2025 AI PM Evaluation Framework
Why I Built This [This conversation](https://www.youtube.com/watch?v=rcz39Y0qFxw) between [Aakash Gupta](https://x.com/aakashg0) and [Jaclyn Konzelmann](https://x.com/jacalulu) (Google's Director of AI Product, on his [podcast](https://www.news.aakashg.com/s/product-growth-podcast)) truly inspired me. Jaclyn's AI PM evaluation framework was so clear and rigorous that I immediately thought: "I need to measure myself against this." "In disaster relief, you don't map safe routes and hide them. You share them." I started outlining…
2025 AI PM Evaluation Framework launched on October 28, 2025 with 12 votes, #913 of 8,178 launches that month and more than 75% of that year's launches.
What it does
Built for hiring teams evaluating AI PM candidates and especially for people from non-traditional backgrounds looking to transition into AI Product Management roles. It uses: OpenAI GPT-5, Anthropic Claude Sonnet 4.5, or Google Gemini 2.5 Pro.
Rigorous open-source AI Product Manager evaluation framework. Free AI PM resume analyzer using GPT-5, Claude, Gemini. 6-pillar assessment for hiring AI PMs. Built for teams seeking builders over coordinators.
A rigorous, open-source way to evaluate Applied AI Product Manager candidates in an era of weekly model releases. Built for teams who need builders, not coordinators. This conversation between Aakash Gupta and Jaclyn Konzelmann (Google's Director of AI Product, on his podcast ) genuinely inspired me. Jaclyn's evaluation framework was so clear and rigorous that my first thought was simple: I need to measure myself against this. I started outlining her criteria as a self-assessment, then realized it shouldn't be a private checklist. So it became a framework with a purpose: give everyone, especially people from non-traditional backgrounds, an actionable guide to what to build, where to focus,…from aipmframework.com
In the maker’s words, at launch
Why I Built This [This conversation](https://www.youtube.com/watch?v=rcz39Y0qFxw) between [Aakash Gupta](https://x.com/aakashg0) and [Jaclyn Konzelmann](https://x.com/jacalulu) (Google's Director of AI Product, on his…
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Mocked2025 · trymocked.com · ▲14Hi HN, I launched an AI tool a few months back to help with product management interviews. It's Leetcode-style prep, but you can verbally respond to questions and receive feedback. I originally started it as a side project, but it blew up on Linkedin and we're nearing 5-figure ARR. I would be grateful for some honest feedback and advice on both the growth and engineering side. I'm particularly interested in: - What's one feature you feel is glaringly missing? - How did similar educational consumer apps (7sage, Leetcode) scale beyond just ads? - Should I implement a landing page? I wanted to…
- AFA free AI risk assessment tool for LLM applications2025 · gettavo.com · ▲37
We’ve built an AI risk assessment tool designed specifically for GenAI/LLM applications. It's still early, but we’d love your feedback. Here’s what it does: 1. it performs comprehensive AI risk assessments by analyzing your codebase against different AI regulation/framework or even internal policies. It identifies potential issues and suggests fixes directly through one click PRs. 2. the first framework the platform supports is OWASP Top 10 for LLM Applications 2025, upcoming framework will be ISO 42001 as well as custom policy documents. 3. we're a small, early stage team, so the…
Create LLM graders and run evals in JavaScript with one file2025 · github.com · ▲28Hi HN! Run it: OPENROUTER_API_KEY="sk" npx bff-eval --demo We built a tool to help people take LLM outputs and easily grade them / eval them to know how good an assistant response is. We've built a number of LLM apps, and while we could ship decent tech demos, we were disappointed with how they'd perform over time. We worked with a few companies who had the same problem, and found out scientifically building prompts and evals is far from a solved problem... writing these things feels more like directing a play than coding. Inspired by Anthropic's constitutional ai concepts, and amazing…
aifeedMay 2026 · aifeed.dev · ▲10Hi HN! I built aifeed as a simple, real-time feed for AI-related links. It's meant for following new tools, articles and projects as they appear. You can also save interesting links to your favorites so they don't get lost. Submissions are community-driven, with light moderation and a small fee to reduce spam. Happy to hear any feedback.
i built an AI code reviewer for github (used it on itself during dev)2025 · codii.dev · ▲6I’ve spent the last 2.5 months building a product that runs LLM-powered code reviews on my pull requests — and I just launched it. The tool is built specifically for solo developers. You install it on your repo, trigger a scan by creating a pull request, and it leaves structured review comments using OpenAI under the hood. Funnily enough, I used the dev version of this app to review its own pull requests while building it. It helped me spot bugs, simplify structure, and keep quality high — all with minimal need for another human in the loop. Things I want to try out in the next months : -…
- WWWe wrote a book on LLM system evals with a bear and fox2024 · ▲11
Hey all! @sridatta and I wrote a book/zine called Forest Friends on system evals for LLM-driven apps. But it's a bit more whimsical, a bit more visual, and very much inspired by the meme of LLMs being a shoggoth polished into a smiley face with RLHF. LLM system evals are important as companies move past the flashy AI demos to reliable production apps. System evals keep coming up as the answer for what you "should do", but it's not exactly a standard part of the software engineering toolkit. So we pulled from @sridatta's seven years as a research engineer at Google, plus a ton of best…
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Source: Product Hunt launch ↗ · launch text quoted in part
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I went down the rabbit hole on a side project and ended up building this: Strange Attractors(https://blog.shashanktomar.com/posts/strange-attractors). It’s built with three.js. Working on it reminded me of the little "maths for fun" exercises I used to do while learning programming in early days. Just trying things out, getting fascinated and geeky, and being surprised by the results. I spent way too much time on this, but it was extreme fun. My favorite part: someone pointed me to the Simone Attractor on Threads. It is a 2D attractor and I asked GPT to extrapolate it to…
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