Neverbell, an AI agent that analyzes markets and executes trades
Hi HN, we're developing Neverbell, an AI agent that combines market analysis with trade execution. One of our beta testers said to Neverbell: “Protect my downside, but don’t be too conservative.” Volatility increased a few days later, and the agent decreased their exposure. Our tester wasn’t happy. The interesting part for us was that both interpretations were reasonable. The agent gave more weight to “protect my downside.” The user thought that “don't be too conservative” was more important. It changed the way we built Neverbell. Now, if the agent sees any instructions that conflict, it…
What it does
In the maker’s words, at launch
Hi HN, we're developing Neverbell, an AI agent that combines market analysis with trade execution. One of our beta testers said to Neverbell: “Protect my downside, but don’t be too conservative.” Volatility increased a few days later, and the agent decreased their exposure. Our tester wasn’t happy. The interesting part for us was that both interpretations were reasonable. The agent gave more weight to “protect my downside.” The user thought that “don't be too conservative” was more important. It changed the way we built Neverbell. Now, if the agent sees any instructions that conflict, it will ask rather than guess what the user was trying to say. We've seen this several times before; so we made it part of the product. Interested in what others are doing. Once an agent starts taking actions instead of just answering questions, where do you draw the line? Will also answer questions about Neverbell, permissions, or anything else we've learned during the beta period.
Does the same job
all alternatives →- ICI created agent skill based on Peter Lynch's booksJun 2026 · github.com · ▲5
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
- IMI made Quantify AI – alternative to TradingView (2 months work)Oct 2025 · quantify-ai.co · ▲6
How it works (tech stack): -Built entirely with Lovabl.dev (no-code front-end + logic) -ChatGPT / Claude for research and inspiration -Powered by GPT-4 Vision to interpret charts visually -Hosted on Supabase for performance & caching It’s not meant to replace analysts — just to speed up how traders interpret data. I’m a designer exploring AI tools, and this is my first attempt to turn an idea into a functional product. Would love to know what you think.
- AAAn AI agent that trades inside limits you set, starting on paperAug 2026 · quantsignals.xyz · ▲17
- MAMulti-Agent Market Simulator for Studying Emergent Trading Dynamics2025 · aitradingsim.com · ▲7
I built this simulator to study how simple trading agents interacting with an order book can create emergent patterns—volatility, clustering, even chaos—without any external shocks. It’s meant as both a research toy and teaching tool. You can run different strategies, adjust configs, and watch dynamics evolve. Curious to hear feedback from the HN crowd on features/dynamics you’d like to see added.
More ai this month
the category →
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
AI · 17d ago · simedw.com
Astute▲585Automate your B2B brand going viral, with new media creators
AI · 18d ago · company-app.joinastute.com
Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
AI · 27d ago · cactuscompute.com
Launched alongside, July 2026
the whole month →- IR
I might be the only SRE on Earth with his own bowling center. It's a more in-depth gig than you'd think. My family and I bought an abandoned 8-lane bowling center in the rural mid-west. In our small town there weren't many recreation options for families. You've heard of a food desert? This is an R&R desert. It had been abandoned for a good reason. The roof leaks, the electrical system was constantly surging, and my 70-year-old bowling equipment (still) doesn't work perfectly. The system that keeps your score is particularly interesting to me. It's the thing you watch during your game, but…
Life & fun · Jul 2026
- EElevators▲1,680
Life & fun · Jul 2026 · john.fun
- 1W18 Words▲1,160
Life & fun · Jul 2026 · 18words.com
- BA
Over the past few months, our team has been building more and more slidedecks using web frontend technologies with coding harnesses like Claude Code, but a common complaint is to make even small edits we need to edit the code either manually or via the harness. To avoid this loop, I ended up creating Bento, a single HTML file with everything you need in a slide tool including animations and shared editing. There's no install or cloud login, everything works offline. The default deck is around 560 KB and it doesn't need to fetch anything once you got it. Open it in a browser and then you can…
Dev tools · Jul 2026 · bento.page
- GG
A few days ago I found myself trying out GLM 5.2 and was really positively impressed. The capabilities and security I was getting from this LLM are similar to those I've gotten from models like Claude or GPT, and this really surprised me. But then I thought, "I wonder how it would work on a normal computer like mine," and above all, "I wonder if it would work without going into OOM on a computer like mine." So I started working with the help of agents to test this possibility. I started converting the model to int4, understanding MTP usage, and if possible implementing DSA for long context.…
AI · Jul 2026 · github.com
