In the Reverse Engineering world, we have a rule: You don't own it until you can take it apart.

The same applies to Artificial Intelligence.

We are currently drowning in API wrappers. Everyone is "building AI apps," but very few people are looking at the wiring underneath. To truly understand modern LLMs, I decided to stop using libraries. I went back to the drawing board to build a custom architecture from scratch.

Meet SARAN (Shallow Auto-Regressive Attention Network).

It’s not designed to beat GPT-4. It’s designed to be transparent. 🔹 I built a strict 15-stage computational graph. 🔹 I manually implemented backpropagation to trace the gradients. 🔹 I scaled it to a 354M parameter model to watch how it learns.

I’ve documented the entire build log—including the architecture decisions and the "why" behind the math—in my new engineering newsletter, Bits & Neurons.

If you want to move beyond the hype and understand the mechanics of AI, read the full breakdown here: https://mytechnotalent.substack.com

#ArtificialIntelligence #MachineLearning #DeepLearning #ReverseEngineering #Engineering #BuildInPublic