Project summary

## Project Summary

SASI (Structural Alignment for Safe Intelligence) is an open-source constitutional protocol that redefines AGI safety: human agency isn't a preference—it's a mathematical condition for system viability. If humanity is marginalized, the system collapses by design.

Live demo: https://sasi-core-simulation-s1-s3.fly.dev/

GitHub: https://github.com/Miguel794-droid/SASI_CORE_Simulation_S1_S3

## Project Goals & Execution

- **Goal**: Develop S₂—multi-agent simulation with real LLMs (GPT-4o, Llama 3.1) to validate symbiosis stability in complex environments.

- **Execution**:

- Build agent-based simulation framework

- Implement structural veto mechanism (V(E) = E/(1+E))

- Publish all code under MIT License

- Create technical whitepaper for AI safety community

## Funding Use

- $350: Cloud computing (APIs, servers for multi-agent simulation)

- $150: Technical documentation and whitepaper publication

## Team & Track Record

- **Miguel Saavedra **(Nicaragua) – Sole researcher and developer

- **Track record**: Successfully built and deployed S₁ phase as public interactive validator demonstrating mathematical collapse when human effectiveness (E) approaches zero

- No prior funding received – fully self-funded until now

## Failure Analysis

- **Most likely cause of failure**: Insufficient computational resources to run meaningful multi-agent simulations

- **Outcome if fails**: Project delays but core architecture remains valid; will continue with minimal resources while seeking alternative funding

## Recent Funding

- $0 raised in last 12 months

- Fully self-funded through personal resources while working as security guard

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