Minesweeper-style puzzle game for Android.
Classic gameplay
 Multiple difficulty levels
 Works offline
 No login, no ads (just a clean experience)
The goal was to keep it simple, fast, and familiar — something to play quickly without distractions. I’d love feedback from anyone who’s a fan of logic games, UI minimalism, or retro-style mobile games.
Play Store link: https://play.google.com/store/apps/details?id=com.vdm.minecr...
Thanks in advance for checking it out!

value: Show HN: Minecrack – A simple, offline Minesweeper game for Android

author: vocenellanotte


value: fatsec

value:
I recently wrote a short piece exploring CWE-843: Type Confusion, a vulnerability that quietly lurks in low-level code, especially in C.
Type confusion bugs are sneaky the code compiles, runs, and often works just fine... until it doesn't. In the article, I walk through a practical example of how a type confusion issue can lead to exploitable memory corruption, explain why this happens at the language level.
https://dev.to/fkkarakurt/review-of-cwe-843-type-confusion-v...

value: Show HN: Review of CWE-843 Type Confusion Vulnerability and Exploit

author: fatsec


value: Lrodd

value:
When I built my last startup, I got traffic from AI tool directories, news articles, Reddit, organic search, email, and more. But I could never tell which sources were actually driving conversions to paid users, or how valuable those users were in terms of LTV, churn, etc. It was a black box.
So I built a lightweight tool for SaaS founders to connect sources of traffic (from UTM/custom referral params) to Stripe revenue. This lets founders answer questions like:
- “What traffic sources drive revenue? Where should I double down?”
- “Where do my most/least valuable users come from?”
It gives founders the signal they need to understand what marketing efforts actually work. I wanted to keep setup simple and geared towards solo founders/small teams that don't have the time or resources for complex data stacks. It involves:
- Adding a JS snippet to your site to capture UTM/referral data
- Connecting your Stripe account
- The tool matches Stripe customer emails to attribution data when revenue events occur
You get a dashboard showing traffic sources alongside revenue, LTV, churn, and weekly insights like:
- Spikes in churn for a specific channel
- New traffic sources that are driving outsized revenue
A few challenges I ran into while building this:
1. Scope creep — There are so many analytics and insight use cases. It was tough to boil this down to a minimum version that still delivers value. I'm looking for feedback on how to evolve the dashboard and insights from here, but scoping a shippable MVP with value and holding myself to it was a real challenge.
2. Cold start problem — The product’s value is in attribution, but attribution data takes time to accumulate after embedding the JS snippet. As a PLG adherent, I couldn’t afford a long time-to-value, so I also built a minimal set of Stripe revenue metrics and insights that aren't available in Stripe's default dashboards. This gives users immediate value as soon as they connect Stripe.
I’m looking for SaaS founders who want more clarity on which marketing channels to lean into. If you'd like to be an early design partner as I build this out, please sign up and I’ll reach out directly: https://www.getboone.com/?utm_source=hackernews&utm_medium=s...

value: Show HN: Easily match your traffic sources to paying customers

author: Lrodd


value:
Hi HN!
I built NaturalCron because I was tired of writing and debugging CRON syntax like:
/5  * * 5
Now you can write something human-readable in .NET:
var expression = new NaturalCronExpression("every 5 minutes on friday");
Or use a Fluent Builder for strong typing and IDE support:
var expression = NaturalCronExpressionBuilder
    .Every().Minutes(5)
    .On(DayOfWeek.Friday)
    .Build();
Great for:
- Code-based scheduling in .NET apps
- Overriding schedules from configs or databases
- Displaying easy-to-read rules in UIs
NuGet: https://www.nuget.org/packages/NaturalCron
GitHub: https://github.com/hugoj0s3/NaturalCron
Would love your feedback on syntax, builder design, and what features you'd like to see next!

value: Show HN: NaturalCron – Human-Readable Scheduling for .NET (With Fluent Builder)


value: aydinjoshi

value:
Hey HN,
I'm Aydin, a 13-year-old developer and indie maker looking to improve the world with my small startups.
Recently, I built 2 micro SaaS projects. I spent days & weeks coding features, always telling myself that after coding one more feature I was for sure to get traction.
This never happened. The reason: I never launched.
With IndieReq, you can launch your startup fast and get real user feedback so you know exactly what features to ship and improve. All you have to do is sign up for free, create a feedback board, and share the public link with your users. It's that easy!
If you've been looking for a tool like this but found the status quo (like Canny) too complex for your needs, this is for you!
I would love any feedback I can get on the project!
Thanks!

value: Show HN: I'm a 13 year old who built a user feedback board for devs to ship fast

author: aydinjoshi


value: salunmarvin

value:
I built this small macOS app in my spare time to solve something that was bothering me.
I have a standing desk… but I wasn’t really using it. I’d get deep into work and forget to stand for hours — which led to back pain and fatigue.
I didn’t want a Pomodoro timer — I wanted something more gentle, that would nudge me to stand, help me build a better routine, and gradually increase my standing time like a habit-forming system.
So I made Break in Motion.
It’s a lightweight app that:
Lives in the menu bar
Reminds you to stand and move
Tracks your streaks and progress
Increases your standing time over time (like levels)
No bloated features. Just something that does the job well.
https://www.breakinmotion.com
It’s free to try — would love any feedback from the HN community!
Thanks

value: Show HN: Break in Motion – a macOS app that helps you use your standing desk

author: salunmarvin


value: ImmuneFOMO

value:
I built Focuser because I kept doom-scrolling when I was supposed to work
What it does
You pick any time-sink site
Next visit, Focuser asks, “Do you really need this site?”
If you tap Yes, you must
1⃣ Write why you need it
2⃣ Choose exactly how long you need access
This 20 second friction is based on Shawn Achor’s habit-formation research
Why it’s different
Runs 100% client-side—no analytics, no external calls
Uses Manifest V3 already (future-proof for June 2025 Chrome deprecation)
Works offline
Settings live in localStorage
Ask
Does the 20-second rule feel too long or too short?
Any edge-cases where permissions worry you?
Ideas for a Firefox port?
Try it here (free): https://focuser.app/
I’m online and happy to answer every question. Thanks for reading!

value: Show HN: Focuser – 20-second pause that blocks doom-scrolling

author: ImmuneFOMO


value: gkoos

value:
Hi Hacker News!
I built Skyline, a Go library implementing skyline queries — a powerful algorithmic technique for filtering datasets by identifying non-dominated points across multiple dimensions. It’s useful for multi-criteria decision making, recommendation systems, and pruning large datasets efficiently.
The repo has examples, benchmarks, and is ready for contributions. Would love to hear your feedback or use cases!

value: Show HN: Skyline – A Go Library for Efficient Multi-Dimensional Skyline Queries

author: gkoos


value: andreinwald

value:
Browser LLM demo working on JavaScript and WebGPU.
WebGPU is already supported in Chrome, Safari, Firefox, iOS (v26) and Android.
Demo, similar to ChatGPT https://andreinwald.github.io/browser-llm/
Code https://github.com/andreinwald/browser-llm
- No need to use your OPENAI_API_KEY - its local model that runs on your device
- No network requests to any API
- No need to install any program
- No need to download files on your device (model is cached in browser)
- Site will ask before downloading large files (llm model) to browser cache
- Hosted on Github Pages from this repo - secure, because you see what you are running

value: Show HN: WebGPU enables local LLM in the browser – demo site with AI chat

author: andreinwald


value: vadiml

value:
  Built a tool combining MLX Whisper + pyannote for fast local audio transcription with speaker diarization on Apple Silicon.

  Key benefits: privacy-first (fully local), hardware-accelerated, automatic speaker identification, multiple output formats (TXT/SRT/JSON).

  Main technical challenge was making MLX Whisper and pyannote work together despite different audio processing - solved with preprocessing pipeline.

  Perfect for interviews, meetings, podcasts. Handles HuggingFace gated models with proper error handling.

value: Show HN: Local audio transcription and speaker ID for Apple Silicon

author: vadiml


value: mtth

value: I like to keep notes when working on a new feature (links to useful resources, ideas to try next, etc.), so I wrote a small script to emulate branch-local git-notes. These persist as commits get added, through merges and rebases, and can be shared when needed.<p>Sharing it here in case it's useful to others - feedback welcome!

value: Show HN: Git-jot – Git notes for branches

author: mtth


value:
You can play the game here: https://gomoku-e0c.pages.dev/
Open to feedback on architecture or code clarity!

value: Show HN: Gomoku game in JavaScript (GitHub and live demo)


value:
Hi everyone,
I’ve been working on Byline CMS, a TypeScript-first, open-source headless CMS built for developers (and users) who want full control over their data and hosting.
The goal is to provide:
Self-hosting freedom – run anywhere without vendor (or framework) lock-in.
TypeScript-native schemas – define content types in TS, generate admin dashboard and collection management UIs and workflows automatically.
Small, opinionated core – easy to understand, with 'grown up' features coming.
GitHub: https://github.com/Byline-CMS/bylinecms.dev
Docs & Roadmap: README - https://github.com/Byline-CMS/bylinecms.dev?tab=readme-ov-fi...
Discussion: https://github.com/Byline-CMS/bylinecms.dev/discussions
I’d love feedback, and if anyone’s interested in contributing, there's plenty to do.

value: Show HN: Byline CMS – A TypeScript-First, Open-Source Headless CMS


value: andrewxhill

value:
I’m Andrew, co-founder of Recall. Over the past few days I’ve been building Predict, a playground where anyone can:
- propose skills we should measure in language models—live examples include difficult math, memory-manipulation resistance, code generation, and empathy under bad news
- write evals (graded prompts) for those skills
- forecast which models will score highest once GPT-5 is released
Why this exists
Benchmarks leak into training data quickly; scores are unreliable and labs still declare progress. The prediction tool aims keeps the target moving by letting the crowd define both the tasks and the scoring. Accepted evals remain private until GPT-5 ships; afterward every prompt, response, and grade is published, with a checksum pinned on-chain for provenance.
A deeper bet
Simon Willison’s “draw a pelican on a bike” is such a great example of a custom prompt that surfaced insights no benchmark caught. Andrej Karpathy has noted that random crowds often miss the better answer. Some people have sharper intuition about model behavior than others; if we can identify that signal and fold it into the tooling, the crowd can stay ahead of the models instead of trailing them.
Implementation
Built almost completely w/ Claude Code (subagents enabled). Originally, working with a designer and using Figma MCP, but by the end we found it faster for him to just learn how to use Claude Code and prompt design iterations right to code. Rough edges remain, but the loop works end-to-end.
I’d value feedback—especially new skill ideas or failure modes we’ve missed.
https://predict.recall.network

value: Show HN: Predict GPT-5 skills with a community AI benchmark

author: andrewxhill


value: goodpanda

value: I use localStorage a lot for different purposes. In the past mostly to store one-off values and things that I didnt really care too much for. These days i am getting more focused on apps that keep data on client side and quickly found that localStorage can get messy with large number of fields and data etc. So this is just gonna make it a bit less messy.

value: Show HN: I Made LocalStorage Better

author: goodpanda

title: Show HN: I Made LocalStorage Better


value: OskarVolcansek

value:
Hi HN,
I started investing when I was 14 and always found it annoying to manually value companies using spreadsheets.
So I built Socks2Stocks for 3 reasons: 1. To calculate fair value in seconds without spreadsheets. 2. To stop jumping between Yahoo Finance, Macrotrends, and Excel just to get a all the data. 3. To get historical data without going bankrupt.
I named it Socks2Stocks because that’s how I started. First saving money in a sock and eventually putting it into the stock market.
Socks2Stocks lets you:
- estimate fair value using a DCF calculator(automatically)
- access 30 years of financial data
- compare up to 5 companies side by side
- view clean charts and switch to a "Berkshire mode" for fun (UI from the 90s)
Would love to hear your thoughts or suggestions.
Thanks,
Oskar

value: Show HN: I built a stock analysis tool after investing since age 14

author: OskarVolcansek


value: jgaleria

value:
* With AI variance of course *
Vibe coded this over the weekend! - Upload a product sketch, image, or describe any idea and it generates a complete Bill of Materials with real components, suppliers and pricing.
Is this useful for any makers/builders? Looking for some feedback.
GitHub: https://github.com/jgaleria/make-stream-bom-demo/tree/main

value: Show HN: Find out how much your products or idea cost

author: jgaleria


value: turblety

value: Show HN: Persisting Data with DuckDB, OPFS and WASM

author: turblety


value: conradmk

value:
Hey everyone! I'm a huge F1 fan and got tired of juggling multiple tabs and apps during race weekends, so I built F1 COSMOS.
What it does:
- Live timing: Real-time data updates in milliseconds - sector times, telemetry, team radio, you name it. No more refreshing pages or waiting for delayed updates.
- Replay feature: Missed qualifying or fell asleep during practice? You can replay the live timing from any past session. Pretty handy when you're in a bad timezone.
- Proper data visualization: I went beyond just showing lap times. There's race analysis with telemetry data, championship standings, technical updates, and a bunch of other stats that make watching races way more interesting. Oh, and the race calendar automatically adjusts to your timezone because I was sick of doing timezone math in my head.
- Multi-device setup: Here's the thing - I watch races on my TV but wanted data on my phone as a second screen. So I spent ages making the mobile experience smooth for exactly this use case. Desktop has customizable widgets if you're into that.
Technical stuff:
Built with modern web stack, focused heavily on real-time performance. The trickiest part was getting the data pipeline right for millisecond updates without everything falling apart.
Why I built this:
Honestly, existing F1 apps either suck or cost money or both. I wanted something that just works and gives me all the data I actually care about in one place.
Been using it myself all season and figured others might find it useful. Currently supports English, Spanish, Japanese, and Korean (partially) - still working on expanding language support. Would love to hear what you think if you check it out during the next race weekend.

value: Show HN: F1 COSMOS – Live timing and data dashboard for F1 fans

author: conradmk


value: gigamick

value: This is my first product as part of this project I'm working on. It's a no-frills, but perfectly functional customer support tool for indie hackers, soloprenuers and small teams. would love your feedback and suggestions of how to make more people aware.

value: Show HN: I've had success in SaaS and now I'm building tools for indie hackers

author: gigamick


value: Show HN: Stop outdated LangGraph API errors by making the AI read your docs


value: andrewfhou

value:
Hey HN!  I’m Andrew, and I’ve been building Cortex (https://cortexdesktop.com/) for the last few weeks. Cortex is my attempt to reimagine how we interact with computers - starting with a simple interface, but aiming for something deeper: an AI layer over your OS that understands what you’re doing, remembers it, and helps you dynamically.
Right now, Cortex is just a floating overlay you can summon anywhere on your Mac. It works like an inline ChatGPT, but it lets you instantly send that context into the chat by highlighting text - so you don’t have to explain what you’re doing. Here is a demo: https://www.youtube.com/watch?v=fZEbpysqH2w&feature=youtu.be
That’s all it does today but the reason I’m building it is because I think that the current way we use computers is kind of antiquated - the OS is relatively dumb and memoryless. I feel like it would be so much better of an experience to work with a computer that is contextually and semantically smart.
This started as a tool I was hacking together for myself while context-switching between projects, tabs, and apps. I was using ChatGPT a lot, but every time I wanted to ask something, I had to re-explain what I was doing. “I’m building this project with (these) specs, and (this) stack, help me plan etc etc”
I realized that firstly, it was super tedious to constantly go back to GPT to query, and secondly that it was annoying that I constantly had to feed it context to make it work the way I wanted. Granted, Chat GPT does have a certain amount of memory nowadays but I mean something far more granular - file diffing, text changes, differences in entire workflows, etc.
I feel that the OS should have memory. It should be able to understand semantically, not just react to commands. Eventually, I want Cortex to become the operating system’s memory. A system that watches what you do across apps (files, text, window titles, tabs), builds a real-time semantic timeline of your work, and lets you ask questions like “What was I working on Thursday before lunch?” Or say “Open the Figma file I was editing after that Zoom call”.
I am technically getting ahead of myself, as right now I’m just trying to test the one use case of having access to AI anywhere in the OS. This is definitely an early-stage product. It’s glitchy in spots. But if you like trying new interfaces and imagining what comes next - I’d love your feedback.
You can use it free for 7 days — no signup needed. I’d love to hear your feedback, ideas, critiques, or even thoughts on how you’d want your computer to "remember."
Thanks!
-Andrew

value: Show HN: Cortex – OS-wide AI with instant context input

author: andrewfhou


value: gkoos

value:
I built a Conway’s Game of Life implementation in plain JavaScript with no frameworks or dependencies. The code is modular and easy to follow, with a focus on performance and clarity.
The project is intended as a clean example of how to implement cellular automata with modern JS, optimized for speed but easy to understand and extend.
Live demo: https://gkoos.github.io/conway/
GitHub repo: https://github.com/gkoos/conway
Would love feedback on the code structure, algorithm efficiency, or any suggestions you might have!

value: Show HN: Conway's Game of Life in JavaScript with efficient implementation


value: danielfetz

value:
Some months ago @andrewrn tried to create a Wordle-style site for order-of-magnitude thinking. This was a wonderful idea, but the actual site was somewhat over-engineered and confusing. (https://news.ycombinator.com/item?id=43632278)
In the past week, I looked at this idea again and built a very simple site which gives you a new Fermi estimation question every day:
How many new cars were sold in the US in 2024?; How many humans have ever lived (including those currently alive)?; How many chickens are slaughtered for meat every year?
To win, you need a guess within ±20% of the correct answer. For this you have a maximum of 6 tries and after each guess, you can see if your answer was too high or too low.
Fermi questions are, by the way, a wonderful way to build up your own numeracy and sense for order-of-magnitude differences. Douglas Hofstadter proposed using them for exactly this reason in his essay "Number Numbness, or Why Innumeracy May Be Just as Dangerous as Illiteracy" (https://gwern.net/doc/math/1982-hofstadter-2.pdf)

value: Show HN: Wordle-style game for Fermi questions

author: danielfetz


value:
Sharing something that I’ve been working on:
I made a save-later app for all my bookmarks. I save links throughout the week and, every Sunday morning, the app sends me a personalized recap with: -patterns and themes that connect my week to my broader interests -a nudge toward links I saved but never revisited -one reflective question to help me decide what else might be worth exploring
I was inspired by older read-later apps like Instapaper. I wanted to make something minimalist, so it’s just a simple feed of your links (with tags and annotations linked to each link) and it is set up to ingest all kinds of content, not just text. I also did want it to be bloated as the full-fat AI stuff you see recently. So this is a simpler and more proactive take on the concept of a bookmarking app.
Happy to answer any questions. (I’m not technical.)

value: Show HN: Personalized insights from your bookmarks delivered every Sunday


value:
I built CLI tool "Repocks", a local RAG server that indexes Markdown docs under your project directory and answers questions via MCP Server.
- Uses Ollama (LLM + embeddings) and DuckDB
- No API keys, fully offline
- One server per project (runs via stdio), so no data mixing
- Ideal for replacing bloated instruction files (like CLAUDE.md)
You can install via npm: https://www.npmjs.com/package/repocks

value: Show HN: Repocks – Local RAG from In-Repo Markdown Docs


value: frendlysquirrel

value:
I've been frustrated with how noisy Twitter, LinkedIn, and Substack have gotten when trying to find genuinely good blog posts. Using a mix of AI automation and hand curation, I am building a better place to discover cool things to read. No more endless scrolling to find thought-provoking and tasteful content. A general focus on ML, AI, alignment, safety, interp, math, crypto, and startups.
Demo vid: https://youtu.be/_Ma5mhM_dXU
It’s early, but would love to hear your thoughts!

value: Show HN: Fiyka – A better way to browse blogs

author: frendlysquirrel


value: crimsoneer

value:
Hey HN! Thought I'd share this side project I've been working on in the last couple of weeks: 4 AI agents play the classic board game Risk, with make belief personas (Genghis Khan doing great, Captain Jack Sparrow not so much) and randomly selected models.
I added the new "cloaked" Horizon Alpha model last week, and it has been absolutely decimating the competition (I've also just added Horizon Beta, so we'll see how it does).
It's a lot more fun than a robust experiment, but I've found the interactions really interesting. If you'd like more detail, you can also read my blog post here: https://andreasthinks.me/posts/ai-at-play/

value: Show HN: AI at Risk, a silly LLM benchmark

author: crimsoneer


value: theahura

value:
I've been working with sqlite recently, and was pretty surprised at how bad a lot of the existing cli tools are. Most don't have tab complete or json pretty printing. Many don't automatically show table headers, which is imo very user unfriendly. And for me, personally, I kept finding myself tabbing over to Claude to ask it how to do basic joins and json extractions because I never bothered to learn/memorize SQL syntax, and didn't need anything performant for just looking through the databases.
I got to thinking it would be very easy to build a better client with AI, that also used AI. And it was -- in less than an hour I put together a cli that supports all of the above.
Most importantly, it has a built in LLM plug-in that has context for your database. You can do things like run `.ai give me the names of my customers` and the cli will make a call to Claude with your table names and table schemas as part of the context.
I've immediately found it useful in my day to day work, so I figured I'd share it here too for others to play with  lmk if there's any other features you think are worth adding!

value: Show HN: AI Enabled SQLite CLI

author: theahura

title: Show HN: AI Enabled SQLite CLI


value: piterrro

value: Show HN: Open-sourced my prompt management tool for LLM-powered apps

author: piterrro


value: adityakumarr

value:
Hey HN,
I’m experimenting with an idea that’s been on my mind for a while — what if developers could jump into a shared codebase without being overwhelmed by everything at once?
I’ve built a prototype called Shiproom — a local, browser-based IDE where access to files and folders is controlled at a granular level. Instead of seeing the whole project, each user only sees the parts they’re allowed to. No setup, no distractions, no access to sensitive stuff like .env or core business logic unless it's needed.
What Shiproom (Prototype) Does:
    Simulates a cloud dev environment with instant onboarding.

    Uses a mock file system with user-based access control.

    You can switch between users to see how their file access differs.

    Files are fully hidden if not allowed, or marked read-only if view-only.

    Runs Monaco Editor (like VS Code in the browser) entirely locally.

    Includes a dummy 2-page app to simulate real-world modular projects.

Why?
Most cloud IDEs today give you the entire repo the moment you're onboarded — which can be overwhelming for juniors, unnecessary for interns, and risky in security-sensitive environments.
With Shiproom, the idea is simple: show people only what they need — and nothing more.
This could be useful for:

    Dev teams onboarding new engineers

    Bootcamps giving students a focused coding view

    Secure contract development environments

    Even pair programming with role separation

What It Isn’t (Yet)
This is just a prototype — there’s no real authentication, no server-side isolation, and no actual code execution. It’s a simulation of the experience, running locally on Node.js + Vanilla JS. But it shows how the concept could work.
Would love feedback or thoughts. Does this use case resonate with anyone? If it’s useful, I’m thinking of turning it into a real service with:

    Auth, Git integration, isolated containers

    Team-based permissions

    Developer onboarding templates

Thanks!

value: Show HN: Shiproom – A Browser-Based Cloud IDE with File-Level Access Control

author: adityakumarr


value: MagneLauritzen

value:
Here's something different than your usual fare: A physical keypad that lets you directly type math!
Ever tried typing mathematical equations in your code IDE, email, or on Slack? You might know it can be tricky. Mathpad solves this with dedicated keys for Greek letters, calculus symbols, and more. Press the ∫ key and get ∫, in any application that accepts text. It uses Unicode composition, so it works everywhere: Browsers, chat apps, code editors, Word, you name it. Basically, anywhere you can type text, Mathpad lets you type mathematics.
I built Mathpad after getting frustrated with the friction of typing equations in e.g. Word, and what a pain in the ass it was to find the specific symbols I needed. I assumed that a product like Mathpad already existed, but that was not true and I had to build it myself.
It turned out to be pretty useful! Three years of solo development later, I'm launching on Crowd Supply. One of the trickiest parts of this project was finding someone who could manufacture custom keycaps with mathematical symbols. Shoutout to Loic at 3dkeycap.com for making it possible!
Fully open source (hardware + software): https://github.com/Summa-Cogni/Mathpad
Campaign: https://www.crowdsupply.com/summa-cogni/mathpad
Project log: https://hackaday.io/project/186205-mathpad-the-math-keypad

value: Show HN: Mathpad – Physical keypad for typing math symbols

author: MagneLauritzen


value: anonyMusk

value:
I vibe coded Jurn AI - a notion integration that lets your diary / journal talk to you.
It works by generating feedback from user’s last night journal. This feedback is then sent over mail to the user every morning with the intention of motivating them.
The idea is to give a friend/family like feel, daily checking up on you based on how your day went by.
To vibe code, used following agents, each with its own dedicated folder to store their system prompts and progress.
Frontend engineer - knows how to build a nextJS website. Responsible for building the user onboarding ramp.
Backend engineer - works with python and fastAPI. Help built the entire server side.
Program Manager - knows the requirements and the deadline. Helps keep a track of pending pointers.
Product expert - Understands what we are building and why. Helps refine Content on the landing page - optimizing layout for max user conversion. Helps in simplifying decisions
Infra Engineer - To be honest, I wasn’t able to use much of agent’s help in this. Their knowledge was outdated when it came to resolving platform specific bugs.
What do you think about this project?

value: Show HN: A Virtual friend that checks up on you, every morning

author: anonyMusk


value: Show HN: A fast proxy checker and IP rotator with ease


value: wtshex

value:
Hey HN  I’m the founder of ObscuritySecurity, a non-profit focused on privacy-first security tools. After weeks of intense work, I built TwoAuth, a fully offline 2FA authenticator — no ads, no telemetry, no cloud, no hidden SDKs.
AES-256 encrypted TOTP codes
 Panic mode with fake codes
 Biometric unlock + auto-lock + trash bin
 Backup/export with a 30-char encrypted key
 No permissions abuse — QR scan only with permission
I built the design, code, and vision by myself, for people who want true privacy. I’d love your thoughts and feedback.
GitHub: https://github.com/ObscuritySecurity

value: Show HN: TwoAuth – an offline, zero-data 2FA Authenticator

author: wtshex


value:
I recently wrote and launched a high-performance Elevation API, built from the ground up, in C. I was highly inspired by the handmade community and I was intrigued by the idea of handling fairly large datasets and optimizing caching and smart prefetching, and to cream out maximum performance in terms of latency and handling large loads.
The whole thing is built from scratch. I wanted to roll my own high performance server that could handle a lot, mostly for the technical challenge but also because it brings down hosting costs.
At the core is a hand made TCP server where a single thread handles all I/O via epoll, distributing the events to a pool of worker threads. The server is fully non-blocking and edge-triggered, with a minimal syscall footprint during steady-state operation.
Worker threads handle request parsing and perform either direct elevation lookups for single- or multi-points, or compute sample points along polyline paths.
The elevation data is stored as memory mapped geotiff raster tiles, The tiles are indexed in an R-tree for fast lookup. Given a coordinate, the correct tile is located with a bounding-box search algorithm through the tree, and the elevation value is extracted directly from the mapped memory. If the tile is missing the data, underlying tiles act as fallback.
I also implemented a prefetching mechanism. That is, to avoid repeated page faults in popular areas, I employ a strategy where each tile is divided into smaller sub-tiles. Then, I have a running popularity count per sub-tile. This information is then used to guide prefetching. More popular sub-tiles trigger larger-radius prefetches around the lookup point, with the logic that if a specific region is seeing frequent access, it’s worth pulling in more of it into RAM. Over time, this makes the memory layout adapt to real usage patterns, keeping hot areas resident and minimizing I/O latency. Prefetching is done using linux madvise, in a separate prefetch thread to not affect request latency.
There’s a free option to try it out!

value: Show HN: Fast Elevation API with memory mapped tiles


value: skyzouw

value:
Hey HN
I built Namefast, a tiny tool that helps you find creative and available names for your next SaaS, startup, or side project.
You just describe your idea in one sentence, and it instantly returns a list of name ideas that are short, brandable, and (most of the time) domain-available.
Why I built it:
I’m always struggling with naming my own projects. GPT-based suggestions often feel too generic or unrealistic (“UltraSyncify Pro Max™”). So I made something focused, fast, and a little more opinionated.
Features:
 • Fast input (no login required)
 • Suggestions based on your concept
 • Tries to balance creativity + clarity
 • Built with indie hackers in mind
Tech stack:
 • Next.js + GPT-4
 • Deployed on Vercel
 • Clean UI, no fluff
Would love to hear your feedback:
 • Do the names feel useful / usable?
 • Should I include filters (e.g. “funny”, “short”, “serious”, etc.)?
 • What would make this a go-to tool for you?
Thanks!
you can try it here : https://www.namefast.me/

value: Show HN: NameFast – Generate names for your SaaS idea in seconds

author: skyzouw


value: nasir

value: Show HN: Rudys.ai, Scale Google Ads Globally in Any Language

author: nasir


value: Brysonbw

value:
There are plenty of HTTP clients out there - Axios being one of the most popular - but I wanted something minimal and closer to the native fetch API.
I originally wrote a small fetch wrapper for a side project. Rather than copying and pasting it into other projects, I decided to expand on it and publish it as a public package.
Feel free to star the repo, and more importantly, contribute.

value: Show HN: Fetchet – A compact, promise-based, HTTP fetch wrapper

author: Brysonbw


value: jasonjmcghee

value: Show HN: SQRZ: An addictive fast-paced matching game, built in Godot

author: jasonjmcghee


value: andrewrn

value:
Hi HN. I built a prototype AI physics tutor that can interpret, draw, and edit free body diagrams.
Lately I've been transfixed with generating diagrams with LLMs. If you pipe generated JSON through a D3.js renderer, you can get pretty consistent SVG results with the smarter models.
This physics tutor prototype is an example of an application. For a couple premade scenes, you can ask it to make an FBD, decompose an angled force into components, run through the math of Newton's Second Law, or off-road and try and generate a FBD for a scene of your own description.
I previously made a similar example for electrical circuits: www.circuit-tutor.xyz
LLMs have been really fun for me to brush up on my favorite physics and engineering topics, but if they could diagram and even simulate systems while also being able to explain the math, I think it could be genuinely useful for learning concepts from scratch.
Would love any feedback on whether this, bolstered with more diagram types, better UX, and more robustness, could be useful for people learning intro physics.

value: Show HN: AI Physics Tutor with Free Body Diagrams

author: andrewrn


value: ssdevproject

value: utfitScore uses computer vision and AI to analyze outfit photos, providing detailed fashion scoring and personalized style recommendations. Users upload photos and receive instant feedback on color harmony, fit, style consistency, and overall aesthetic appeal. With three tiers (Free, Premium, Professional), the platform serves fashion enthusiasts and style-conscious consumers seeking data-driven wardrobe decisions. Early traction shows strong user engagement with our freemium model.

value: Show HN: AI-powered outfit analysis with detailed fashion scoring

author: ssdevproject


value: nadermx

value: Show HN: Xtwitt.com – X/Twitter Video Downloader

author: nadermx


value: honoyomu

value:
Hi HN, we just released InsForge: an open-source, agent-native alternative to Supabase/Firebase designed from the ground up for AI coding agents like Cline, Cursor, and Claude Code. We're building Supabase's features in an AI-native way, enabling agents to build and manage full-stack applications autonomously. (GitHub: https://github.com/InsForge/InsForge)
With coding agents, coding is actually the easy part now. You can build a working prototype for your idea in a few hours and run it locally. But to make it production-ready, you still have a long list of things to do manually, which might take a week or so:
1. Get API keys for external services
2. Set up authentication
3. Configure a database and storage
4. Add payments
5. Set up a custom domain
6. Deploy on Vercel
And none of these is really "coding." It's just you switching tabs, opening dashboards, copying tokens, pasting configs. The interesting part is your agents know exactly what to do. They can walk you through every step - "go to this URL, click that button, paste this key" - but they can't actually do it themselves. Why can't you just do it for me? Because all of these backend/devops platforms and services were built for humans, not for agents.
So we built InsForge. We built an MCP Server as middleware and redesigned the backend API to give agents persistent context, so they can:
1. Learn how to use InsForge during the session (re-check documentation if needed)
2. Understand the current backend structure before making changes, so configurations are more accurate
3. Make changes, debug, check logs, and update settings on their own
Example: you type "help me build an Instagram clone social media app" in your Cursor/Claude Code, then it will communicate and configure the entire backend on InsForge:
- Auth: Google + email/password login
- Database Tables: users, posts, comments, likes, profiles
- File Storage Buckets: avatars, post-images
And then it will write the fullstack application without you doing anything. You stay in your IDE or agent interface, focus on writing prompts and QA-ing the result, and let your agent handle the rest.
This is an early release, and we'd appreciate feedback from the community. Try it out and let us know what breaks or what features you'd want to see. We're trying to make prompt-to-production a reality!
P.S: In the coming weeks (by the end of August), we'll be launching a few new features:
- Cloud Hosting Platform
- Serverless Functions
- Site Deploy
We'll be around in the comments!

value: Show HN: InsForge – Open-source agent-native alternative to Supabase

author: honoyomu


value: This is software for my headless, PC based oscilloscope, which is controlled entirely via commands similar to the Vim text editor. I built this because I liked the idea of headless oscilloscopes; I always have my laptop around when I’m working on electronics anyway, and it’s very convenient to save images of captured waveforms. However, I found the software for off the shelf models to be annoying and cumbersome to work with. In my experience, this holds true both when opening the software and connecting to an attached oscilloscope, and when adjusting the scope settings using menus and buttons. I have also built my own oscilloscope hardware for use with Voltpeek. The specs are nothing to write home about (7.5MHz BW, 62.5MS/s), but they should be adequate for some basic debugging and measurement tasks.

value: Show HN: Voltpeek – Vim-inspired oscilloscope software


value: namuol

value:
I've been learning all about autostereograms (aka "Magic eye" illusions) recently and had a fun idea: If I can somehow get a depth image of my webcam, I can see myself in a "magic (eye) mirror" on my screen. It turns out that it's actually pretty feasible to get real-time depth estimates, at least on newer hardware and in browsers with WebGPU. To my delight, this worked pretty well, so I decided to polish it somewhat and share it here.
To be honest, all the heavy lifting is done by the depth-estimation model [1], otherwise this demo just wouldn't be possible.
I will warn you that viewing this may take some practice if you aren't already very well-versed in autostereogram viewing, and you will probably only want to run this on somewhat beefier laptop/desktop hardware, preferably in a Chromium browser.
For something less intense and mobile-friendly, I also made a sibling app that works with still images:
https://namuol.github.io/magic-eye-anything
Both projects are open-source:
- https://github.com/namuol/magic-eye-mirror
- https://github.com/namuol/magic-eye-anything
[1]: https://huggingface.co/spaces/Xenova/webgpu-realtime-depth-e...

value: Show HN: Realtime Magic-Eye Mirror

author: namuol

title: Show HN: Realtime Magic-Eye Mirror


value: nikkisharma

value:
Hi HN — I’m a senior director at Intel with 20+ years of experience leading AI product strategy and go-to-market (GTM) for emerging technologies, including developer ecosystems, edge computing, and AI platforms.
Being a founder myself early in my career and living through the struggle with product-market fit, complex messaging, and go-to-market execution, I’m now offering a live 3-session masterclass for AI founders who want to:
• Craft a clear GTM strategy tailored to their AI product
• Build messaging that resonates with decision-makers, not just technical teams
• Launch with confidence, with a 30-60-90 day GTM plan in hand
This is not a course on AI or sales tactics — it’s a hands-on, strategy-driven class with templates, frameworks, and optional 1:1 consults.
Details and signup: https://maven.com/renuka-awasthi/ai-go-to-market-gtm-strateg...
Happy to answer any GTM-related questions in the comments!

value: Show HN: GTM Strategy Masterclass for AI Founders (3 sessions, $2.500)

author: nikkisharma


value: kianworkk

value:
Hi HN,
I built OnlyFeets, a web app that lets users generate custom foot imagery with AI.
Describe what you want—pose, style, skin tone, etc.—and get unique images instantly. No stock photos, just AI-generated content based on user prompts.
Demo: https://onlyfeets.app
Feedback on the AI generation pipeline, user flow, or technical implementation is welcome.

value: Show HN: OnlyFeets – AI-Powered Custom Foot Image Generator

author: kianworkk


value: dottchen

value:
Hi HN!
I built *BookTranslator.app* (https://www.booktranslator.app/) initially to help myself read English books in my native language. Later on as I shared on twitter, more and more people were finding it useful. So I thought it might also be helpful to share it here.
You can drag-and-drop an *EPUB or PDF (≤ 50 MB)*, pick one of *76 target languages*, and ~60 seconds later you get a layout-preserving translation plus a side-by-side bilingual reader.
The whole pipeline runs on the gpt-4o API with a bit of prompt-engineering to keep chapter structure, images and footnotes intact.
### Why I think it’s worth showing
* Most “AI translators” still force you to split books into chapters or plain text; I wanted true *one-click, whole-file* handling.
* Speed: 100k words finishes in about a minute because translation requests are parallelised at the section level.
* The bilingual view has proven handy for language learners and volunteer proof-readers.
### Tech stack
* *Frontend*: Next.js + Tailwind.
* *Backend*: Node.js with GPT-4o calls
### Try it (no signup)
There’s a *guest tier* without needing for signup and a *free tier)) providing 1,000 free credits so you can upload a small chapter or novella. Full pricing starts at a \$10/mo Pro plan.
### Looking for feedback
1. Accuracy vs. speed trade-offs – would you prefer a slower “highest-quality” model option?
2. Does the side-by-side reader help, or would you rather download just the translated EPUB/PDF?
3. Any edge cases (RTL languages, math formulas, EPUB3 media overlays) I should prioritise?
### Caveats & next steps
* Still ironing out rare formatting glitches (tables, SVG images).
Thanks for reading—happy to answer anything!

value: Show HN: BookTranslator – one-click full-book translation

author: dottchen


value:
Hi HN –
I hacked together AlephAI (https://alephai.net/) because I kept reaching for Runway’s Gen-4 Aleph model but wanted a dead-simple, single-page UI I could put in front of non-technical teammates.

value: Show HN: AlephAI – Video-to-Video Style Transfer in the Browser


value: hrtk

value: Show HN: Axilöck – VCS Agnostic Secret Prevention

author: hrtk


value: byronknoll

value: Show HN: I built a hair cutting robot

author: byronknoll

title: Show HN: I built a hair cutting robot


value:
Hi HN — we're the team behind ArchGW [1], an edge and service proxy for agents written in Rust, and we just recently published our research on LLM Routing: https://arxiv.org/abs/2506.16655
As teams integrate multiple LLMs - each with different strengths, styles, or cost/latency profiles — routing the right prompt to the right model becomes a critical part of the application design. But it's still an open problem. Most routing systems fall into two camps:
- Embedding-based routers use intent classifiers — label a prompt as “support,” “SQL,” or “math,” then route to a matching model. This works for simple tasks but breaks down in real conversations. Users shift topics mid-conversation, task boundaries blur, and product changes require retraining classifiers.
- Performance-based routers pick models based on benchmarks like MMLU or MT-Bench, or based on latency or cost curves. But benchmarks often miss what matters in production: domain-specific quality or subjective preferences like “Will legal accept this clause?”
Arch-Router takes a different approach: it decouples route selection from model assignment. Developers can write route policies using a domain-action taxonomy (like "engineering" or "image editing" respectively), and the router maps the prompt (and conversation context) to those policies using a lightweight 1.5B autoregressive model. No retraining, no fragile if/else chains. We built this with input from teams at Twilio and Atlassian. Arch-Router handles intent drift, supports multi-turn conversations, and lets you swap in or out models with a one-line change to the routing policy. Full details are in our paper, but here's a snapshot:
Specs:
- 1.5B params — runs on a single GPU (or CPU for testing)
- No retraining needed — point it at any mix of LLMs
- Routing can be cost, latency or quality aware based on your preferences
- Outperforms larger closed models on our conversational routing benchmarks (benchmarks in the paper)
Links:
- ArchGW (open source edge and service proxy for agents ): https://github.com/katanemo/archgw
- Model + code: https://huggingface.co/katanemo/Arch-Router-1.5B
- Paper: https://arxiv.org/abs/2506.16655

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