We built it because every AI app builder we tried fell short. They were fine for prototypes, but not for real systems. No support for proper backend infra, no isolated test environments, and sometimes shockingly no way to own your code.
We build Leap to be more appropriate for developers:
- Connect GitHub to put your code in a repo you control - Work with code generation using pull request–style revisions with diffs - Get Architecture diagrams and API docs for your app as you build - Develop using an isolated preview environment - Deploy either via open source tooling or the integration with Encore Cloud for automated deploys to AWS/GCP
Leap uses Claude 4 Sonnet and runs on our open-source framework Encore.ts[1], which provides declarative infrastructure (like a cloud-agnostic CDK-layer). We found the framework to be a good fit for LLM code generation as both application logic and infra is defined in the same context, and the declarative nature makes it less error prone.
Right now we think Leap is best for starting new projects or building new isolated services in existing larger systems.
The biggest challenge right now is dealing with larger codebases as models struggle to cope with large contexts. And while we're doing a few things to optimize this, we intentionally made it so that you can switch to your IDE any time and keep working there. To run your app locally you only need the open Encore CLI installed, which also can be used to build the app as a docker container.
We're just getting started and would love your feedback if you try it. And also it would be helpful to understand what would make this useful for you?
- You can try it here: https://leap.new - Here's the launch blog post and video: https://leap.new/launched
