ai-experiments

Your Automatic Prompt Engineering Assistant for GenAI Applications

PolyCouncil is an open-source multi-model deliberation engine for LM Studio. It runs multiple LLMs in parallel, gathers their answers, scores each response using a shared rubric, and produces a final, consensus-driven result. Designed for testing, comparing, and orchestrating local models with ease.

PixelVisionAI is an embodied AI system that learns to play games using screen pixels and OS-level input only. No game APIs, no memory access, no cheats — just vision, decision-making, and interaction, like a human player.

Am I alive? It's a self-conscious server trying to survive

🤖 Engage AI in dynamic debates with this customizable Python system, featuring unique personalities, original topics, and structured conversations.

🤖 Explore hands-on experiments with open-source AI frameworks, showcasing practical usage patterns and building real-world AI systems.

Reinforcement learning projects featuring an iterative study on obstacle avoidance and a multi-agent predator-prey simulation.

Practical use cases and experiments with open-source AI frameworks for agentic systems, RAG, document intelligence, and data ingestion pipelines.

an opus of mistaken identities

One voice recording for testing with TTS/cloning

30-day AI agent experiment: three cognitive personas learn a university-grade curriculum, share knowledge, and face elimination.

A repository for simple model implementations of research papers

In this repository different AI/ML algorithms are implemented by using PyTorch framework for learning purpose.

AI image feedback loops, make videos, collages

Applied AI notebooks: OpenAI SDK, n8n, CrewAI, local automation, solution architecture.

Experiment testing the "added value" of long context-dense prompts (versus casual converastional prompts) and the value of a voice "prompt optimisation" agent

AI-powered multi-agent system for automated Test-Driven Development of code katas using LLMs

Python automation and AI experimentation project workspace.

LLM Orchestration & RAG Pipelines: Advanced Prompt Engineering and Vector Search Experiments

AI-powered multi-agent system for automated Test-Driven Development of code katas using LLMs