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In this post I compare existing solutions for the backend of AI generated apps and share our journey building , a minimalistic open source backend for AI-assisted coding.
As of today, AI code editors already work very smoothly with frontend generation. Even a non coder is able to create nice UIs and websites with a bit of motivation. However vibe coding the backend side is still a bit laborious.
The bootstrap approach to backend (local tools)
Local AI code editors like , and are made for people already familiar with IDEs, matching high requirements like a strong version control or working with existing/legacy codebases.
If you ask any of those editor to create a backend, chances are that you will get something made with FastAPI or Django in Python, Laravel in PHP, Ruby on rails, NestJS and so on.
All of those frameworks have proven to be exceptional products, robust and highly customizable. They have been used by developers for years support top tier platforms.
However, in the context of AI-assisted programming, they have some drawbacks:
Then you have the online vibe coding tools like , , and so on. Those tools are addressing a large audience and require little knowledge to get started. They are amazing to quickly ship a project from scratch.
What do they have in common regarding the backend ? They all have the "connect to Supabase" button. It actually makes a lot of sense as it is so much simpler to rely on a cloud backend rather than creating a consistent environment for different backend stacks.
is a well-know BaaS (Backend as a Service) based on PostgreSQL and giving built-in features like auth or storage. Nevertheless, even if Supabase is an amazing product on its own, linking your AI-generated frontend to a Supabase backend can be tricky for many reasons:
Even if Supabase is building a strong MCP to connect the service, it will always be 2 connected services at the end of the day.
Manifest: finding the sweet spot
When we first built , as an internal tool, we did not think right away about making it fit in the context of AI coding. However, we strongly focused on simplicity of use and reducing the development time. Those characteristics are now 100x enhanced by AI code tools that we use today which makes a perfect fit for Manifest as a backend for AI editors.
Manifest is a complete backend that fits into 1 simple YAML file, that makes it so easy for LLMs to generate that content, and for humans to validate. Relying on pre-made components like auth or upload modules is also a way of ensuring the developer that there is no breaches in security or privacy.
We also wanted Manifest to be not only open source but also 100% portable, it's just an that you can add to any codebase with a package.json in it. Manifest uses SQLite by default, a file-based DB that works even in browser environments like [Stackblitz][).
Where we go next
Manifest is still on BETA but already used on multiple projects. If you think Manifest could be a good fit for you, give it a try ! You can share some love by and we'll be happy to hear your feedback on our .
As of today, AI code editors already work very smoothly with frontend generation. Even a non coder is able to create nice UIs and websites with a bit of motivation. However vibe coding the backend side is still a bit laborious.
The bootstrap approach to backend (local tools)
Local AI code editors like , and are made for people already familiar with IDEs, matching high requirements like a strong version control or working with existing/legacy codebases.
If you ask any of those editor to create a backend, chances are that you will get something made with FastAPI or Django in Python, Laravel in PHP, Ruby on rails, NestJS and so on.
All of those frameworks have proven to be exceptional products, robust and highly customizable. They have been used by developers for years support top tier platforms.
However, in the context of AI-assisted programming, they have some drawbacks:
- A backend with those frameworks consists necessarily in a huge amount of files which makes it nearly impossible to be humanly validated and cost a lot in computing (tokens)
- Each feature is mostly developed in the spot for you and may contain security flaws for unknown reasons
- The developer must still have solid knowledge with the framework to understand it
Then you have the online vibe coding tools like , , and so on. Those tools are addressing a large audience and require little knowledge to get started. They are amazing to quickly ship a project from scratch.
What do they have in common regarding the backend ? They all have the "connect to Supabase" button. It actually makes a lot of sense as it is so much simpler to rely on a cloud backend rather than creating a consistent environment for different backend stacks.
is a well-know BaaS (Backend as a Service) based on PostgreSQL and giving built-in features like auth or storage. Nevertheless, even if Supabase is an amazing product on its own, linking your AI-generated frontend to a Supabase backend can be tricky for many reasons:
- Having to deal with 2 projects creates a poor DX, making you going back and forth between 2 dashboards and the LLM not always understanding what is on the other side
- Branching, versionning and environment management becomes suddenly way more complex
- You may not be familiar with PostgreSQL
Even if Supabase is building a strong MCP to connect the service, it will always be 2 connected services at the end of the day.
Manifest: finding the sweet spot
When we first built , as an internal tool, we did not think right away about making it fit in the context of AI coding. However, we strongly focused on simplicity of use and reducing the development time. Those characteristics are now 100x enhanced by AI code tools that we use today which makes a perfect fit for Manifest as a backend for AI editors.
Manifest is a complete backend that fits into 1 simple YAML file, that makes it so easy for LLMs to generate that content, and for humans to validate. Relying on pre-made components like auth or upload modules is also a way of ensuring the developer that there is no breaches in security or privacy.
We also wanted Manifest to be not only open source but also 100% portable, it's just an that you can add to any codebase with a package.json in it. Manifest uses SQLite by default, a file-based DB that works even in browser environments like [Stackblitz][).
Where we go next
Manifest is still on BETA but already used on multiple projects. If you think Manifest could be a good fit for you, give it a try ! You can share some love by and we'll be happy to hear your feedback on our .