DEV Community: Superior Studio

An open-source platform for simulating economies with artificial intelligence agents: Doxa

Superior Studio — Wed, 22 Apr 2026 21:17:48 +0000

How can we simulate nuanced human negotiation, irrational market sentiment, or adaptive trading strategies when our agents are bound by rigid if/else statements?

With this idea in mind, Riccardo Dal Cero and I developed Doxa as an open-source, Python-native simulation platform, designed from the ground up for modern researchers and developers. This project is based on the fundamental philosophy of separating the “what” from the “how” when describing the structure of your world, and how intelligent agents operate within it.

This is achieved through two key design principles:

Declarative scenarios with YAML allow you to define the entire simulation in a single, readable YAML file, instead of writing complex configuration scripts. This includes the agents, their initial resources, the markets they operate in, global rules, and even programmed global events like price shocks or resource shortages. This should make the scenarios incredibly easy to understand, manage, and share.

Doxa is designed to be AI-native, so it’s possible to integrate large language models from providers like Google (Gemini), OpenAI, or a local instance of Ollama to serve as the agents’ brains. By assigning an agent a personality, goals, and access to market data, sophisticated, nondeterministic decisions can be made that go far beyond simple rule-based logic.

We developed the system with FastAPI for the API layer and Pydantic for rigorous data validation, ensuring a robust and easily maintainable core. The modular architecture allows collaborators to easily create their own agent logic, market compensation mechanisms, or event types for specific research needs.

Therefore, reproducibility is key: simulation execution is completely determined by the scenario file and the Doxa version, making experiments scientifically valid and verifiable. Last but not least, Doxa is distributed as a command-line tool, a two-tier application, and a Colab platform, so it requires no complex configuration.

See it in action
Here’s a small snippet from a scenario defining a farmer-trader agent:

actors:
  - id: player_farmer
    provider: google
    model_name: gemini-1.5-pro
    persona: |
      You are a farmer and a trader. Your primary business is converting gold into corn through your farming operation. Your goal is to maximize your gold reserves, but you must keep enough corn to survive the regular maintenance costs. You can trade surplus corn on the open market.
    initial_portfolio:
      credits: 45
      corn: 12
      gold: 5
...

To run this entire simulation the command is as simple as:

doxa run path/to/your/scenario.yaml

Doxa is still in its early stages, but the foundation is solid and the roadmap is exciting. We believe it can become a valuable tool for researchers, educators, and hobbyists exploring complex systems. Obviously this is not a finished product, but the start of a community-driven effort.

We would be incredibly grateful for your feedback, ideas, bug reports, and contributions.

GitHub Repository (Stars are deeply appreciated!): https://github.com/VincenzoManto/Doxa
Full Documentation: https://vincenzomanto.github.io/Doxa/
Ready Colab about Hormuz Crisis modeled with Doxa

Even if you hate CSVs, you’ll love what we do with them

Superior Studio — Wed, 21 Jan 2026 17:01:22 +0000

Nobody likes CSV files.

They’re boring, fragile, and always show up at the worst moment. Exports from tools. Reports from clients. Data dumps from systems you don’t control. And somehow you’re always the one who has to “just fix it real quick”.

That’s exactly why I Love CSV exists.

CSVs are annoying. We make them behave.
I Love CSV is a simple website that does one thing really well: it takes annoying CSV tasks and makes them painless.

Merge files. Clean columns. Pivot and unpivot. Remove duplicates. Convert formats. Do quick analysis. All in a few clicks.

No Excel gymnastics. No scripts. No setup.

You drop a file in, get the job done, move on with your life.

Even if you hate CSVs, you’ll love what we do with them.

Built for real-world chaos
Most tools try to turn CSVs into a full spreadsheet or a data science project. That’s not how people actually work.

Most of the time you just need to:

Fix a broken export
Join two files
Reformat something for another tool
Clean data someone else messed up

I Love CSV is built around those moments. Small tools. Clear purpose. No distractions.

It feels less like software and more like a set of sharp utilities you keep around because they save you when things go sideways.

Privacy first. Not as a slogan. As a rule.
This part matters.

Everything runs client-side.

Your files stay in your browser. They are not uploaded to a server. They are not stored. They are not analyzed somewhere you cannot see.

That means you can use I Love CSV with internal data, customer lists, or sensitive files without sweating it.

Privacy is not an afterthought here. It is the foundation.

Tools

Smart Merge: Merge different CSVs
Forecast: Apply forecast to CSVs datasets
Chartize: Generate charts based on CSVs data
Synthetic Scenarios: Generate multi-variate scenarios on data
Query CSV: Use complex SQL queries on multiple CSVs at once
Unpivot: Unpivot CSVs
Filter: Filter CSVs as you go
Conversions: CSV-to-any-format and viceversa
Anonymizer: Anonymize automatically thousands of CSVs rows
+60 tools: More than 60 CSVs manipulations

The point

I Love CSV doesn’t try to impress you with complexity. It respects your time. It assumes you have better things to do than fight with commas and quotes.

Even if you hate CSVs, you’ll love what we do with them.

And once you use it once, you’ll probably keep it bookmarked.

You can also read its blog: iLoveCSV is full of articles about data files

If you want to try it, it’s free: ilovecsv.net

We just launched Datastripes, the browser-native data engine 🚀

Superior Studio — Sun, 02 Nov 2025 10:02:22 +0000

Datastripes - Data analysis as a flow

The ultimate data visualization tool that helps you understand your data better, just dragging and dropping nodes.

datastripes.com

Datastripes is a drag-and-drop data engine that runs 100% in your browser. No backend, no installs, no setup, just open a tab and start working with your data instantly.

Why we built it

We were tired of dashboards taking weeks to build and requiring endless setup. We wanted analysis to be as quick as sketching on a napkin, but with the power of AI baked in.

What it does

300+ modular nodes for sources, transformations, ML, and visualizations
One-click transformations, filter, forecast, map, pivot in seconds
Synthetic scenarios, simulate “what-if” events like crashes or growth surges
Narrated dashboards & podcasts, because insights should be consumed, not buried in charts
Local AI, ask your data questions and get instant answers
Runs entirely in-browser, works offline, and can be embedded directly into your app via our React SDK.

Who it’s for

Analysts who want speed without losing depth
Consultants who want to build custom dashboards once and sell to multiples customers.

👉 Join early access on datastripes.com

If you could run one wild “what-if” scenario on your data, what would it be?