Airbyte

Airbyte AI

Airbyte AI

Airbyte AI

Airbyte AI

Airbyte AI

Airbyte AI

Airbyte AI

Airbyte AI

Airbyte AI

Airbyte AI

We build AI agents with Claude Code. Just open-sourced the framework we use.

Hey everyone, Daniel here, cofounder of GrowthX. We build AI agents with Claude Code for clients like Lovable, Webflow, Airbyte. We just open-sourced our AI framework - designed for coding agents from day one. We kept hitting the same problems. AI development has a lot of things to figure out that are unique to it - how do you iterate on a codebase packed with prompts? How do you orchestrate API calls that fail in unpredictable ways? How do you track what things actually cost? How do you test code that's non-deterministic? On top of that, every piece of the tooling ecosystem is a different SaaS product that Claude Code couldn't access. We focused on solving three things: Make it easy for coding agents to work with your AI codebase. Filesystem-first - everything your agent needs is files it can read, organized in self-contained folders. TypeScript because it's compiled and Zod gives agents validation and documentation together. We picked Claude Code and built a deep integration through the plugin ecosystem and our CLI. In practice we can one-shot complex workflows and keep iterating fast. Self-contained. One package instead of a dozen SaaS subscriptions - prompts, evals, tracing, cost tracking, credentials. Your data stays on your infrastructure. Fast learning curve. We have engineers at different levels and a lot of AI dev patterns are still being figured out. We baked in conventions so people don't have to figure things out on their own for every project. The more advanced things - evals, LLM-as-a-judge - are abstracted until you actually need them. We've been building this way for over a year. Some of the agents we've deployed for clients: one that creates website templates for Lovable from screenshots and ideas, one that generates connector docs for Airbyte every time a new connector is published, one that researches CVEs and writes detailed reports. The entire framework is structured so Claude has full local context. Every workflow keeps its files together, conventions are baked in, and a native plugin gives Claude deep knowledge of the patterns. You describe what you want in plain English, Claude builds production-grade workflows and agents with all the best practices already in place. No context-switching, no scattered docs, just ship. After finally getting the extraction to a shippable state, we wanted to share it. Would love feedback. https://output.ai https://github.com/growthxai/output submitted by /u/danielvlopes [link] [comments]