2025년 9월 25일의 Show HN

Hi HN, I made Lingo - the SQLite of semantic search.

I'm a self-taught developer and researcher who left school at 16, and I've spent some time exploring a first-principles approach to system design for various frontier problems. In this case it's AI that challenges the 'bigger is better' transformer paradigm.

Lingo is the first piece of that research, a high-performance linguistic database designed to run on-device.

The full technical overview and manifesto is here: https://medium.com/@robm.antunes/bcd1e9752af6

The paper has been archived on Zenodo with a DOI: https://doi.org/10.5281/zenodo.17196613

The code is open-source and can be found at https://github.com/RobAntunes/lingodb, it's currently broken and feature incomplete but I'm working on it - just wanted to start getting some feedback.

All benchmarks are reproducible from the repo and can also be found in the various texts.

As an independent without academic affiliation, I'd be incredibly grateful for your feedback! I'm here to answer any questions.

Cheers!

Hey HN, We’re Alex, Land, and Rajit. We’re building Prism (prismai.sh), a tool that helps browser agents authenticate onto websites with user credentials. Developers pass in credentials, Prism logs into a website on their behalf, and hands them back the cookies so they have an authenticated session. Here’s an example of how developers can use Prism to complete username/password flows (https://youtu.be/SEtVUnWnxuE), and here’s an example of how developers can use Prism to complete login flows that require an OTP code (https://youtu.be/fe9w9PvrwH0).

We spoke to browser agent developers and saw people copying and pasting credentials and even credit card numbers directly into model system prompts. We were surprised that there wasn’t a better way to give agents access to websites on a human’s behalf. Moreover, we noticed that every company had to build infrastructure to manage OTP, TOTP, and MFA and that auth remained a significant hurdle in agent reliability. We wondered if this was a boring part of the problem of building web automations that someone could automate away.

We started working with Casco, an autonomous security testing company, to enable their agent to access customer sites. Before a pentest, Casco makes a request to Prism’s API specifying test user credentials, a domain, and a login method. For example, give me an authenticated session for the account [email protected] for OpenAI via OTP code over email. Our agent logs in on their behalf (without exposing credentials to a model), and we download the cookies and send them back in the response.

To maintain speed and reliability, we use playwright in most cases to login (which gives us speed), and we fallback to AI on failure (which gives us reliability). We have a number of websites we support out of the box and add new scripts as the number of websites we need to support grows. We are working on a way for the agent to update the existing playwright script on failure, so our scripts always stay up to date.

To try our api, you can use our API playground docs.prismai.sh/api-reference/endpoint/login to sign into x.com with the following API key: pk_54abb1cd0a637eb973ed690416e71a953e98f2ea839cf16529bbfa41a41bc016 .

We’d love to learn more about how other developers give agents access to their accounts. We look forward to everyone’s feedback and comments.

Phishcan provides crucial threat intelligence, and it currently tracks phishing domains for:

• Scotiabank, Desjardins, RBC, Interac…

• Telecom providers, provincial power and health services...

• Federal & provincial services, CRA, Canada Post, Service Canada, Revenue Québec...

How Phishcan works:

• Parsing millions of domains: Continuously scanning and analyzing vast numbers of domains to detect suspicious patterns and potential phishing sites.

• Monitoring threat actors : close watch on cyber‑criminal infrastructures and their new domain registrations.

• Data enrichment : adding contextual insights and connections to improve the information

• Feeds are updated every 12 hours.

• You can use the API freely at: https://phishcan.com/api-docs

Data is also available on: https://github.com/Phishcan/phishcan-data

I plan to improve the whole platform with more data during my free time!

It’s still young, but they are shipping fast, and it's open source. Anyone else playing with it?

Small businesses use 10+ apps to run their operations. CRM, project management, invoicing, team chat, reporting - all disconnected. Besides this, they don't have any system in place. That's why we offer much more than a SaaS PM tool, a business OS.

Built specifically for 5-150 person teams (not enterprise bloat) Plug n play setup Priced like a single tool, replaces 5-7

Try it: aqtos.com

Questions? Happy to answer anything about the tech stack, business model, or SMB pain points we're solving -> https://x.com/DamjanDano

As a musician, I was frustrated by online collaboration tools that either had no curation (everything gets mixed together) or were too restrictive (only the creator decides).

So I built Jamfound: a democratic music collaboration platform where the community decides what sounds good.

Here's how it works: 1. Someone uploads a base track (max 30 seconds, WAV) 2. Musicians contribute stems (bass, drums, vocals, etc.) 3. The community votes on their favorite contributions 4. The winning stems are automatically mixed into the final track

It's like a musical version of Reddit's upvoting system, but for audio.

Built with Flask + React, supports high-quality WAV files, includes BPM detection and automatic mixing.

Try it: https://jamfound.com Code: https://github.com/Jamfound/Jamfound

The voting system prevents the chaos of endless revisions while keeping the collaborative spirit alive.

We build a platform to create Polars data pipelines and run them end-to-end. Data can come from our Rust scraping engine (browser management + proxies, scales across containers), api/db connections or from excel/csv files. It’s a quicker way to go from “I need this dataset” to “here’s the pipeline + structured output,” without hand-writing a ton of boilerplate.

Hi HN,

I built LeetEngineer because while software engineers have platforms like LeetCode or HackerRank to prepare for interviews, non-IT engineers (mechanical, civil, aerospace, manufacturing, etc.) have almost nothing.

From my own experience applying for 500+ jobs, I realized interviews for engineers often focus on scenario-based questions that test how you apply engineering skills to real-world problems. I wanted a tool that helps with exactly that.

With LeetEngineer, you just paste a job description and the platform generates tailored, scenario-based practice questions so you can walk into your interview prepared and confident.

This is the first MVP and I’d love feedback from this community. https://leetengineerai.com

What do you think about the idea, and what features would you find most useful?

Thanks!

A Proxmox VE virtual machine management API service developed in Go, automatically downloads official images and completes end-to-end deployment. Supports one-click automated deployment for Debian, Ubuntu, and RockyLinux.