#Agent Tuning
793 related articles
·3 min
Agent Skills Explained: Plug-and-Play Skill Packs for AI
A deep dive into Agent Skills architecture: modular design, progressive disclosure mechanism, and how it differs from Multi-Agent systems for AI capability extension.
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·4 min
IntelliJ IDEA Efficiency Configuration Guide: Lessons from Seven Years of Java Development
A senior Java developer shares 7 years of IntelliJ IDEA configuration tips: JVM tuning, AI-assisted coding, Testcontainers testing, debugging tricks, and Spring toolchain setup.
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·5 min
The Complete Guide to AI Agent Development: A Four-Stage Progressive Roadmap
A systematic guide to AI Agent development across four stages: LLM fundamentals, ReAct paradigm, memory & tools, and multi-agent collaboration for developers.
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·5 min
Getting Started with Codex: Four Product Forms Explained & How to Choose Between Cursor, Claude Code, and Codex
In-depth analysis of OpenAI Codex's four forms (CLI, web, plugin, app), comparing Codex, Claude Code, and Cursor on price, stability, and use cases to help developers choose the right tool.
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·2 min
ag-kit: A Deep Dive into the TypeScript-Based AI Agent Development Toolkit
An in-depth analysis of ag-kit, a TypeScript-based AI Agent development toolkit covering core architecture, modular design, use cases, and tech selection advice for full-stack developers.
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·1 min
Gemini 3.5 Internal Testing Leaked: Checkpoint Reportedly Surpasses Opus 5
Reddit leak claims Google Gemini 3.5 training checkpoint beat Opus 5 max thinking mode. We analyze the implications, limitations, and what it means for the LLM race.
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·4 min
Gemini 3.5 Pro Hands-On: No More Lazy Code Generation, Complete Projects in a Single Output
A Reddit user tested Gemini 3.5 Pro in Arena and found it generates 20+ files with hundreds of lines of code per file in a single pass, with no lazy shortcuts or placeholders.
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·4 min
GenAI Job Interview Gone Wrong: Interviewer Googles Gemini for Questions on the Spot — What's Broken in AI Hiring?
A fresh grad interviewing for a GenAI Trainer role faced prime number coding and activation function questions while the interviewer used Gemini to generate questions live — exposing AI hiring chaos.
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·3 min
Copilot Now Charges at API Prices — What Are You Actually Paying For?
With GitHub Copilot now billing at API rates, model costs match raw APIs. This article analyzes Copilot's real value in workflow integration, enterprise governance, and harness engineering.
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·5 min
From Chat to Agent: Automating Your Entire Business Workflow with AI Agents
Veteran AI practitioner Remy breaks down the leap from chat models to AI agents: how agents work, the three pillars of context, tools, and skills, MCP connections, and hands-on architecture to make you a 100x employee.
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·3 min
GLM 5.2 Hands-On: An Open-Source, Low-Cost Model That Rivals Opus
In-depth hands-on review of GLM 5.2: a 753B-parameter open-source model with a 1M-token context, rivaling Opus 4.8 at about one-tenth the price. Full setup guide for Claude Code and Cursor.
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·3 min
ProductPai Weekly Roundup: 5 New AI Products Worth Watching
Based on the ProductPai discovery community's weekly rankings, we round up the top five new AI products—from the family AI picture book platform Tonghui and AI imaging studio Zopia to the layout tool Kami and macOS app Frosted.
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·3 min
ProductPai Weekly Roundup: 5 Noteworthy New AI Products
A roundup of the top five AI products from ProductPai's weekly rankings: from the family AI picture-book platform TongHui and AI imaging studio Zopia, to the document layout tool Kami and macOS efficiency app Frosted.
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·3 min
Hermes Agent in Practice: A Self-Evolving AI Agent Framework
Hermes Agent is a mature AI Agent framework with built-in Claude Code and Codex coding capabilities, supporting 200+ models, multi-platform deployment, and WeChat integration. Its layered memory and self-evolution features enable low-Token automated task execution.
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·3 min
Agent Intent Recognition: Engineering Practices Behind the Three-Layer Funnel Architecture
An in-depth look at the three-layer funnel architecture for agent intent recognition: rules for fast interception, context for routine intents, and LLM as fallback. Exploring the engineering trade-offs of accuracy, latency, and cost.
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·4 min
Mass-Producing AI Short Dramas in Practice: Building a Continuous Production Workflow with Skills
The hardest part of AI short dramas isn't generating a pretty shot, but keeping characters, scenes, and style consistent. This article uses a real American campus drama test to detail how to build reusable workflows with Skills, plus three pitfall-avoidance tips.
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·3 min
Getting Started with AI Agent Development: A Learning Path from Zero to Deployment
A systematic guide to the complete learning path for AI Agent development—covering prompt engineering, RAG knowledge bases, LangChain & LangGraph, fine-tuning, and multi-agent collaboration.
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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.
Read more →
·2 min
Agent Skills Explained: Giving AI Plug-and-Play Capability Packs
Agent Skills is a lightweight open-source format that lets AI agents extend professional capabilities on demand, like loading plugins. Learn what Agent Skills are, the problems they solve, and their modular advantages.
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