FIG_000 · curriculum v1.0 · 2026 open source · MIT

# AI Engineering
from Scratch

416 lessons. 20 phases. Every algorithm built from raw math before a single framework gets imported.

Maintained by Rohit Ghumare and contributors. Run on your own machine.

FIG_006 · the stack memory · reasoning · kb
How this works

Most AI material teaches in scattered pieces. A paper here, a fine-tuning post there, a flashy agent demo somewhere else. The pieces rarely line up. You ship a chatbot but can't explain its loss curve. You hook a function to an agent but can't say what attention does inside the model that's calling it.

This curriculum is the spine. 20 phases, 416 lessons, four languages: Python, TypeScript, Rust, Julia. Linear algebra at one end, autonomous swarms at the other. Every algorithm gets built from raw math first. Backprop. Tokenizer. Attention. Agent loop. By the time PyTorch shows up, you already know what it's doing under the hood.

Each lesson runs the same loop: read the problem, derive the math, write the code, run the test, keep the artifact. No five-minute videos, no copy-paste deploys, no hand-holding. Free, open source, and built to run on your own laptop.

Current Progress
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From the same author

## Memory + reasoning + knowledge protocol

Three open-source repositories that compose into a full agent stack. The curriculum teaches the primitives; these tools ship them in production.

FIG_006 · the agent stack memory · reasoning · knowledge
Three repositories, one stack: agentmemory writes durable state, agentbrain steers the loop from evidence, akbp answers knowledge queries between sessions and across agents.
agentmemory

Persistent memory for AI coding agents. The state surface from Phase 14, productionized.

View on GitHub →
agentbrain

Evidence-first operating system for agents. The reasoning + verification surfaces, wired end-to-end.

View on GitHub →
akbp

Agent Knowledge Base Protocol. The handoff + knowledge layer between sessions and across agents.

View on GitHub →
Colophon

The entire curriculum is on GitHub. Clone it, fork it, learn at your own pace. No paywall, no signup. Every lesson has runnable code in Python, TypeScript, Rust, or Julia, depending on what fits the concept best.

`git clone https://github.com/rohitg00/ai-engineering-from-scratch.git`