Stop Rewriting the Same AI Code: A Cookbook for Developers Who'd Rather Build
You've figured out how to call an LLM from Python. Now you want to build something that actually holds up—RAG, agents, a pipeline that doesn't fall apart the moment it touches real data. The problem isn't ideas, it's that you keep rebuilding the same scaffolding from scratch. The AI Cookbook is a collection of examples and tutorials designed to give you copy/paste code snippets you can drop straight into your own projects.
What It Does
The AI Cookbook is a repository of examples and tutorials for building AI systems. That's the whole pitch, and it's a good one: instead of reading abstract documentation and translating it into working code, you get snippets you can paste into your project and adapt.
The repo is maintained by Dave Ebbelaar, an AI engineer and founder of Datalumina, an AI development company. The examples come out of that practical context—the same patterns his team uses with agency clients—rather than being written in a vacuum. Alongside the cookbook, he runs a YouTube channel with tutorials on building AI systems that work in the real world, so the repository and the video content feed into each other.
The README doesn't list a specific tech stack, framework lineup, or directory structure, so I won't pretend otherwise. What it does make clear is the intent: practical, integrable code over theory.
Why It's Cool
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Copy/paste is an underrated design goal. A lot of AI tutorials teach you a concept and leave you to figure out the implementation. This one assumes you already understand the concept and just want working code. That's a meaningful shift in who it's for—it respects your time.
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It comes from agency work. Dave runs an AI development company, and the README explicitly frames the material around building systems that "actually work in the real world." That phrasing matters. There's a wide gap between a demo that impresses on a laptop and something you'd hand to a client. Code that's been through client work tends to account for the messy parts.
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The surrounding resources are tiered sensibly. The README points to a free five-hour course for people new to AI and Python, a paid program for developers who want to build and deploy end-to-end GenAI solutions, and help for experienced folks going independent. That's a clear-eyed view of where people actually are in their careers, not a one-size-fits-all funnel.
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It's honest about being a cookbook. There's no claim of being a framework or a library you install. It's examples. That's a lower-commitment thing to try—you can browse, grab what's useful, and leave the rest.
How to Try It
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Head to the repository: github.com/daveebbelaar/ai-cookbook
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Browse the examples and tutorials. Since the README describes the content as copy/paste snippets, the intended workflow is straightforward: find the pattern closest to what you're building, copy it, and adapt it to your project.
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If you're completely new to AI and just getting started with Python, the README points to a free five-hour course that covers the foundations. Worth doing before you start pasting snippets you don't yet understand.
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If you're comfortable with the basics and want to go further, there's a program on building and deploying end-to-end GenAI solutions using the same approach used for agency clients.
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If you're a skilled developer or data professional looking to go independent, there's separate help for landing your first client.
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For more tutorials in video form, check out the YouTube channel.
The README doesn't include install commands or usage examples, so the repository itself is where you'll find the actual code. Start there.
Final Thoughts
This is best for developers who already know the fundamentals and are tired of writing the same boilerplate for every AI project. If you're brand new, the free course is the better entry point—the cookbook assumes you can read code and know what you're looking at. If you're experienced, the value is in skipping the setup and getting to the interesting parts. It's a practical resource from someone who ships AI systems for a living, and the copy/paste framing tells you exactly what kind of relationship it wants with you: low ceremony, high utility.
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