Prompt-Caching

🔗 Related Deep-Dives High-Throughput Go Microservices Architecture Generative UI with Model Context Protocol (MCP) Engineering Reading Map & System Design Guides Executive Summary: The 2026–2027 Engineering Case Part 2 — The 8 Core Blocks Part 6 — Production PromptOps, Evals & Security MCP Engineering In Production — where L2 tool policies meet real MCP infrastructure Prerequisite: Completion of Part 2 core blocks and knowledge of foundation model prefix caching mechanisms. ...

Answer-first: Advanced Context Engineering moves beyond monolithic system prompts by organizing constraints into modular, glob-scoped .cursor/rules/*.mdc files and standardized AGENTS.md contracts. By binding rules dynamically to active file patterns and capitalizing on prefix prompt caching (achieving a 90% latency and cost reduction), teams provide coding agents with razor-sharp focus while preventing context window pollution. 📖 Bản tiếng Việt (Vietnamese Edition) | ← Series Hub | Next Chapter: Part 3A: Enterprise RAG Architecture → ...

🔗 Related Deep-Dives High-Throughput Go Microservices Architecture Generative UI with Model Context Protocol (MCP) Engineering Reading Map & System Design Guides Executive Summary: The 2026–2027 Engineering Case Part 2 — The 8 Core Blocks Part 3 — Layered Prompt Architecture Part 4 — Context Enrichment with MCP and Hybrid RAG Prerequisite: Knowledge of retrieval-augmented generation architectures, tokenization limits, and vector database semantics. Answer-first: Context Engineering represents the systematic orchestration of dynamic information pipelines into the LLM context window, superseding static prompt string tweaking. Anchored by three core pillars—hybrid vector retrieval, dynamic Model Context Protocol (MCP) tool injection, and token budget compression—it actively counters attention degradation and distractor amplification across expanding long context windows in production. ...