Daily Dose of Data Science | Avi Chawla | Substack07 phút
The AI Engineering Master Stack for 2026!
A comprehensive overview of the AI engineering stack for 2026, organized into ten layers: foundations, model behavior, prompt engineering, retrieval, agents, context engineering, fine-tuning, inference optimization, evaluation, and LLMOps/safety. A significant portion dives into context engineering specifically, arguing it accounts for 75% of AI app output quality. The six components covered are prompting techniques, query augmentation, long-term memory, short-term memory, knowledge base retrieval, and tools/agents. Practical open-source tools like Zep Graphiti and Airweave are mentioned for memory and retrieval respectively, along with MCP as a standard protocol for tool integration.