#Goal-Oriented Action Planning
23 related articles
·3 min
A Beginner's Guide to AI Agents: Two Learning Paths for Developers and Practitioners
How to learn AI Agents from scratch? This guide covers two clear paths: developers go from Python to LLMs to open-source framework source code; practitioners use Claude Code or similar tools to get results fast.
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·1 min
Becoming an AI Agent Engineer: A Detailed 4-Week Hands-On Learning Roadmap
Want to become an AI Agent engineer? This article breaks down a 4-week roadmap: from core agent architecture and ReAct, to multi-agent collaboration and real projects.
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·3 min
GPT 5.6 Deep Dive Review: The Most Capable Model Yet — But Also the Most Confusing to Use?
GPT 5.6 brings major capability upgrades and new SOUL/TERRA/LUNA tiers — but also confusing entry points, hidden quota consumption, and a chat window crammed into a floating widget. A deep-dive review.
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·4 min
9 Proven Methods to Make Hermes Agent Actually Work for You
9 battle-tested methods from hundreds of hours with Hermes Agent: model selection (Opus/ChatGPT/GLM), multi-agent failover, cross-device coordination via Tailscale, and reverse prompting workflows.
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·5 min
A Programmer's Guide to Large Language Models: The Complete Path from Prompts to Agents
A tailored large-model learning path for ordinary programmers: from prompt engineering, API calls, and LangChain, to RAG, Agents, fine-tuning, and enterprise deployment—six steps to build AI application skills fast.
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·4 min
Godot Game AI Development: Building Autonomous NPC Planning with GOAP
A deep dive into building a GOAP (Goal-Oriented Action Planning) AI system in Godot — moving beyond FSMs and behavior trees to enable autonomous NPC planning. Covers core mechanics, extensions, and real-world test cases.
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·7 min
AI Agent Practical Guide: From Content Generation to Enterprise Applications
A deep dive into AI Agent's two core directions: 2C content generation (text/images/video) and 2B enterprise applications (RAG/AutoGen/LLM integration). With real startup cases and practical methods.
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·7 min
Building an AI Agent from Scratch: Implementing Core Conversational Agent Features in Python
Learn AI Agent development from scratch. This tutorial covers LLMs and prompts, then builds a conversational agent in Python using the DeepSeek API with multi-turn dialogue and system prompts.
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·4 min
HAMAS Multi-Agent Framework in Practice: A Guide to Building 5 AI Personas Working in Harmony
Learn how to build a multi-Agent AI team with the HAMAS framework: 5 role configurations, Skill mechanisms, gradient model scheduling, and solutions for AI hallucination and deception.
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·3 min
Planning with Files: Solving AI Coding's "Amnesia" Problem with Three Files
Planning with Files uses three Markdown files and Hooks to solve the context loss problem in AI coding tools like Claude Code and Cursor during long tasks.
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·3 min
Beginner's Guide to Agent Skills: Structure Breakdown & Custom AI Skill Development
A deep dive into Agent Skill's core concepts and internal structure, covering skill.md, references, scripts, and assets with a restaurant poster Skill example.
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·3 min
12 Practical Tips for Vibe Coding with Trae SOLO: From Getting Started to Efficient Collaboration
12 practical tips for vibe coding with Trae SOLO covering agent selection, Plan mode, context management, custom rules, and more to build an efficient AI programming workflow.
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·2 min
Claude Fable User Guide: Four Core Tips to Boost AI Development Efficiency
Anthropic shares four key tips for Claude Fable: assign bigger tasks, choose effort levels wisely, rewrite old instructions, and shift from tasks to goals.
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·3 min
AI Startup in Practice: A Complete Breakdown of $8,374 in Revenue from a $100 Investment in 13 Days
Robbie, an ordinary employee, used $100 and an AI Agent to launch a business, earning $8,374 in 13 days. A full breakdown of the path from failure to success, including AI-driven market analysis and a stunning 43.8% conversion rate.
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·4 min
AI Agent Core Architecture Explained: A Deep Dive into the Four Key Modules — Perception, Brain, Action, and Memory
Deep dive into AI Agent architecture: explore the four core modules — Perception, Brain, Action, and Memory — covering RAG, tool calling, Chain of Thought, and more.
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Deep Dives·3 min
Deep Dive into How Claude Code Works: A New Programming Paradigm Driven by the Agent Loop
Deep dive into how Claude Code works, including the Agentic Loop, automatic context compaction, tool calling, and permission modes that power autonomous AI programming.
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Deep Dives·3 min
How Claude Code Works: Inside the Agentic Programming Tool
Deep dive into Claude Code's core mechanisms including tool calling, agentic search, memory systems, and MCP protocol extensions. Learn how this CLI agent tool autonomously plans and executes complex development tasks.
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Product Reviews·3 min
Costco Research Automation Agent Hands-On: One-Click Reproduction of Eigenfaces from Paper to Code
Hands-on test of Costco end-to-end research automation Agent: from reading the classic Eigenfaces paper to PCA code implementation, eigenface visualization, experimental evaluation, and LaTeX paper delivery in six steps.
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Product Reviews·3 min
Ruflo: A Multi-Agent Orchestration Solution That Turns Claude Code into a 100-Person AI Team
Ruflo is an open-source multi-agent orchestration platform that upgrades single-threaded Claude Code into a distributed AI dev team with 100+ specialized Agents and a SANA self-learning engine.
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Tutorials·3 min
35 Lines of Prompts Let Codex Auto-Optimize Your Workflow — Reposted by OpenAI's President
An OpenAI employee used just 35 lines of prompts to have Codex analyze 30 days of work history, identify repetitive tasks, and generate reusable automated Skills. Combined with screen reading and long-term memory, Codex is becoming a proactive workflow optimization agent.
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