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 with path-scoped cursor rules structures repository knowledge into targeted hierarchical instructions matching glob patterns, preventing token window exhaustion and instruction shadowing by feeding coding agents only domain-specific constraints, architectural rules, and anti-corruption interfaces relevant to the active source file rather than flooding the prompt buffer with irrelevant monorepo files. Prerequisite: Familiarity with Cursor IDE configuration, glob pattern matching, and directory structure design in monorepos. 1. The Death of the Monolithic Prompt File In early AI coding setups, teams placed a massive 2,000-line .cursorrules file at the root of their repository containing every guideline imaginable: React component standards, Go concurrency patterns, SQL migration rules, and CSS styling guides. ...

🔗 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. ...