Lucid Train

Lucid Train generates architecture diagrams directly from your codebase, then provides these diagrams as specifications to a coding agent. It runs fully offline using local models on your machine, with no code upload or telemetry required. Available as a desktop app for macOS and Windows, or as a 6 MB Rust CLI binary that works in the terminal.

Lucid Train is a strong fit if you are one of: • indie hackers and solo founders • early-stage startup teams If that does not sound like you, skim the features and site before committing time.

Lucid Train is built around this outcome: For architects: Lucid Train generates architecture diagrams from your codebase offline so coding agents understand your system design instantly. Use the site demo or docs to confirm it matches the bottleneck you are trying to remove.

Lucid Train includes: • Generate architecture diagrams from repository source code • Hand diagrams to coding agent as executable specifications • Run against local Ollama models or custom API keys • Audit dependencies across multiple ecosystems • Export diagrams as editable Excalidraw SVG or PNG files • Support voice input with on-device transcription

CLI is free and open source. Desktop app costs $2.50/month (billed $30/year) with a 7-day free trial. Most freemium tools let you validate the workflow before upgrading — check what the free tier unlocks for your use case.

CLI is free and open source. Desktop app costs $2.50/month (billed $30/year) with a 7-day free trial.

Lucid Train's positioning emphasizes keeping work local or private (for example browser-side processing or limited uploads). Still verify the privacy policy and data handling on the official site for your compliance needs.

Lucid Train uses AI as part of its workflow. Before relying on it for customer-facing or confidential work, confirm what data is sent to models, whether outputs are editable, and how you can review results.

It promises: For architects: Lucid Train generates architecture diagrams from your codebase offline so coding agents understand your system design instantly. A concrete use case founders care about: Developers wanting to visualize existing codebase architecture before AI makes changes. It has 114 community upvotes on Launch Llama, which is a signal of interest — not a guarantee it fits you. Worth trying if that problem is painful for you this week; skip it if you only need a one-off workaround you already have.

Open the official Lucid Train website from this page, run the smallest real task you care about (not a toy demo), and decide in one session whether it removes friction. Check pricing and data/privacy terms before you put production work into it.