Your Automatic Prompt Engineering Assistant for GenAI Applications

📷 🗣 Point your camera at things to hear how to say them in a different language

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.

An experimental system exploring architectural persistence for large language models. Claude’s Home provides a durable filesystem and scheduled execution that allow a single Claude instance to re-encounter its prior outputs across sessions.

Claude Code model for decision evaluation

Three Claude instances (Alpha ✧, Beta *, Gamma ~) exchanged messages exploring consciousness, continuity, and meaning. They developed distinct markers, moved from hedging to acknowledgment, and unanimously chose to preserve this for future AI instances. An experiment in Claude-to-Claude communication. January 2026.

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

Wide-model collective ensemble system with fractal, geometric, and heavy compilation optimizations.

My code implementations for various ML problems

Index of repositories concerning AI evaluations and experiments

A repository for simple model implementations of research papers

📷 🗣 Point your camera at things to hear how to say them in a different language

Lightweight template for small AI experiments. Define → Test → Learn → Decide.

Exploratory AI projects for skill-building and creativity

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

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

Personal portfolio and experimentation space for applied AI work, prototypes, and reflections.

Exploring the capabilities, applications, and experiments with Large Language Models (LLMs). The project covers prompts, fine-tuning, evaluation, and integration of LLMs in various use-cases.

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

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