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Hand-picked articles showcasing the best of LLM practice
Compare 8 LLM architectures: DeepSeek V3 MLA (37B active/671B total), Llama 4 MoE, Qwen3 dense models. Learn MLA vs GQA, shared experts, QK-norm. Includes code examples and design trade-offs.
Complete guide to Transformer architecture: self-attention mechanisms, encoder-decoder design, and how Transformers power GPT, BERT, and modern LLMs. With code examples and visual diagrams.
Compare 7 LLM sampling methods: Top-P (Nucleus), Temperature, Beam Search, Min-P, Mirostat. Fix repetitive outputs, improve quality. Includes parameter tuning guide for GPT/Claude/Gemini.
Fresh insights and practical techniques
AI agent challenges explained: solve latency issues, fix brittle planning, and avoid reflection loops. Advanced engineering patterns and RL techniques for production-ready agentic AI systems.
NVIDIA TensorRT-LLM switches from C++ to PyTorch achieving 3x faster prototyping + production-grade inference. Learn KV Cache management, expert parallelism, speculative decoding on GB200. MLPerf 5.1 benchmarks included.
Compare 4 vector databases for RAG: Milvus (billion vectors, self-hosted), Pinecone (managed, millisecond latency), LanceDB (50M vectors, edge), Chroma (millions, LangChain). Performance benchmarks, cost analysis, production deployment guide.
Comprehensive RAG chunking guide: compare 9 strategies (Fixed-size, Recursive, Semantic, etc.) with Python code examples. Optimize chunk size and overlap for better retrieval. Includes LangChain implementations.
Complete LangChain ecosystem comparison: LangChain for building chains, LangGraph for complex agents, LangSmith for monitoring. Decision matrix, code examples, and use cases for each tool.
Learn how to add special tokens to LLMs during fine-tuning without causing catastrophic forgetting. Our guide covers smart initialization and PEFT/LoRA.
Practical wisdom from the intersection of research and production
Every technique shared comes from real production systems handling millions of requests. No theoretical fluff, just what works.
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