#agent observability
416 related articles
·3 min
Wattage: An AI Agent Token Cost Profiling and Regression Protection Tool
Deep dive into Wattage, an AI Agent token consumption profiling and cost regression protection tool, exploring its core features, industry context, and value for developers.
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·3 min
Herder: The Open-Source Terminal Tool for Unified Management of Multiple AI Coding Agents
Herder is an open-source terminal multiplexer for macOS and Windows that unifies management of Claude Code, Codex, OpenCode, and other AI coding agents—with persistence and remote reconnection.
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·2 min
Getting Started with AI Agent Development: A Complete Guide from Zero to Real-World Projects
A beginner-friendly guide to AI Agent development, covering the full learning path from LLM basics, prompt engineering, and RAG to LangChain and multi-agent collaboration.
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·2 min
Getting Started with AI Agent Development: A Complete Guide from Zero to Deployment
A beginner-friendly guide to AI Agent development, covering the full learning path from LLM fundamentals, prompt engineering, and RAG to LangChain and multi-agent collaboration.
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·4 min
Spring AI 2.0: Five Key Updates Explained — Marching Toward the Age of AI Agents
Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, Tools parsing moving up, a built-in Agentic mechanism, MCP switching to Streamable HTTP, and an on-demand tool Advisor.
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·4 min
Spring AI 2.0 Explained: Five Key Updates Ushering in the Age of AI Agents
Spring AI 2.0 brings five core updates: mandatory Spring Boot 4 upgrade, Tools parsing moved up, built-in Agentic mechanism, MCP switch to Streamable HTTP, and on-demand tool-loading Advisor.
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·4 min
Spring AI 2.0: Five Key Updates Explained — Stepping into the Agent Era
Spring AI 2.0 brings five core updates: mandatory upgrade to Spring Boot 4, lifted Tools parsing, built-in Agentic mechanism, MCP switch to Streamable HTTP, and an on-demand tool-loading Advisor.
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·4 min
Burning Through 80 Billion Tokens: Why Vibe Coding Is Doomed to Fail
A creator spent 40 days and 80 billion tokens testing the real limits of Vibe Coding. This article dissects why AI programming crashes in production: complexity, context limits, and compression loss.
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·3 min
Anthropic's Hands-On Guide: How to Scientifically Choose and Evaluate AI Models
Anthropic's Applied AI team breaks down a methodology for choosing AI models: building custom evals, avoiding three common pitfalls, measuring value by cost per success, and cutting costs with prompt caching and context engineering.
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·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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·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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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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