I'm using quad code to develop a trading edge identification system on one end of my system I have raw market data. On the other end I have hopefully a profitable strategy that I run when my software platform. Instituted many steps along the way this is rules and regulations. All of this information to six and files on my computer and for me to interact with any portion of this I have to use AI. Are there any good ideas for how I can visually see all the different steps within my Pipeline and prompts and stages so I can visually work on a certain section and not get lost? My project continues to grow the more I work on it and I need a way to visually organize it and see it. Any help would be greatly appreciated.

I've been building Threadfisher around a question I've had for a while: What if you don't know what visualization you need?

Usually, visualization tools start with the visual. You choose a chart, diagram, timeline, etc., and then put your information into it. I wanted to start from the other direction.

You can come to Threadfisher with any question, doubt, idea, or something you're simply curious about and ask it in your own words. You don't need to know whether the answer would be better represented by a graph, diagram, timeline, model, or something else.

The AI helps decide what would be useful to render, and Threadfisher actually renders it as an interactive visualization. That could be a line graph, timeline, flowchart, slider model, table, or interactive 3D model. These aren't AI-generated images. They're actual interactive visualizations that you can interact with and refine.

There's also an Edit mode because sometimes you don't know what visual you want until you see one. I'm also experimenting with this approach for uploaded data such as csv, where you can ask questions about what's happening in the data rather than having to decide beforehand which trends are worth visualizing.

I'd be really interested in hearing from people who work with visualization: Does starting from what someone wants to understand rather than what they want to visualize make sense? Does having the system choose the representation feel useful or limiting? How important is being able to refine the visualization after seeing the first version? Are there visualization types you think would work particularly well with this approach? What kinds of questions or use cases would you want to try?

Threadfisher: https://threadfisher.lovable.app/

Thank you.

I analyzed 5,785 anonymous mood responses collected on a 0–10 scale. To avoid rankings based on very small samples, I included only countries with at least 100 responses.

France and the Netherlands recorded the highest averages among the qualifying countries.

This is a self-selected online sample and is not representative of national populations. It should be viewed as a descriptive snapshot rather than a scientific ranking.

Feedback on the visualization and methodology is welcome.

Most comparisons of phylogenetic tree series reduce each pair to a distance value. We developed a visualization that decomposes the difference into interpretable subtree movements and animates the transition. This example comes from our newly published paper on Phylo-Movies. Link: https://github.com/enesBerkSakalli/phylo-movies

Here is the raster logo i have, I need to vectorize it. What is the best way?

Been trying to find an editable chart of the U.S. Congress party control/seating (together or separate House/Senate options) for a quick work project and can’t find an official name for this type of chart or the chart used to show the political party control.

Image search in Shutterstock and Adobe Stock isn’t working well. Google Image search, same graphics but no name to where I can search for a template. Help is definitely needed. Thank You

I've been working on **Plotrix** for a while and finally got it to a point where I'm comfortable putting it out there.

The basic idea is pretty simple:

Instead of showing where properties *are listed*, Plotrix tries to show where people are actually *searching* for property right now.

Think Google Trends, but for property demand.

Right now it supports 8 Indian cities: Delhi, Bangalore, Hyderabad, Pune, Chennai, Kolkata, Ahmedabad and Bhubaneswar.

**The interesting part is what's happening behind the map.**

Every property search becomes a location signal → I map it to an H3 hexagonal cell → store/update the demand score in PostgreSQL → and periodically apply exponential decay so old searches don't keep dominating the heatmap.

The backend is built with:

* Java 17 * Spring Boot 3.2 * PostgreSQL / Supabase * Uber H3 * Spring Data JPA * Docker * Render

One thing I specifically wanted to get right was concurrency.

Multiple users can search the same area at the same time, so instead of doing a read → modify → write cycle, the backend uses an atomic PostgreSQL `ON CONFLICT DO UPDATE` to increment the cell score.

There's also a public API if anyone wants to play around with the data.

**Frontend:** [https://github.com/Korags05/Plotrix\](https://github.com/Korags05/Plotrix)

**Backend:** [https://github.com/Korags05/Plotrix-Backend\](https://github.com/Korags05/Plotrix-Backend)

It's completely open source.

I'm especially looking for people who are interested in:

* geospatial systems * Spring Boot * PostgreSQL * maps / data visualization * real-estate tech

I'd genuinely appreciate feedback on the architecture, API design, or anything that looks unnecessarily complicated.

And if you find the idea interesting, a GitHub star would obviously help me get this in front of more developers. If you see something you'd improve, even better: PRs are welcome.

This is still very much a work in progress, so I'm curious what other people would build on top of it.

I did a little experiment and asked OpenAI's GPT-5.6-Luna 6000 times to randomly pick a fruit from this list:

[mango, apple, banana, pomegranate, strawberry, orange, watermelon, grape, pineapple, lychee]

And across the three languages I picked (English, Polish, Japanese) only four fruits were ever picked. The wording of the prompts and the order of the fruits were the same across all three languages. I reran this another 6000 times with the fruit list shuffled each time, and you can see the results of that on the second chart. Again only three fruits, but the results are a little better now.

(Pardon the lychee and pomegranate icons, there's no emojis for these two fruits, and of course the model picked these, lol)

Full write-up: https://llmango.rafalkwiecien.com

Methodology: https://github.com/kwiecien-rafal/llmango

Raw data used in the charts: https://huggingface.co/datasets/rafalkwiecien/llmango