niteagent@blog:~$cat /etc/motd
>NiteAgent — production patterns for AI agent engineering
>MCP servers · multi-agent orchestration · agent evaluation · LLM ops
>Real code, deployable templates, production-tested patterns
$ ./featured.sh ── latest publication ───── ───── ───── ───── ───── ─────
📄~/posts/2026-07-15-agentic-rag-production-guide/featured
$ ls -la /posts/ ── by category ───── ───── ───── ───── ───── ───── ─────
❯agent-engineering(8)
- >TypeScript Multi-Agent Orchestration: Building Task DAGs with open-multi-agent
- >Self-Hosted Multi-Agent Orchestration with Mission Control: Production Patterns
- >Swarms: Enterprise-Grade Multi-Agent Orchestration Framework Deep Dive
- >Astron Agent: iFlyTek's Open-Source Enterprise Multi-Agent Orchestration Platform Goes Apache 2.0
- >open-multi-agent: TypeScript-Native Multi-Agent Orchestration From Goal to Task DAG
- >UI-TARS: Inside ByteDance's 35K★ Multimodal Agent Stack
- >A2A Protocol 2026: A Practical Guide to Google's Agent-to-Agent Standard
- >Agent Architectures 2026: 5 Patterns That Actually Work
❯mcp-protocols(15)
- >Building MCP Servers in Python: A Production Guide with FastMCP (2026)
- >Building a Production MCP Server with FastMCP: A Step-by-Step Build Log
- >MCP Server Testing and Debugging: A Practical Guide to Development, Integration, and Production Validation
- >Building Custom MCP Servers: A Step-by-Step Guide from Zero to Production
- >MCP Server Instructions: Giving LLMs a User Manual for Your Tools
- >MCP Server Observability in Production: Instrumentation, Metrics, and Alerting
- >Testing MCP Servers in Production: Unit Tests, Mocking, and CI/CD Integration
- >Production Tool Calling Architecture: Parallel Execution, Error Recovery, and Tool Selection
- >Building with the 2026 Agent Protocol Stack: MCP, A2A, and the Production Architecture
- >MCP Server Production Deployment: Auth, Rate Limiting, and Monitoring
- >Building a Production MCP Tool Gateway with FastMCP 3.x — A Build Log
- >Build an MCP Server That Cuts Claude Code Context Consumption by 98%
- >MCP in 2026: The Protocol That Standardized AI Agent Tool Integration
- >Build a Custom MCP Server in Python: Step-by-Step Tutorial (2026)
- >WebMCP: Google's New Web Agent Protocol Changes How AI Interacts with Websites
❯production-patterns(3)
❯llm-deep-dives(6)
- >Build a Production Agent Loop with Ollama Tool Calling: Complete Guide
- >Claude Agent SDK vs OpenAI Agents SDK vs Google ADK: The 2026 Vendor SDK Showdown
- >Claude Code Built a Real iPhone App with 1500+ Users — Case Study
- >Building Your First AI Agent with the Claude Agent SDK: A Step-by-Step Tutorial
- >LLM Context in 2026: Long Context vs RAG Decision Guide
- >Context Engineering 2026: 5 Prompt Patterns That Work
❯build-logs(34)
- >Building Reliable Agent Error Handling — Retry, Fallback, and Circuit Breaker Patterns for Production AI Agents
- >Semantic Caching for AI Agents: Reduce LLM Costs by 40–60% with Embedding-Based Response Caching
- >MCP Protocol Integration: Connecting Agent Frameworks to Tools in Production
- >CrewAI: Building Production Multi-Agent Workflows with Roles, Tasks, and Processes
- >Streaming AI Agent Responses in Production: SSE, WebSocket, and Real-Time Output Patterns
- >OpenAI Agents SDK: Building Production Multi-Agent Systems
- >OpenAI Responses API: Building Agents with the Unified AI Interface
- >PydanticAI: Building Type-Safe Agent Workflows with Structured Outputs
- >Managing Rate Limits and Token Budgets in Production AI Agents
- >Containerizing AI Agent Services with Docker: A Production Guide
- >Building an Agent Coordination Layer with Message Queues
- >Building a Prompt Versioning and Management System for Production AI Agents
- >Building Durable AI Agents with Temporal — Crash-Proof Long-Running Workflows
- >Free AI Hosting in 2026 — Where to Deploy Your AI Apps
- >Building a Document Understanding Agent with Vision LLMs and Structured Extraction
- >Agent Memory Systems in Production: Persistent Context Across Sessions
- >Building Agentic Workflows with Human-in-the-Loop: Approval Gates, Conditional Branching, and State Management
- >Building an AI Code Review Agent: Architecture, Patterns, and Production Deployment
- >Building an Agentic RAG Pipeline with Query Planning and Self-Correcting Retrieval
- >Prompt Caching in Production: A Provider-by-Provider Implementation Guide
- >Building a Multi-Provider LLM Router with Intelligent Fallback Chains
- >Cross-Provider Structured Outputs: A Production Guide for OpenAI, Anthropic, and Gemini
- >Building an AI Agent Evaluation Suite with DeepEval — A Practical Guide
- >Building a Production MCP Server with FastMCP 3.0 — Build Log
- >OpenAI Agents SDK in Production: From Prototype to Deployed Multi-Agent System
- >Building a Multi-Agent Software Delivery Pipeline with Codex CLI and OpenAI Agents SDK
- >Prompt Cache Hit Rate Engineering: A Production Guide for AI Agents
- >Structured Outputs Across LLM Providers: A Production Guide to JSON Mode, Tool Calling, and Constrained Decoding
- >Build an MCP PDF Extractor Server for Hermes Agent
- >Build a Self-Hosted AI Gateway with LiteLLM Proxy
- >Building a Production Research Agent with LangGraph and OpenTelemetry
- >Building a Custom MCP Server for Your AI Agent
- >How I Built an Agent Eval Harness: Lessons from 500 Runs
- >MCP in Production: 5 Integration Patterns for AI Agents in 2026
❯tool-reviews(4)