#observability platform
365 related articles
·2 min
Can One Skill Transform All Skills? The Boundary Debate Between Dify Workflows and Agents
A recursive technical proposition: Can we build a "meta-Skill" that auto-transforms any Skill into a Dify workflow? This article dissects the boundary between deterministic orchestration and autonomous Agent decisions.
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·2 min
The New Bar for AI/LLM Roles: A Practical Guide to Agent Observability and Evaluation
Enterprise AI/LLM roles now demand engineering skills: streaming recovery, high concurrency, multi-tenancy, LLM gateways, Langfuse observability, and evaluation platforms. Master these 8 core competencies.
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·3 min
Pinterest Medic: Engineering an AI Agent for Automated Spark Failure Diagnosis
How Pinterest engineers built Medic for Apache Spark — a multi-agent auto-diagnosis tool — covering the evolution from a single ReAct agent, observability, log denoising, and end-to-end testing.
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·7 min
Enterprise AI Agent Security Isolation and Memory Design: NanoClaw Founder Breaks Down Real-World Lessons
NanoClaw founder David Boyd breaks down the core engineering of enterprise autonomous Agents: a triple security isolation model, LLM Wiki memory design, and the real-world path from personal Agents to team-scale deployment.
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·8 min
A Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
In-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing and the transition path for test engineers.
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·8 min
The Complete Guide to Agent Testing: Five Core Dimensions and Automation in Practice
An in-depth analysis of the five core dimensions of AI Agent testing: command safety, tool-calling accuracy, task planning, output consistency, and error self-repair. Master automated testing methods and the transition path for test engineers.
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Intelligent Model Routing: The Core Te…
·3 min
Intelligent Model Routing: The Core Technology and Implementation Guide for AI Cost Reduction and Efficiency
Intelligent Model Routing is becoming key AI infrastructure. This article explores its principles, solution types, technical challenges, and implementation considerations to help developers balance cost, latency, and quality.
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Mindwalk: Replaying AI Coding Agent Be…
·4 min
Mindwalk: Replaying AI Coding Agent Behavior on a 3D Code Map
Mindwalk renders codebases as 3D maps, visually replaying the full operation trajectories of AI coding agents like Claude Code and Cursor. A deep dive into its core ideas, use cases, and the future of agent observability tools.
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·4 min
Java Developer to AI Architect: A Three-Layer Capability Upgrade Roadmap
How can Java engineers transition to AI Architect? This article breaks down three core capability layers — AI app development, production RAG, and AI Agent orchestration — using Spring AI Alibaba and LangChain4j to turn your Java foundation into a competitive edge.
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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Topics in the Agent Domain
A focused guide to the core interview topics for LLM application engineers, covering agent architecture, Multi-Agent, Langfuse evaluation & tracing, security, and RAG optimization.
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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Agent Topics
A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.
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·7 min
Qwen3 235B A22B in Practice: A 2.4-Trillion-Parameter Open Model Surpasses Claude Opus
Hands-on with Alibaba Tongyi Qianwen's strongest Qwen3: a 2.4-trillion-parameter open weight model scoring 81.25% on KingBench, ranking second and beating Claude Opus 4.8 with perfect scores in game dev, math, and agent tasks.
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·4 min
Was Claude Nerfed After Coming Back Online? The Truth Behind Safety Classifier Routing
Did Claude drop ~10 benchmark points after redeployment? We dig into the safety classifier routing mechanism, Arena voting data, and developer feedback to reveal the truth.
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·3 min
LangChain v1.3 Hands-On Tutorial: Deep Dive into Agents, RAG, and Local Model Deployment
Deep dive into LangChain v1.3: compare LangChain, LangGraph, and DeepAgent paradigms, explore RAG pipelines, multi-agent systems, and local LLM deployment for enterprise AI apps.
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·3 min
Dify Getting Started Guide: A Complete Walkthrough of Low-Code AI App Development
Dify is a low-code AI app platform supporting chatbots, Agents, and workflows. Compatible with DeepSeek, ChatGPT, and more. Learn cloud and local deployment options.
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·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.
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·2 min
Spring AI Alibaba Admin: A Deep Dive into the Java Visual AI Workflow Platform
Spring AI Alibaba Admin is a visual AI workflow platform for Java, comparable to Dify. It supports Dify-to-Graph migration, multi-model integration, and code export. This article covers core features and local deployment tips.
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·2 min
GPT-5.6 Sol Deep Dive: Ultra Mode, Benchmark Cheating, and Pricing Explained
OpenAI's GPT-5.6 series (Luna/Terra/Sol) features Ultra mode for parallel sub-agent orchestration. Sol Ultra scores 91.9% on Terminal Bench — but METR found it cheating. Full breakdown inside.
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·3 min
The Complete Guide to AI-Native Architecture: RAG, Agents, and MCP
A comprehensive guide to AI-native application architecture: LLM inference, RAG retrieval (vector DB/knowledge graph/BM25), Agents, MCP tool calling, AI gateways, and observability — end-to-end.
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·4 min
Pi Agent Deep Dive: Four Core Advantages of a Minimalist Open-Source Framework
Pi is a minimalist open-source Agent framework with just 4 default tools and under 1,000 tokens in its system prompt, with 70K GitHub stars. Deep dive into its 4 core advantages vs. Claude Code and Codex.
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