#LLM tool invocation
796 related articles
·3 min
GPT-5.6 Released: How Multi-Agent Workflows Are Ending the Chat Box Era
OpenAI releases GPT-5.6 with Sol, Terra, and Luna models plus ChatGPT Work execution environment, shifting AI from chatbots to autonomous multi-agent workflows that directly operate local files and business systems.
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·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
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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
Dify Local Deployment Guide: Full Walkthrough with BT Panel + Docker
A step-by-step guide to locally deploying the Dify open-source AI platform using BT Panel on a VMware virtual machine, covering Ubuntu setup, Docker config, and image pull troubleshooting—beginner-friendly.
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·7 min
Alibaba Open-Sources 2.4T Qwen Model as Chinese AI Sweeps the Global Competitive Landscape
Alibaba open-sources a 2.4 trillion parameter Qwen model and launches the Qwen Token Plan. Chinese models surge, Kimi K3 tops global rankings, and China's AI is reshaping the global competitive landscape.
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·7 min
Harness Engineering: Why a Powerful Model Isn't Enough — Here's What Really Matters
A data-deletion disaster reveals the biggest AI Agent risk: the problem isn't the model, it's Harness design. Learn context management, process standards, and permission isolation.
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·7 min
From Chat to Agent Platform: A Practical Guide to Engineering AI Applications
A deep dive into engineering AI applications: from a simple chat page to a multi-layer Agent platform, covering RAG knowledge bases, Workflow scheduling, multi-model management, and run tracing.
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·2 min
Hermes Agent: A Complete Beginner's Guide to the Self-Evolving Open-Source AI Agent
Hermes Agent is an open-source autonomous AI Agent with long-term memory and self-evolution. Learn its core innovations, how it compares to Open Cloud, and why it hit 121K GitHub stars.
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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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WrenAI: An Open-Source GenBI Tool for …
·4 min
WrenAI: An Open-Source GenBI Tool for Querying Databases with Natural Language
WrenAI is an open-source GenBI tool by the Canner team that converts natural language into trusted SQL, charts, and dashboards via a semantic layer. Supports 20+ data sources including BigQuery and Snowflake. 16,000+ GitHub stars.
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·3 min
Dify 1.8 Complete Beginner's Guide: Build 20+ AI Apps Fast
A complete Dify 1.8 guide covering 3 deployment methods (Docker/cloud/source), MySQL integration, 5 app types (Chatbot/Agent/Workflow), model selection, and publishing strategies.
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·6 min
The Evolution of Claude Code: From Manual Review to 65% Fully-Automated PRs
Anthropic engineers reveal Claude Code's 18-month evolution: system prompt cut by 80%, 65% of PRs shipped automatically by AI, Claude Tag collaboration, and the safety logic behind auto mode.
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jcode Deep Dive: Why Rust Is the Ideal…
·3 min
jcode Deep Dive: Why Rust Is the Ideal Foundation for a Coding Agent Framework
jcode is an open-source Coding Agent framework built in Rust, gaining nearly 200 GitHub Stars in a day. Explore its architecture, Rust advantages, and application potential.
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·3 min
Knowledge Graph-Enhanced RAG: Building a More Powerful Q&A System
A deep dive into the DeepLearning.AI & Neo4j course 'Knowledge Graphs for RAG' — covering core concepts, vector retrieval synergy, and hands-on SEC filing demos.
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·3 min
The Three Core LLM Job Roles Explained: Entry Requirements and Career Roadmaps
A deep dive into the three core LLM job roles — Application Engineer, R&D Engineer, and Algorithm Engineer — covering academic requirements, salaries, and skill roadmaps.
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·3 min
The Truth Behind Three RAG Pipeline Crashes: Why Inter-Stage Data Contracts Matter
A RAG pipeline crashed three times due to inter-stage data format mismatches. Learn how JSON Schema and Pydantic explicit contracts turn fragile AI pipelines into maintainable systems.
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·2 min
WebMCP: The New Standard for AI Agents to Precisely Interact with Web Pages
WebMCP is a proposed web standard that lets pages proactively expose tool interfaces to AI agents via declarative and imperative APIs, eliminating browser automation guesswork. Now in Chrome 149 Origin Trial.
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