13 docs tagged with "ai-agents"

A comprehensive guide to AI agent architectures — covering the ReAct loop, Andrew Ng's four agentic patterns, memory systems, multi-agent coordination, framework comparisons, and production engineering deep dives.

A complete guide to AI agent capabilities — Tool Use (Function Calling), Model Context Protocol (MCP), Memory systems, RAG, and how to write production-grade agent skills from beginner to senior.

Senior-level interview questions and comprehensive answers on AI Agents, Agent Architectures, Context Engineering, Tool Security, MCP, Sandboxing, and Production Engineering.

Introduction to AI Agents, the core agentic formula, the evolution of LLMs, and why autonomous agents are transforming software development in the vibe coding era.

A deep-dive into Context Engineering, Context Compaction, Context Rot, Model Routing, Thinking Budget, AGENTS.md/CLAUDE.md configuration, and advanced Vibe Coding discipline for 2026.

Master Loop Engineering — explore the 4+1 architectural layers of AI loops (Execution, Task/Ralph, Product, System, and Oversight), context rot mitigation, and the evolution of software abstraction from CRUD to Loops.

A complete architectural guide to the Model Context Protocol (MCP) vs traditional APIs, and the 3 distinct layers of modern AI systems — Generative AI, Agentic AI, and Autonomous AI Agents.

Master Prompt Caching and KV-Cache reuse for AI Agents — understand input prefix caching, transformer attention mechanics, golden rules to prevent cache invalidation, and enterprise Spring AI & LangChain4j patterns.

Master the art and science of Prompt Engineering — system prompt design, few-shot learning, Chain-of-Thought reasoning, structured output techniques, and developer workflow prompt templates.

Complete architectural deep-dive into Retrieval-Augmented Generation (RAG) — from offline document ingestion and vector databases to Advanced Reranking and Agentic RAG workflows.

A complete guide to agent harness engineering — sandboxing, Human-in-the-Loop patterns, security threat mitigation, cost control, evaluation frameworks, and production reliability for AI agents.

A practical comparison of AI coding tools (Cursor, Windsurf, Copilot, Devin, Replit Agent) and frontier LLM models (Claude 3.5/3.7, GPT-4o/o3, Gemini 2.0, Llama 3) for modern software development.

Actionable guidelines, workflow frameworks, best practices, and anti-patterns for software development in the era of AI agentic orchestration.