Reinforcement Learning Course
Markov Decision Processes and Value Functions
RL Part 2: Markov decision processes, returns, policies, and value functions.
Archive
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Reinforcement Learning Course
Foundations of Reinforcement Learning
RL Part 1: Agents, environments, rewards, and why RL is different from supervised learning.
Classical ML and Deep Learning
Diffusion LLMs from the Ground Up: Training, Inference, and Practical Engineering
Diffusion LLMs Part 2: How dLLMs scale to 100B parameters, the inference stack that makes them fast, hands-on code, and when to actually use them.
Claude
10 Must-use Slash Commands in Claude Code
...explained with exact prompts and usage!
Agents
Build Agents That Never Forget
A first-principles walk through agent memory (open-source).
Classical ML and Deep Learning
Diffusion LLMs from the Ground Up: Theory, Math, and Why They Work
Diffusion LLMs Part 1: Understanding how diffusion language models work from first principles, the math behind masked diffusion, and why they represent a fundamentally different approach to text generation.
Agents
Advisor Strategy in Agents
Reduce token costs and improve performance...and how to use it with Claude!
Claude
The Anatomy of an Agent Harness
A deep dive into what Anthropic, OpenAI, Perplexity and LangChain are actually building.
