Did you catch our first AI development demystification blog? As promised, we are excited to release our very first edition of “Monthly Insights for AI developers”, focusing on useful resources to kickstart your development of AI features in your products. Let's dive in!

To kick things off, we recommend exploring generative AI technologies. The buzz around this area is huge right now, and it’s likely your clients will be asking for it. 

No matter what solution you’re planning to build, especially if it involves language models or generative AI, I highly recommend starting with this wealth of knowledge from Greg Kamradt.

Once you’ve got the basics down, it’s time to roll up your sleeves and dive into some implementation. Do a solid code review and analyze how things are done in existing projects. A standout example is Superagent, which is backed by Y Combinator. You can even fork it and build something on top: Superagent GitHub Repository.

Another one worth checking out is Verba, dubbed "the golden RAGtriever": Verba GitHub Repository

By now, you should be getting familiar with the open-source library Unstructured, which is frequently used in RAG solutions. I suggest exploring the other features that https://unstructured.io/ provides. In addition to the open-source part. 

And don’t forget about the Unstructured Serverless API — it has some great benefits! Check them out and compare with the limited open source part. 

If you are going to build something really big that processes a ton of documents and requires continuous updates of data sources, definitely look into their Enterprise platform. It’s currently in beta, but once it’s production ready, there probably won’t be anything with the same functionality. We are still at the early stage of the generative AI era, so don't miss the bus!