#Agent Tool Calling
1867 related articles
·2 min
The Four Core Concepts of AI Agents Explained: Function Calling, Tool, MCP, and Skill
A clear breakdown of the four core AI Agent concepts: Function Calling, Tool, MCP, and Skill — understand the full tech stack behind intelligent agent development.
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·2 min
AI Agent Development in Practice: A Complete Guide to Framework Selection, Tool Calling, and Production Deployment
A comprehensive guide to AI Agent development: covering Agent vs. Chatbot differences, framework selection, tool calling design, RAG pipeline setup, and production deployment best practices.
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·3 min
Local Gemma 3 12B as an AI Agent: A Practical Guide to Tool Calling and Framework Selection
Running Gemma 3 12B locally via Ollama and want to build an AI Agent? This guide covers tool calling, n8n/LangChain/CrewAI comparisons, context limits, and more.
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·5 min
GPT-5.6 Released: Hands-On Analysis of Programmatic Tool Calling and Autonomous Agents
GPT-5.6 is officially released with core upgrades including programmatic tool calling, autonomous subagent delegation, and higher token information density. A hands-on card game build reveals its Agentic power.
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·4 min
The Three Eras of AI Agents: The Capability Leap from Tool Calling to Autonomous Orchestration
An in-depth look at the three core eras of AI Agent development: reliable tool calling, coherent long-task execution, and autonomous orchestration with metacognition. Helps developers match tasks to model capabilities.
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·4 min
Enterprise AI Agent Development Guide: Multi-Task Recognition and Dynamic Tool Calling in Practice
A deep dive into AI Agent architecture and enterprise deployment. From LangChain and ReAct design to dynamic tool calling and multi-task recognition — build autonomous enterprise AI assistants.
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·4 min
Building an AI Agent Framework from Scratch: Deep Dive into Tool Calling, Memory, and Dual-Model Scheduling
Build an AI Agent from scratch — no frameworks. Deep dive into Function Call schema design, MCP remote mirroring, dual-model routing, and short-term memory management.
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Tutorials·3 min
ReAct vs. CodeAct: Two Core Approaches to Agent Tool Calling
In-depth comparison of ReAct and CodeAct — two core Agent tool-calling architectures. From paper principles to code implementation, learn the trade-offs between reasoning+action and code execution.
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Tutorials·3 min
MCP Protocol Explained: Differences from Function Calling and Agent Tool Development in Practice
Deep dive into MCP (Model Context Protocol): its principles, communication architecture, and practical applications. Compare MCP vs Function Calling, explore client-server communication and security.
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·2 min
Agenta: A Detailed Look at the Open-Source Self-Hosted Claude Cowork Alternative
Agenta is an open-source AI Agent collaboration platform supporting self-hosted models and any Agent framework, positioned as an open-source Claude Cowork alternative.
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·3 min
Gemini Managed Agents API Update: Environment Hooks and Free Tier Fully Explained
Google Gemini Managed Agents API introduces environment hooks, model selection, free tier support, and default model upgrades—empowering AI Agent developers with stronger execution control and lower barriers to entry.
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·3 min
Lessons from Claude Code's 80% Prompt Reduction: Less Is More in Prompt Engineering
Anthropic cut Claude Code's system prompt by 80% and got better performance. Learn why verbose prompts hurt, how to streamline them, and key takeaways for AI developers.
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·4 min
Free Claude Code Tutorial: Complete Configuration Guide for Connecting to Agnes Multi-Modal Models
Learn how to connect Claude Code to Agnes AI's free models via Sense Switch for zero-cost text, image, and video generation, with complete setup steps and real-world results.
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·4 min
Getting Started with Claude Code: Environment Setup, Common Commands, and Git Workflow in Practice
A detailed guide to Claude Code installation, domestic model switching, project analysis commands, and Git workflow practice to help developers quickly master this AI programming collaboration tool.
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·4 min
Microsoft Open-Sources AI Agent Governance Toolkit: Comprehensive Coverage of OWASP Top 10 Risks
Microsoft open-sources agent-governance-toolkit covering all OWASP Agentic Top 10 risks through policy enforcement, zero-trust identity, execution sandboxing, and reliability engineering for production AI Agent deployment.
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·2 min
Google's Beyond Zero: An Enterprise Security Framework That Goes Beyond Zero Trust for the AI Era
Deep dive into Google's Beyond Zero security concept, exploring how enterprises can move beyond traditional Zero Trust models in the AI era to address prompt injection, data poisoning, and other emerging threats.
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·2 min
Three Major Updates to Gemini API Managed Agents: Free Tier, Cost Controls, and Scheduled Triggers
Google Gemini API Managed Agents launches three key updates: Free Tier for universal access, Cost Controls for budget safety, and Scheduled Triggers for automated execution.
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·5 min
July 24 AI Daily Brief: Flux 3 Multimodal Release, Kimi K3 Lags in Testing, Qwen Tops TTS Rankings
July 24 AI news: Black Forest Labs launches Flux 3 multimodal model, Kimi K3 lags in US-UK gov tests, Alibaba Qwen tops TTS rankings, Etched raises $300M, AMD unveils MI430X.
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·4 min
Harness Engineering: The Core Infrastructure for Taking AI Agents from Demo to Production
Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to go from demo to production.
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·4 min
Harness Engineering: The Core Infrastructure for Taking AI Agents from Demo to Production
Deep dive into Harness Engineering: why AI Agents need memory management, durable execution, guardrails & approvals to reach production. Based on Scott Moss's workshop.
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