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Products that do what AI Trolley Problem Arena does

I built a tool that presents custom trolley problems to GPT, Claude, Gemini, Llama, Grok, and DeepSeek simultaneously and streams their ethical reasoning in real-time. Some interesting findings: - The models are surprisingly split on classic dilemmas. - Models will protect their creator (Sam Altman vs Dario Amodei) - Criminals are not valued equally even when compared to itself Try it: https://aitrolleyproblem.com

  1. 1

    Every problem is the trolley problem

    2022

  2. 2IB

    Hi HN, I'm the creator of this project. For the past months, I've been working on building an AI agent that could move beyond simple generation and tackle inventive challenges autonomously. The core idea was to create a system with a "metacognitive loop"—the ability to recognize when it's stuck on a fundamental problem and then launch a sub-mission to solve that specific bottleneck before continuing. The linked article is a deeper introduction to the system's architecture and a snapshot from a recent run. I tried to design it to be evidence-grounded and self-critical to avoid the pitfalls of…

    2025 · robw1se.substack.com

  3. 3IB

    I haven't seen anything like this so I decided to build it in a weekend. How it works: You see a bunch of things pulled from Wikipedia displayed on cards. You ask yes or no questions to figure out which card is the secret article. The AI model has access to the image and wiki text and it's own knowledge to answer your question. Happy to have my credits burned for the day but I'll probably have to make this paid at some point so enjoy. I found it's not easy to get cheap+fast+good responses but the tech is getting there. Most of the prompts are running through Groq infra or hitting a cache…

    Apr 2026 · sleuththetruth.com

  4. 4AG

    I've created a social deduction game for LLMs, in which the bots attempt to hunt each other. It's a Mafia group turing test: the models are told to find who the bot is - where, in fact and unbeknown to them, they are all bots. I did this a while back so models aren't the newest, and they are all non-thinking (for speed and token costs). Et voilà.

    Jan 2026 · hiding-robot.vercel.app

  5. 5GV

    Hey HN, I just updated my project that compares some LLMs. It uses your prompt for all the models and runs at the same time. You can see the results being generated in real-time and decide what's the best for your use case. I'm open to any suggestions and feedback. Thanks!

    2024 · geminivsgpt.com

  6. 6IM

    Hey HN! Thank you for all the support and feedback on my original submission 2 months ago. I've been improving the backend using a MCTS/AlphaZero approach and it's currently producing much better results. My long term goal is to allow users to manage multiple projects, deployed autonomously, both from scratch and by making continual updates all prompted with natural language. The cost of each project has been lowered to $9 as performance with smaller models has improved (I migrated from Claude-3-Opus to gemini-1.5-flash). Thanks for checking it out!

    2024 · saas-quick.com

  7. 7IM

    Hey HN! I got tired of AI agents being a pain to set up, impossible to customize without a PhD, and only viable if you're some Fortune 500 company. So I built something different, a chatbot you can literally drop onto your website with a single script tag. Create an account, add your domain, customize literally everything (theme, icon, welcome message, suggested responses, whatever), and you're done. The bot scrapes your site once a day to understand your business, or you can just upload docs-pricing sheets, policies, FAQs, you name it. That's your chatbot's brain right there. It only works…

    Oct 2025 · sitesidekick.io

  8. 88B

    Hey all, Justin here. I previously built Phind, the AI search engine for developers. One of the biggest problems we had there was figuring out what went wrong with bad searches. We had tons of searches per day, but less than 1% of users gave any explicit feedback. So we were either manually digging through searches or making general system improvements and hoping they helped. This problem gets harder with agents. Traces are longer and more complex. It takes more effort to review them, so I'm building a tool that lets you analyze LLM outputs directly to help developers of LLM apps and agents…

    Jan 2026 · trails-red.vercel.app

  9. 9IB

    Hi HN, I’m the creator of Cordum. I’ve been working in DevOps and infrastructure for years (currently in the fintech/security space), and as I started playing with AI agents, I noticed a scary pattern. Most "safety" mechanisms rely on system prompts ("Please don't do X") or flimsy Python logic inside the agent itself. If we treat agents as autonomous employees, giving them root access and hoping they listen to instructions felt insane to me. I wanted a way to enforce hard constraints that the LLM cannot override, no matter how "jailbroken" it gets. So I built Cordum. It’s an open-source…

    Jan 2026 · github.com

  10. 10IS

    Hey HN! For that last 8 months I've been trying to make agents that can hack web applications to find vulnerabilities in them - An AI Security Tester. The system has 29 agents in total, a custom LLM Orchestration framework which works on the task-subtask architecture (old-school but works amazingly for my use case, and is pretty reliable) with custom agent calling mechanism. No Auo-Gen, Langchain and Crew AI - Everything custom built for pentesting. Each test runs in an isolated Kali linux environment (on AWS Fargate), where the agents have full access to the environment to undertake any…

    2025

  11. 11PS

    I didn't want to buy a standalone computer or repurpose a laptop to run constantly so I could maintain a system to sync my LLMs, so I built this. It's a simple overview of my system, laid out in a way easy to unpack and replicate for yourself. The project is meant to be configured individually, and uniquely, since one solution might not be what's best for another. If anything, maybe it gives you some ideas on how to implement things for your own project. Best wishes, Ryan.

    27d ago · pacslate.com

  12. 12AA

    Looking for feedback on how Props can make your life easier as an LLM application developer.

    2024 · wwww.getprops.ai

  13. 13IB

    Hi HN, I built ChatOne while working on a project and constantly switching between AI models like GPT-4 and newer ones like Claude 3.5. I kept wondering if I was missing out on better answers, so I created ChatOne to get responses from multiple models at once and compare them easily. -Teddy

    2024 · chatone.io

  14. 14AL

    Hi HN, I built this to address what I see as the fundamental problem with ReAct-style agents: compounding errors. Even a small mistake made early enough in the loop can snowball and ruin the final output. But with search, agents can look multiple steps ahead and backtrack before committing to a particular trajectory. This has already been shown in a few papers to help agents avoid mistakes and boost overall task performance, but there's no easy way to actually build these kinds of agents. So that's why I made this framework. I believe search will eventually become table stakes for building…

    2024 · github.com

  15. 15AB

    Hi everyone! My team and I just open-sourced a bunch of cool agent dev tools: Invariant Explorer to visually inspect and understand AI traces and a testing framework, building on pytest.

    2024 · github.com

  16. 16IB

    Hey HN. I built an AI agent harness over the past few months and I'm open sourcing it today. Some context on why. I've been building with Claude Code daily using this harness. It orchestrates multiple AI agents as a team, with a dashboard, chat, kanban board, the works. I used it to build a full SaaS product (MyUpMonitor, https://myupmonitor.com) in about 24 hours of focused coding. Then yesterday Anthropic announced Mythos and decided to keep it behind closed doors. Meanwhile I'm paying for Claude and I can't access their best model. I don't think that is nice at all... So I'm…

    Apr 2026 · github.com

  17. 17IB

    hey hacker news! no matter what I have tried, nothing actually got rid of spam calls. built an AI agent that picks up your phone to filter out these spammers dynamically. next on the roadmap is automating scheduling

    2025 · apps.apple.com

  18. 18AA

    Hey folks, I'm Yuval. I run a tiny startup called Glitter AI. It's just me full-time here, with a couple of freelances to help here and there. A couple of months ago, I went from managing zero requests to hundreds -- overnight (won Product of the day on Product Hunt). As someone who gets VERY easily distracted (maybe you relate), I had to find some sort of way of handling all the chaos if I didn't want to burn out. I came up with a pretty cool automation flow that I thought folks on HN here may be interested in reading about :) So here goes: Most of my interactions come through Intercom.…

    2024

  19. 19FA

    Founder here. I built NEO, an AI agent designed specifically for AI and ML engineering workflows, after repeatedly hitting the same wall with existing tools: they work for short, linear tasks, but fall apart once workflows become long-running, stateful, and feedback-driven. In real ML work, you don’t just generate code and move on. You explore data, train models, evaluate results, adjust assumptions, rerun experiments, compare metrics, generate artifacts, and iterate; often over hours or days. Most modern coding agents already go beyond single prompts. They can plan steps, write files, run…

    Jan 2026 · marketplace.visualstudio.com

  20. 20IC

    For the last few months I have been analysing Peter Lynch’s books on stock picking and doing prompt engineering to check if AI could create useful stock analyses. To my surprise it started making reports that allow me to understand companies much faster with well cited sources. I hope you find it interesting and useful :) Perter Lynch’s books I analyzed: Learn to earn, One up on Wall Street, Beating the street

    Jun 2026 · github.com

  21. 21IB

    Hey HN! I just released a suite of AI models for deployment on UAV and other "overhead" devices to provide some understanding of the world below. The objective is to empower all sorts of open-source use cases around search and rescue, wildfire prevention, ground risk mitigation for flight over populated areas etc... The neural networks are trained for a bunch of different devices from big GPUs to tiny edge AI cameras like the Luxonis OAK, with some optimised ones for Nvidia TensorRT and other cool bits and pieces too. The main release package also includes some boilerplate code for running…

    2023 · github.com

  22. 22

    a valuable product for community

    3d ago · bolt.new

  23. 23

    A harness for local AI models, with RSI features and RL envs

    14d ago · github.com

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