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Launch HN: Modelence (YC S25) – App Builder with TypeScript / MongoDB Framework

12•eduardpi•1h ago
Hi all, Aram and Eduard here - co-founders of Modelence (https://modelence.com). After spending years on scaling our previous startup’s platform, we built an open-source full-stack TypeScript + MongoDB framework to stop solving the same auth / database / API / cron job implementations every time we created an app, and we didn’t like the idea of using multiple managed platforms for each of these to run our apps either.

(Here’s our prior Show HN post for reference: https://news.ycombinator.com/item?id=44902227)

At the same time, we were excited by the whole AI app builder boom and realized that the real challenge there is the platform rather than the tool itself. Now we’re making Modelence the first full-stack framework that’s built for coding agents and humans alike:

- TypeScript is already great for AI coding because it provides guardrails and catches many errors at build time, so agents can auto-correct

- MongoDB eliminates the schema management problem for agents, which is where they fail the most often otherwise (+ works great with TS/Node.js)

- Built-in auth, database, cron jobs and else that just works together out of the box means agents only focus on your product logic and don’t fail at trying to set these things up (+ less tokens spent on boilerplate).

You can now try the Modelence app builder (based on Claude Agent SDK) by just typing a prompt on our landing page ( https://modelence.com ) - watch a demo video here: https://youtu.be/BPsYvj_nGuE

Then you can check it out locally and continue working in your own IDE, while still using Modelence Cloud as your backend, with a dev cloud environment, and later deploy and run on Modelence Cloud with built-in observability around every operation running in your app.

We’re also going to add a built-in DevOps agent that lives in the same cloud, knows the framework end-to-end, and will use all this observability data to act on errors, alerts, and incidents - closing the loop, because running in production is much harder than just building.

We launched the app builder as a quick start for developers, to demonstrate the framework and Modelence Cloud without having to manually read docs and follow the steps to set up a new app. Our main focus is still the platform itself, since we believe the real challenge in AI coding is the framework and the platform rather than the builder tool itself.

Comments

Soerensen•56m ago
The TypeScript + MongoDB combination for AI coding is a smart architectural choice. I've found that schema-less databases reduce the class of errors agents struggle with most - the migration/schema drift issues that require understanding of state over time.

Question: How are you handling the built-in auth when users want to extend it? For example, adding OAuth providers that aren't pre-configured, or custom claims/roles logic. Is this something the framework supports as extension points, or would users need to fork/modify core auth code?

The Claude Agent SDK integration is interesting - have you found specific prompting patterns that work better for TypeScript generation vs other languages? Curious if the type system actually helps agents self-correct as expected.

artahian•41m ago
Great questions:

- For extending auth, currently the framework contribution is the main option, but we've intentionally made everything modular so we will be making it extensible with custom external packages as well (or even directly in your app without a package).

- Our system prompt actually doesn't have anything TypeScript specific (only Modelence specific instructions). But the typing system is literally a miracle - the success percentage from a single prompt went from about 30% to 90%+ just by adding the type checks for the agent. It is surprisingly good at self-correcting, to the point that even when it lacks context it ends up going into the framework code itself from node_modules to find the right usage.

koakuma-chan•1m ago
You eliminate the schema management problem by not having a schema at all? Also, what do you mean schema management problem? I have never had an issue with that when using LLMs.

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