Sostieni OverPayingForAI - Coding Safety Lab

The AI Coding Safety Lab explores practical approaches to safer AI-assisted software engineering.

The focus is not replacing engineers.

The focus is improving visibility, validation and orchestration around AI-generated code and autonomous development workflows.

Core principles:

• Use domain knowledge first.

• Use evidence next.

• Use expensive AI only where it adds value.

• Keep humans in control.

• Make reasoning and judgement visible.

This lab experiments with:

• autonomous repository validation

• multi-agent orchestration

• benchmark-driven evaluation

• engineering guardrails

• practical AI-assisted development workflows

The goal is practical engineering research — not hype-driven demos.

Your support helps fund:

• OpenRouter model usage

• Replit runtime infrastructure

• repository validation experiments

• autonomous orchestration testing

• benchmark development

• AI safety evaluation workflows

• future Azure deployment environments

Current infrastructure:

✔ OpenRouter

✔ Replit runtime

✔ GitHub automation

In progress:

⬜ autonomous orchestration pipelines

⬜ benchmark datasets

⬜ Azure deployment testing

The focus is practical, transparent experimentation around real-world AI engineering workflows.

AI does not replace judgement.

AI makes judgement visible.

This initiative is independently funded.

Support helps accelerate practical experimentation around AI coding safety, orchestration reliability and autonomous software validation.