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Products that do what I used an LLM to parse HN Who's Hiring comments to structured job data does
Hello! I used an LLM to extract structured data from each comment on the “Ask HN: Who is Hiring? (January 2024)” post, available at: https://news.ycombinator.com/item?id=38842977. This created a dataset of 400+ jobs with data such as title, company name, location, is job remote, salary data, and the URL/email to contact. For the UI, a NextJS static site was created to filter and view the structured data.
- 1HH
Hi HN! A few days ago I saw a graph[0] that showed the # of job postings on HN was declining. I started wondering what other trends I could glean from the data, so I created this! You can filter through the top level comments by keyword; for example you can filter by "remote" to see the massive spike around March 2020. Another interesting thing I found is that I can compare hiring across cities. I hope you enjoy! I made it so that the links to your search are sharable so if you have some interesting data you should be able to just link the page you're on! [0]…
2023 · hnhiringtrends.com
- 2TW
Hello HN Community! I've transformed the "Ask HN: Who's hiring? (November 2023)" post into a Google Sheet. Here's a quick rundown of the method: I utilized the Hacker News Algolia Search API to extract data. You can find the specific thread URL here: https://hn.algolia.com/api/v1/search_by_date?tags=comment,st... Using a GET request, I fetched comments from the thread and processed them via the ChatGPT API. Employing the ChatGPT API for each comment, I parsed crucial job details such as company, position, location, and more. This information was structured and…
2023 · docs.google.com
- 3DA
2024 · basc.substack.com
- 4HR
Hey HN! I'm excited to show off this side project I've been working on. This project matches your resume with the best matching jobs from the monthly HN Who's Hiring post. It works by creating a vector embedding of your resume using OpenAI's embedding API, and then ranking the jobs using a vector similarity score. (You can toggle between max inner product, cosine, and euclidean in the "Advanced Options") I was laid off in August and it took a whole 6 months for me to find my new job. Fortunately, I found my new role on January's HN Who's Hiring post. So I hope this will prove useful to any…
2023 · hnresumetojobs.com
- 5RL
We've been building data pipelines that scrape websites and extract structured data for a while now. If you've done this, you know the drill: you write CSS selectors, the site changes its layout, everything breaks at 2am, and you spend your morning rewriting parsers. LLMs seemed like the obvious fix — just throw the HTML at GPT and ask for JSON. Except in practice, it's more painful than that: - Raw HTML is full of nav bars, footers, and tracking junk that eats your token budget. A typical product page is 80% noise. - LLMs return malformed JSON more often than you'd expect, especially with…
Mar 2026 · github.com
- 6KG
Hi HN! My latest side project is knowledge graph that maps the French culinary network using data extracted from restaurant reviews from LeFooding.com. The project uses LLMs to extract structured information from unstructured text. Some technical aspects you may be interested in: - Used structured generation to reliably parse unstructured text into a consistent schema - Tested multiple models (Mistral-7B-v0.3, Llama3.2-3B, gpt4o-mini) for information extraction - Created an interactive visualization using gephi-lite and Retina (WebGL) - Built (with Claude) a simple Flask web app to clean and…
2025 · theophilecantelob.re
- 7
Find your next hire or your next role from Hacker News monthly threads. AI-powered matching between candidates and job postings.
5d ago · hnmatchmaker.com
- 8AO
2018 · letstalkalgorithms.com
- 9TA
I built this tool because I wanted a way to just take a bunch of URLs or domains, and query their content in RAG applications. It takes away the pain of crawling, extracting content, chunking, vectorizing, and updating periodically. I'm curious to see if it can be useful to others. I meant to launch this six months ago but life got in the way...
2024 · embedding.io
- 10JA
There are existing HN job aggregators, but I thought we could take it a step further. Inspired by an insightful comment on a previous thread (https://news.ycombinator.com/item?id=36163021), I built a tool that aggregates job postings and intelligently categorizes them based on user-specific preferences: * Country and remote work preferences * Employer type (e.g., startup, corporation, government) * Industry * Technologies used * Role type (developer, architect, product owner, etc.) * Salary range (where available) One of the superpowers of LLMs is reformatting information from…
2023 · kadoa.com
- 11AJ
This is a personal experiment that uses LLMs to rank unstructured job posting data based on user-defined criteria. Traditional job search platforms rely on rigid filtering systems, but many users lack such concrete criteria. One of the superpowers of LLMs is understanding unstructured data, like the job postings in the monthly "Ask HN: who's hiring" threads. So I built a little tool that lets you define your preferences in a more natural way and then rates each job postings based on the relevance. You can define what you're looking for in simple terms and get a custom list ranked by…
2023 · github.com
- 12AT
Hi HN, I spent a few weeks looking at the top HN posts of all time. This included exploration, clustering, creating visualizations, and zooming in on what (to me personally) seems like some of the best discussions on here. Three things in this post: 1- The interesting groups of HN posts 2- The interactive visualizations that you can explore in your browser 3- The data from this exploration -- this includes CSV of the titles as well as the text embeddings of 3,000 Ask HN articles. Blog post about this whole process here: [1] ============ 1- The interesting groups of HN posts From the…
2022
- 13AN
When building workflows that rely on LLMs, we commonly use structured output for programmatic use cases like converting an invoice into rows or meeting transcripts into tickets or even complex PDFs into database entries. The model may return the schema you want, but with hallucinated values like `invoice_date` being off by 2 months or the transcript array ordered wrongly. The JSON is valid, but the values are not. Structured output today is a big part of using LLMs, especially when building deterministic workflows. Current structured output benchmarks (e.g., JSONSchemaBench) only validate…
Apr 2026 · interfaze.ai
- 14LS
2024 · github.com
- 15HH
TLDR: Build a quick HN profile to see how little context LLMs need to personalise your feed. Rate 30 posts once, get a permanent ranked homepage you can return to. Our goal was to build a tool that allowed us to test a range of "personal contexts" on a very focused everyday use case for us, reading HN! We are exploring use of personal context with LLMs, specifically what kind of data, how much, and with how much additional effort on the user’s part was needed to get decent results. The test tool was a bit of fun on its own so we re-skinned it and decided to post it here. First time posting…
2025 · hackernews.coffee
- 16IM
I noticed the who's hiring threads are very popular every month, so I decided to create a job board specifically for hacker news. You can tag jobs, search, view user's profiles and more. Tell me what you guys thing! Any feedback is appreciated.
2013 · hnjobs.org
- 17HA
Hey HN, I built a UI on top of the "Who is hiring" posts. Take a look at https://hnwork.app! One of the downsides of unstructured text posts is the readability due to it being free-form and having little to no format. While there are other tools that have been built over the years to make perusing Who is hiring posts easier, I took a try on making my own (I actually tried to build this at a YC hackathon a few years back, but got around to completing it recently). Features: 1. Text search and search filters 2. Original post text with call outs to important information 3. Removes…
Jul 2026 · hnwork.app
- 18IM
I vibe-coded a small project that turns the “Ask HN: Who is hiring?” thread into searchable job data using OpenAI, PostgreSQL, and Metabase. It pulls the thread using the Hacker News API, uses GPT to extract fields like company, role, location, salary, and contact, stores everything in PostgreSQL, and spins up Metabase so you can explore and search the results. Right now it runs locally, but would anyone be interested if I built this out a bit more and made a public dashboard?
2025 · github.com
- 19
- 20JB
2015 · github.com
- 21WI
Hi HN, I made Ethos, an open-source tool to visualize the discourse on Hacker News. It extracts entities, tracks sentiment, and groups discussions by concept. Check it out: https://ethos.devrupt.io This was a "budget build" experiment. I managed to ship it for under $1 in infra costs. Originally I was using `qwen3-8b` for the LLM and `qwen3-embedding-8b` for the embedding, but I ran into some capacity issues with that model and decided to use `llama-3.1-8b-instruct` to stay within a similar budget while having higher throughput. What LLM or embedding would you have used within the…
Feb 2026 · ethos.devrupt.io
- 22BY
Hi Hacker News, I developed an open source browser extension for summarizing Hacker News articles with OpenAI and Anthropic LLMs. It currently supports Chrome [1] and Firefox [2] (desktop). The extension adds the summarize buttons to the HN front page and article pages. It is bring-your-own-key, i.e. there's no back end behind it and the usage is free, you insert your API key and pay only for tokens to your LLM provider. [1] https://chromewebstore.google.com/detail/hacker-news-tldr/oo... [2]…
2024 · github.com
- 23IB
(not sure why my previous post didn't appear on Show HN even though I included it in the title, mods please remove if not allowed) Ever applied for a job and never heard back? Many companies just go silent instead of sending rejection emails, leaving you guessing whether to keep waiting or move on. I faced this frustration during my own internship search, especially when there was no real point of contact (automated replies don't count, lol). So, I built didtheyghost.me, a simple open-source tool that crowdsources job application responses. This isn't a job scraper or another job board. It's…
2025 · didtheyghost.me
- 24SE
I built a CLI tool in Go that extracts structured data (JSON, CSV, Parquet) from messy PDFs and HTML pages. The core idea: LLMs are great at understanding structure but wasteful for bulk data extraction. So smelt uses a two-pass architecture: 1. A fast Go capture layer parses the document and detects table-like regions 2. Those regions (not the whole document) get sent to Claude for schema inference — column names, types, nesting 3. The Go layer then does deterministic extraction using the inferred schema This means the LLM is never in the hot path of actual data processing. It figures out…
Mar 2026 · github.com
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