Long-form articles on AI Engineering — RAG systems, LLM fine-tuning, autonomous agents, and production ML. Unfiltered notes from building real systems.
A deep-dive into architecting Retrieval-Augmented Generation systems that actually hold up in production — covering chunking strategies, embedding models, vector stores, and latency tradeoffs.
How to fine-tune large language models on consumer hardware and cloud spot instances using QLoRA, PEFT, and efficient training techniques that won't bankrupt your project.
A practical guide to building reliable AI agents — covering the ReAct pattern, tool design, memory management, failure modes, and production monitoring strategies.