Fighting Context Drift (github.com)

Trepan, a local-first architectural linter, has been introduced to combat "Architecture Drift," a common issue among AI tools that often lead to hastily constructed code. Unlike traditional AI tools that serve as "yes-men," Trepan is designed to enforce architectural integrity, validating code on the developer's hardware entirely offline—eliminating risks associated with cloud storage and third-party data leaks. It runs on a locally hosted Llama 3.1 model and performs strict intent verification, providing clear ACCEPT or REJECT verdicts for AI-generated suggestions while logging every decision in a detailed audit trail. This tool is significant for the AI/ML community as it empowers developers to maintain robust project outlines and coding standards without reliance on external resources. Trepan enforces guidelines through a structured framework that includes whitelists and blacklists, dynamic task management, and a cryptographic safeguard, ensuring that only authorized changes are applied. By positioning AI as a skeptical partner in development processes, Trepan seeks to preserve the architectural integrity of projects and support secure coding practices, ultimately fostering a more thoughtful approach to AI integration in software development.