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20+ production-ready prompt templates. Chain-of-Thought, Few-Shot, ReAct patterns following 2025 best practices.
Systematically learn core AI technologies and build a complete knowledge system
Master Retrieval-Augmented Generation technology
Build intelligent autonomous AI agent systems
AI system architecture and performance optimization
Advanced techniques for LLM training
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
--- title: 'TensorRT-LLM: How NVIDIA Cut Inference Cost by 60% (Production Guide 2025)' date: '2025-10-15' lastModified: '2025-11-05' excerpt: "NVIDIA TensorRT-LLM reduces LLM inference costs by 60% a...
--- title: 'We Tested 5 RAG Frameworks: Here's Which One Saves the Most Dev Time (2025)' date: '2025-09-18' lastModified: '2025-11-05' excerpt: 'Real-world RAG framework benchmarks: LangChain won for ...
We tested 10 multi-agent AI frameworks and ranked them by use case. CrewAI wins for production, OpenAI Swarm for learning, AutoGen for complex tasks. Benchmarks, code examples, and decision matrix included.
Comprehensive Cursor 2.0 review: New Composer model (200 tokens/s), integrated browser for UI development, Agents Mode, and parallel task management. Is this AI code editor worth it?
Master prompt engineering with this complete 2025 guide. Learn zero-shot, few-shot, and Chain-of-Thought techniques for ChatGPT, Claude, and Gemini. Includes 20+ ready-to-use templates.
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.
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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