How can we create a (mostly) safe environment for running LLM-based code review? Amidst the hype around AI, security concerns may easily be forgotten. The aim of this POC project was to build a secure context in which LLMs can be used for code reviews. The goal was to be able to review untrusted but proprietary code. The main concerns were: Prompt injection and data or code exfiltration.
The result was a pull request review orchestrator with a small Express/SQLite control UI. For each review it creates an isolated Docker setup with separate containers for code review, infrastructure access via MCP and limited web access via proxy.
Full-stack web application for digital workshop facilitation and business strategy development. Features real-time collaborative whiteboard with canvases for SWOT analysis, value proposition design, design thinking workshops, and business model development. Includes guided workshop templates, real-time cursor tracking, user presence indicators, and integrated tools for brainstorming, clustering, and presentation. Built with React frontend and NestJS backend with WebSocket support for realtime team collaboration.
I build this project as part of a 4 people startup team, in which I handled most of the tech work and coordinated one remote developer. The other team members focused on business development, marketing and customer acquisition. Unfortunately we could not acquire enough customers to make the project sustainable in the long run, so we had to discontinue it in 2022.