#DAG planning
141 related articles
·3 min
Coze for Beginners: A Complete Guide to Templates and Workflow Building
Learn how to use Coze (扣子) with zero coding experience — from the Template Store to building custom AI workflows. A complete beginner's guide.
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Multi-Agent Collaboration: A GPT Team …
·2 min
Multi-Agent Collaboration: A GPT Team Engineering Paradigm and Practical Guide
Explore multi-agent collaboration architecture: role division, communication protocols, coordination mechanisms, and how Workbench templates help developers build efficient AI agent teams.
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AI Agents 101: The Core Difference Between LLMs and Agents, and How They're Built
What is an AI agent? How does it differ from a large language model? Learn the core concepts, the Agent formula (LLM + Workflow + Knowledge Base), and how to choose between Dify, LangChain, and LlamaIndex.
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·3 min
LTX2.3 Open-Source Model Tested: Full AI Comic Drama Pipeline on Just 6GB VRAM
LTX2.3 ComfyUI bundle tested: runs locally on 6GB VRAM, covering character generation, image-to-video, storyboarding, motion transfer, and frame interpolation for full AI comic drama workflows.
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·3 min
LangGraph Production Template in Practice: A Complete Guide to Budget Control and Canary Routing
Deep dive into langgraph-agent-stack: per-run dollar budget control, canary traffic routing, Mock testing mode, and 800+ test cases to safely deploy AI Agents from demo to production.
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·3 min
Intent-Driven Development: Claude Code's Evolving Paradigm and Practical Tips
Anthropic engineer Lydia and YK Sugi break down Claude Code's Intent-Driven Development paradigm, covering dynamic workflows, auto mode, sub-agent orchestration, and the evolving role of software engineers in the AI era.
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DeepTutor: An Open-Source AI Tutoring …
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DeepTutor: An Open-Source AI Tutoring System for Lifelong Personalized Learning
DeepTutor is an open-source lifelong personalized AI tutoring system from HKUDS with 26,000+ GitHub stars. Explore its knowledge tracing, RAG, and multi-agent architecture.
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·2 min
Karma: An AI Coding Agent Orchestration Tool for Building Multi-Agent Collaborative Systems
Karma is an orchestration layer for AI coding agent frameworks, solving multi-agent collaboration, task decomposition, state management, and observability challenges. Compatible with Aider, OpenHands, and more.
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·2 min
Forge: Adding Reliability Guardrails to Local Model Tool Calling
Forge is an open-source Python middleware for local models (Ollama, llama.cpp, vLLM) that boosts tool-calling reliability via three-layer guardrails: validation, rescue parsing, and retry.
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·3 min
Open-Source Dynamic Workflows: How awman Enables Multi-Model Collaborative AI Programming
awman's --dynamic flag enables cross-framework dynamic workflows with multi-model collaboration. Explore its leader agent architecture, shared context design, and auto fault-tolerance mechanisms.
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·2 min
AI Agent Development for Beginners: A Three-Phase Learning Roadmap
A structured zero-to-one roadmap for AI Agent development: Phase 1 covers Python & LLM basics, Phase 2 tackles five core Agent capabilities and LangChain/LangGraph, Phase 3 delivers hands-on RAG projects.
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Building RL-Powered Autonomous Researc…
·2 min
Building RL-Powered Autonomous Research Agents with NVIDIA NeMo
How NVIDIA NeMo combines reinforcement learning to train agent skills and build an Autoresearch workflow capable of autonomously running ML experiments end-to-end.
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·3 min
How to Choose an AI Agent Development Course? 5 Practical Screening Criteria to Avoid Common Pitfalls
How to choose a quality AI Agent development course? This guide covers 5 key criteria: complete delivery pipeline, resume-worthy projects, real engineering perspective, update frequency, and mentorship.
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·4 min
LangChain in Practice: Mastering the Four Core Modules of the Agent Ecosystem
A deep dive into LangChain's four core modules: LangChain components, LangGraph orchestration, Deep Agents, and LangSmith. Build your first Agent from scratch.
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·4 min
From 50% to 92%: A Practical Methodology for Teaching AI Agents to Master Spreadsheets
An engineering team spent four months raising an AI coding agent's spreadsheet accuracy from 50% to 92%. Deep dive into REPL architecture, validation loops, and domain knowledge injection.
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Latent Reasoning: The Next-Generation …
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Latent Reasoning: The Next-Generation AI Reasoning Paradigm Beyond Chain of Thought
Is CoT really AI 'thinking'? This deep dive covers latent reasoning's rise — Coconut, HRM, BDH — and the core trade-offs between interpretability, efficiency, and governance in high-stakes AI.
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·3 min
AI Agent Learning Roadmap: From Zero to Building Your Own Intelligent Agents
A structured AI Agent learning roadmap covering fundamentals (Agent principles, Prompt engineering), advanced topics (RAG, multi-agent collaboration), and three hands-on projects — ideal for beginners.
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·2 min
AI Agent Primer: The Core Differences Between Workflows and Intelligent Agents — and How to Build Them
Explore the key differences between AI Agents and workflows, and how LLMs evolve from reasoning to execution. Covers ReAct, task decomposition, enterprise value, and Python+LangChain development.
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·2 min
Graph Theory Algorithm Visualizer: Free Interactive Animations That Make BFS/DFS/Dijkstra Click
LearnGraphTheory.org is a free, ad-free graph theory visualization site with interactive animations for BFS, DFS, Dijkstra, and more. Perfect for beginners.
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·3 min
AI Agent Beginner's Guide: LLMs vs. Agents, and a Full Breakdown of Development Tools
What is an AI Agent? This guide explains the key differences between LLMs and Agents, breaks down the Agent formula (LLM + Workflow + Knowledge Base), and compares tools like Dify, Coze, LangChain, and LlamaIndex.
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