#three-layer architecture
199 related articles
·2 min
Getting Started with LangGraph: Graph Orchestration and State Machines for AI Agents
A comprehensive guide to LangGraph's core concepts: Graph API vs Functional API, three-layer architecture, and workflow visualization methods for building AI Agents.
Read more →
·3 min
AI Agent Development Landscape: From Architecture Design to Production Deployment
A systematic overview of the AI Agent tech stack: RAG retrieval, Agent planning, MCP protocol, AI Gateway, and observability — helping developers build production-grade AI systems.
Read more →
·3 min
AI Toolchain-Driven Development: A Guide to Rebuilding Programmer Core Competencies
AI is driving software development's third tool revolution. Explore how MasterGo AI, Cursor, and similar tools span design to code, and learn the future competitiveness formula: full-stack skills + AI proficiency + real-world experience.
Read more →
·3 min
Agent Infinite Loop Engineering Guide: Detection, Breaking, and Root Cause Analysis
How to handle Agent infinite loops? This guide covers three-layer loop detection, four strategy-switching techniques, root cause analysis, and multi-layer fallbacks for building stable, production-grade Agent systems.
Read more →
·3 min
LangGraph Production Template in Practice: A Complete Guide to Budget Control and Canary Routing
Deep dive into langgraph-agent-stack: per-run dollar budget control, canary traffic routing, Mock testing mode, and 800+ test cases to safely deploy AI Agents from demo to production.
Read more →
·4 min
Stop Shipping Skills Blindly! A Google DeepMind Engineer's Hands-On Guide to Agent Evaluation
Google DeepMind engineer Philip reveals: almost everyone uses coding agent Skills, yet almost no one writes evals for them. A deep dive into Skill evaluation methods, 8 actionable tips, and a real Gemini API case study.
Read more →
ui-skills: An AI Skills Library Built …
·4 min
ui-skills: An AI Skills Library Built for Design Engineers
ui-skills is an open-source AI Skills library for design engineers that helps AI generate higher-quality UI code. It quickly gained thousands of GitHub Stars.
Read more →
·3 min
ByteDance Interviewer Deep Dive: How Vibe Coding Is Reshaping Frontend Engineers' Core Competitiveness
A ByteDance interviewer breaks down the 3-layer Vibe Coding interview framework: AI tool awareness, complex product engineering, and a 1-hour full-stack challenge. Architectural thinking wins.
Read more →
·4 min
Loop Engineering in Practice: Designing and Deploying a Multi-Agent Collaborative Development System
A deep dive into Loop Engineering: how multi-agent collaborative dev systems achieve automated coding loops through workflow scheduling, step isolation, and validation.
Read more →
·3 min
Claude Code Enterprise Guide: Environment Setup, Git Workflows, and Switching to Chinese AI Models
Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.
Read more →
·2 min
BrowserSkill: A Controlled Channel for AI Agents to Safely Borrow Your Logged-In Browser
Tencent's open-source BrowserSkill (BSK) lets AI agents reuse your real browser login state via a separate window, single-tab borrowing, and human takeover — safely and within clear boundaries.
Read more →
·3 min
Agent Performance Evaluation: A Three-Layer Framework and Engineering Implementation Guide
A deep dive into the three-layer AI Agent evaluation framework — outcome, process, and system layers — covering trajectory evaluation, tool call accuracy, automated testing, and key engineering challenges.
Read more →
·2 min
Training a CPU-Native LLM on Zero Budget: The Architectural Gamble of Ternary Quantization × Sparse MoE
An indie dev attempts to train a CPU-native LLM on $0 budget using ternary quantization, sparsity, and fine-grained MoE — with pre-registered success criteria and full public reporting.
Read more →
·3 min
AI Code Getting Worse with Every Fix? A Three-Layer Closed-Loop Engineering Methodology to Break the Cycle
AI code spiraling out of control? This article breaks down a three-layer engineering system — Prompt rules, Skill workflows, and Harness feedback loops — with real-world results showing pass rates rising from 70% to 98%.
Read more →
How DSLs Make LLM Outputs More Reliabl…
·3 min
How DSLs Make LLM Outputs More Reliable: Principles and Practice
LLM output instability is a core production challenge. This article analyzes how DSLs improve LLM reliability through verifiability, semantic convergence, and structural constraints.
Read more →
·3 min
Agent Tool Call Failures? Layered Fault Governance Is the Right Answer
How to handle Agent tool call failures? Learn a 3-tier fault governance system: exponential backoff, self-correction loops, and human-in-the-loop for high-risk failures.
Read more →
·3 min
What to Do When Model Training Fails? A Systematic Debugging and Iteration Guide
Model training failure is the norm in research, not the end. Using a real DiT fine-tuning failure on weather radar as a case study, this guide offers a systematic three-layer debugging methodology — data, training convergence, and evaluation — to help deep learning practitioners diagnose issues and iterate efficiently.
Read more →
·3 min
Complete AI Agent Development Learning Path: From Core Principles to Enterprise Deployment
A structured AI Agent learning path covering core principles, prompt engineering, tool use, multi-agent systems, and frameworks like LangChain, CrewAI, and Dify for enterprise deployment.
Read more →
Deep Dives
Deep Dive into AI Agent Skill Design: …
·3 min
Deep Dive into AI Agent Skill Design: Engineering Practices from Anthropic and Perplexity
A deep dive into Skill design philosophy from Anthropic's Claude Code team and Perplexity's Agent team, covering the Tax Test, Gotchas Flywheel, progressive disclosure, and Eval-First practices for building high-quality AI Agent skill systems.
Read more →
Voice-Driven Geometric Interaction: LL…
·2 min
Voice-Driven Geometric Interaction: LLM Semantic Parsing and Function Calling Architecture in Practice
How can LLMs translate natural language into geometric operations? This article breaks down a voice-driven geometry system: LLM for semantic parsing, Function Calling to bridge the geometry SDK.
Read more →