A clear, practical guide to Mixture-of-Experts (MoE) architecture: routing, experts, training stability, distributed systems, and when to use it.
A step-by-step guide to preparing high-quality datasets for LLM fine-tuning, from sourcing and cleaning to formats, safety, splits, and evaluation.
Design and ship a production-grade AI image recognition API for mobile apps: architecture, models, privacy, performance, and code snippets for iOS/Android.
A practical tutorial on reasoning models and chain-of-thought: safe prompting, self-consistency, tree-of-thought, tooling, and evaluation patterns.
Build a production-ready LangGraph multi-agent workflow with a supervisor, tools, checkpointing, and streaming—step-by-step with tested Python code.
A practical, end-to-end guide to reducing AI hallucinations with data, training, retrieval, decoding, and verification techniques.
