DEV Community: Esteban Palman

🌱 I Built an Open‑Source Adaptive Learning Framework (ALF) — Modular, Bilingual, and JSON‑Driven

Esteban Palman — Tue, 23 Dec 2025 22:46:43 +0000

Hey everyone,

Over the past weeks I’ve been building something that started as a small experiment and slowly grew into a fully modular, bilingual, open‑source Adaptive Learning Framework (ALF) for STEM education.
It’s now at a point where it feels real, stable, and ready for others to explore — so I’m sharing it with the community.

🚀 What is ALF?
ALF is a lightweight, transparent, and extensible framework that models a simple but powerful adaptive learning loop:

Diagnosis → Drill → Integration

It detects misconceptions, generates targeted practice, and verifies mastery — all driven by clean JSON modules that anyone can write.

No black boxes.
No hidden heuristics.
Just explicit logic, modular design, and a focus on clarity.

🧠 How It Works

JSON Problem Bank Each topic is defined in a standalone JSON file:

question

correct answer

common error patterns

drill prompts

integration test

This makes ALF incredibly easy to extend — educators can add new topics without touching the engine.

Adaptive Learner (State Machine) A simple, readable Python class that moves through:

Phase 1: Diagnose

Phase 2: Drill

Phase 3: Integration

It stores history, last error, and current phase.

Engine Layer A thin orchestration layer that:

initializes learners

routes answers

returns structured results to the UI

Streamlit UI (Bilingual) The interface supports English and Dutch, selectable via sidebar. The UI is intentionally minimal — the logic lives in the engine.

🌍 Why I Built It
I’ve worked in education, tech, and the military.
One thing I’ve learned: people in power don’t always want to do the work to understand systems — but they do respond to clarity, transparency, and evolution.

So I documented the entire growth of ALF with photos and structure diagrams.
Not because it’s flashy, but because it shows the system is real, intentional, and built with care.

📸 Evolution of the Framework
I included a /FotoDocs folder with images showing:

early prototypes

first working adaptive loop

the modular engine

the bilingual UI

the JSON problem bank

It’s a visual timeline of how the system matured.

🔧 Tech Stack
Python

Streamlit

JSON

Modular engine + learner architecture

GPLv3 open‑source license

🧪 Try It Out
If you want to explore or contribute:

Add new topics

Improve the engine

Extend the UI

Add new languages

Experiment with adaptive learning ideas

Everything is modular and easy to modify.

❤️ Why Share This?
Because adaptive learning shouldn’t be locked behind corporate walls.
It should be open, transparent, and accessible — something educators, developers, and researchers can build on together.

If this sparks ideas, criticism, curiosity, or collaboration, I’d love to hear it.

I built an open research framework for studying alignment, entropy, and stability in multi‑agent systems

Esteban Palman — Tue, 23 Dec 2025 15:20:07 +0000

Hey everyone,

Over the past weeks I’ve been building an open‑source research framework that models alignment, entropy evolution, and stability in multi‑agent systems. I structured it as a fully reproducible research lab, with simulations, theory, documentation, and visual outputs all integrated.

The framework includes:

Two core experiments: voluntary alignment vs forced uniformity

Entropy tracking, PCA visualizations, and CLI output

A complete theoretical foundation (definitions → lemmas → theorem → full paper)

A hybrid license (GPLv3 for code, CC‑BY 4.0 / CC0 for docs) to keep it open while preventing black‑box enclosure

Clear documentation, diagrams, and reproducible run folders

GitHub repo:

I’m sharing this to get feedback, criticism, ideas for extensions, or potential collaborations.
If anyone is interested in expanding the experiments, formalizing the theory further, or applying the framework to other domains, I’d love to hear your thoughts.

Thanks for taking a look.

Built a 32D Emotional State Tracking system for transparent ethical AI - Now open source (GPLv3)

Esteban Palman — Sun, 21 Dec 2025 19:43:17 +0000

What I Built

Project North Star - An ethical AI framework with 32-dimensional emotional state tracking and transparent internal processing.

Live demo in GitHub Codespaces: [https://github.com/palman22-hue/Project-North-Star]

Why This Matters

Current AI systems are black boxes. This framework makes the AI's internal emotional state visible in real-time, allowing users to see:

Current coherence level (0-1)
Active emotions across 32 dimensions
Transparent decision-making process

The Journey (Today)

Started with: ModuleNotFoundError chaos
Ended with: Fully deployed GitHub repo with working UI

Stack:

Python / FastAPI
Mistral AI
32D state modeling
Real-time visualization
GPLv3 licensed

Try It

Clone it, fork it, improve it. Looking for feedback and potential collaborators who care about ethical AI.

Repo: [https://github.com/palman22-hue/Project-North-Star]

Built this because AI needs to be transparent, honest, and accountable. Hope this helps others working on similar problems.