See the Whole AI System Before You Run It
Graph Engineering turns a complex idea into a connected visual system. Instead of guessing your way through a long prompt, you lay out the stages, dependencies and checks first — then review the whole thing at a glance.
Windows and macOS apps are coming soon.
Everything a graph is made of
Eight simple primitives are enough to describe most real projects — and to expose the steps that were quietly missing.
Nodes
Each node holds one unit of work with a clear purpose and expected output.
Stages
Group nodes into phases so a long project reads as a sequence, not a blob.
Branches
Split the path when the work legitimately diverges by type, risk or audience.
Dependencies
Make it explicit what has to exist before a later step can start.
Decisions
Encode the choice points that usually stay hidden in someone's head.
Validation steps
Add quality checks where mistakes are cheapest to catch.
Execution paths
See the route the work will actually take, including fallbacks.
Completion conditions
Define what finished means so work stops on purpose, not by exhaustion.
From a vague idea to a reviewable system
Graphs help you organise complex projects, expose missing steps, understand dependencies, and build workflows that are easy to review and reuse.
Illustrative graph structure. Your own graphs are built and edited inside the app.
Organise complex projects
Break a large ambition into stages you can actually reason about, instead of one very long instruction.
Expose missing steps
Gaps become obvious the moment the work is drawn: no validation, no fallback, no definition of done.
Understand dependencies
See which steps are blocked, which can run in parallel, and where a decision changes the path.
Review and reuse
A saved graph is a reusable asset. Duplicate it, adjust a branch, and run the same structure on a new project.
Available now on mobile
Loop Engineering AI is live on the Apple App Store and Google Play. Desktop apps are on the way.
iPhone and iPad
Native iOS app with the full graph, loop and prompt workspace.
Download on the App StoreAndroid phones and tablets
Native Android app with the same local-first project library.
Get it on Google PlayWindows
A desktop canvas for larger graphs is in development.
macOS
A native Mac workspace is in development.
Graph Engineering FAQ
Graph Engineering is the practice of designing an AI system as an explicit graph — nodes that do work, edges that connect them, decisions that branch, validation steps that check quality, and completion conditions that end the work. You design the structure before anything runs.
Related pages
Start building visual AI systems today
Design graphs, engineer loops and keep every project on your device.
Windows and macOS apps are coming soon.