#JSON Schema generation
375 related articles
·2 min
QuantaMind: An Open-Source Tool for Testing AI Agent Reliability Locally
QuantaMind is a free, open-source local AI Agent reliability testing tool using pass^k scoring and deterministic evaluation, supporting Ollama, llama.cpp, vLLM, and more.
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·3 min
Programmer to AI Engineer: You're Already 80% There — Here Are the 6 Skills You're Missing
Programmers transitioning to AI engineering aren't starting from scratch. Learn the 6 core skills — LLM APIs, RAG, prompt engineering, LLMOps — needed to make the leap.
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·2 min
From Beginner to Advanced AI Agent Development: A Deep Dive into One Essential Hands-On Book
A deep dive into a hands-on AI Agent development book covering component architecture, RAG, multi-agent systems, Function Calling, and production observability.
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Structured Information Extraction with…
·3 min
Structured Information Extraction with Local 7B Quantized Models: Root Cause Analysis and Engineering Optimization
Using Qwen 2.5 7B quantized locally to extract 60+ fields from insurance/financial contracts? Learn why it struggles and how task splitting, RAG, GBNF, and smarter chunking can fix it.
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The Hidden Costs of AI Coding Tools: A…
·2 min
The Hidden Costs of AI Coding Tools: A Deep Dive into Claude Code's 33k Token Overhead
Claude Code consumes up to 33,000 tokens per request before reading your prompt, vs. 7,000 for OpenCode. We break down why this 5x gap matters for cost, latency, and context windows.
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Migrating a Production AI Agent to GPT…
·2 min
Migrating a Production AI Agent to GPT-5.6: 2.2x Faster, 27% Cheaper — Engineering Lessons Learned
A production AI Agent migrated to GPT-5.6 achieved 2.2x faster speed and 27% lower cost. Deep dive into prompt compatibility, eval frameworks, and migration best practices.
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·4 min
OpenAI Plugins Deep Dive: The Plugin System That Connects ChatGPT to the Real World
A deep dive into OpenAI Plugins: how the system works, its technical architecture, and why it matters. Learn how ChatGPT uses plugins to access real-time data, take real-world actions, and lay the groundwork for AI Agents and Tool Use.
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·4 min
A Deep Dive into Claude Cookbooks: A Guide to the Official 47K-Star Hands-On Code Repository
Anthropic's open-source Claude Cookbooks project offers runnable Jupyter Notebook examples covering RAG, Tool Use, multimodal processing, and more—helping developers master Claude API best practices.
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·5 min
How Can Working IT Professionals Learn AI Efficiently? A Practical Learning Path from Zero to Real-World Projects
Limited time but want to learn AI systematically? This guide maps out a practical learning path for working IT pros—from AI application engineering and prompt engineering to RAG and Agents.
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·3 min
Can MiniMax Serve as a Hermes Agent's Brain? A Complete V0.18 Evaluation
A hands-on test of MiniMax as an AI Agent brain using the Hermes V0.18 framework: fast inference, low cost, stable long tasks—but clear flaws in complex reasoning and tool calling. Learn its three strengths, three weaknesses, and best-fit workflows.
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Reverse-Engineering Web Apps: A New Ap…
·3 min
Reverse-Engineering Web Apps: A New Approach to Breaking Through the API Barrier for AI Agents
Explore a new approach to AI Agent tool integration: reverse-engineering web apps to turn API-less pages into callable Agent tools, with analysis of MCP synergy and challenges.
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·4 min
AI + Automated Testing: Building an Engine-Agnostic Quality System with Skill + CLI
An in-depth analysis of the AI-driven software testing paradigm: with Skill and CLI as the core hub, supporting both platformized management and digital employees, helping testing teams transform from script writers into capability builders.
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·2 min
4-Step Roadmap to Becoming an AI Agent Engineer: From Zero to a $50K LLM Role
A proven 4-step roadmap to becoming an AI Agent engineer: stable LLM calls, tool use (RAG + Function Calling), production engineering, and resume optimization.
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·4 min
Baidu AI Automation System: Trigger Skill Chains with a Single Sentence, Say Goodbye to Manual Workflows
The Baidu AI Automation System uses departmentalized skill libraries and Agent-style orchestration to let managers trigger multi-skill workflows with one sentence—no tech background needed.
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·3 min
Langchain.js Agent Development: A Guide to Deconstructing the OpenClaw Engine Architecture
An in-depth analysis of AI agent development based on Langchain.js—comparing workflow agents and Agent Loops, deconstructing the TypeScript implementation path of an OpenClaw-like engine, covering structured output, MCP, and LangGraph.
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·6 min
AI Agent Development Learning Path: Four Stages from Zero to Hands-On Projects
A systematic breakdown of the AI agent development learning path, covering four stages: fundamentals, RAG knowledge bases, tool use, multi-agent collaboration, and hands-on projects.
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·4 min
The Complete AI Agent Development Learning Path: From Zero to Enterprise-Grade Practice
A systematic AI Agent development learning path covering fundamentals, prompt engineering, tool calling, multi-agent collaboration, and hands-on practice with LangChain, CrewAI, and Dify.
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·7 min
Unity Custom MCP Tool Development Guide: Enabling AI Agents to Precisely Control the Editor
Learn how to develop custom tools based on the Unity MCP Relay Server, enabling AI agents like Cursor to directly control the Unity editor. Covers setup, tool building, parameter validation, and MCP Pro comparison.
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·3 min
GPT-5.6 Sol in Action: A 3D Interactive London Website Generated in 5 Minutes
A Reddit user tested GPT-5.6 Sol with a single prompt. In the Row-Bot framework, the model built a 3D interactive London website in 5 minutes—complete with browser verification and vision analysis. A deep dive into AI coding Agents.
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·4 min
Coze in Practice: A Complete Guide to Building Multi-Agent Collaboration Teams
A systematic guide to Coze's positioning and capabilities, covering Agent-building platform categories, Skill modules, workflow orchestration, and multi-Agent team building.
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