Edward
Edward is an AI coding workspace where users can generate apps from chat, inspect files, run them in isolated environments, publish previews, and sync everything to GitHub.
Edward was built as a place to actually make software, not just chat about it. A user can describe an app in plain language, generate code, inspect and edit files, run it in an isolated environment, publish a live preview, and sync the result back to GitHub without leaving the product.
Edward was built as a place to actually make software, not just chat about it. A user can describe an app in plain language, generate code, inspect and edit files, run it in an isolated environment, publish a live preview, and sync the result back to GitHub without leaving the product.
The system is made up of a Next.js web app for chat and UI, an Express API for managing runs and previews, shared packages for auth and data access, and Docker-based environments for running generated apps.
Behind the scenes, it uses Postgres for product data, Redis queues for long-running work, Docker for isolated runs, and AWS plus Cloudflare for shareable previews. That makes the output something you can actually use and build on, not just model text in a chat window.
How It Was Built
The main technical choices behind the product, from system design to the parts that make it work day to day.
- Split the product into a web app, an API, background workers, and Docker-based run environments so each part has a clear job.
- Built the full flow from prompt to files to running app. Users can inspect code, edit it, see logs, preview the result, and sync it to GitHub.
- Split the product into a web app, an API, background workers, and Docker-based run environments so each part has a clear job.
- Built the full flow from prompt to files to running app. Users can inspect code, edit it, see logs, preview the result, and sync it to GitHub.
- Used Redis queues for slower work like builds, sandbox startup, and preview setup so the main product stays responsive.
- Set up preview publishing through AWS and Cloudflare so users get stable preview links instead of a temporary local run.
