#tree of thoughts
11 related articles
·3 min
The Complete Guide to Prompt Engineering: From Zero to Practical Application
A complete guide to learning Prompt Engineering, covering LLM selection, prompt writing techniques, zero-shot/few-shot prompting, chain of thought reasoning, and Python API development.
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·3 min
Loopcraft Explained: Loop-Stacking Architecture Design in AI Agent Development
Deep dive into Loopcraft loop-stacking architecture for AI Agent development, covering retry, self-validation, and meta-learning loops to boost reliability.
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·3 min
A Three-Month Roadmap to LLM Development: A Deep Dive into the Learning Path from Zero to Freelancing
A deep dive into the three-step LLM development learning path: from prompt engineering and RAG knowledge bases to AI Agent development, with realistic timelines for beginners and experienced developers.
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·3 min
Building a Cold Chain Logistics Optimization Research Project with Codex: A Complete Workflow from Scratch to PDF Paper
Learn how to use OpenAI Codex to build a complete cold chain logistics optimization research project from scratch, including simulated annealing implementation, experiments, figures, and LaTeX paper compilation.
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·4 min
AI Agent Development: A Complete 6-Week Systematic Learning Roadmap
A 6-week systematic learning roadmap for AI Agent development, covering core architecture, ReAct principles, multi-agent collaboration, RAG integration, and deployment.
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·4 min
Learning Path for AI Agent Development: A Complete Guide from Core Architecture to Production Deployment
A complete learning path for AI Agent development covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and lightweight deployment to guide developers from basics to production.
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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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·3 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Guide from Beginner to Practitioner
A systematic AI Agent development learning roadmap covering core concepts, ReAct/CoT paradigms, multi-agent collaboration, and hands-on projects across four stages.
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·2 min
Two Years of AI Growth: From Passively Following Instructions to Proactively Understanding Intent
A look at AI's core evolution over two years: from a prompt-dependent instruction follower to an autonomous collaborator that understands intent, plans tasks, and self-corrects.
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Tutorials·3 min
Hermes Agent Framework Practical Guide: Building AI Agents from Scratch
A detailed guide on ByteDance's Hermes Agent framework covering core features, deployment, custom tool development, and enterprise-grade AI Agent applications.
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Tutorials·3 min
Complete Breakdown of Andrew Ng's Agent Course: A Practical Guide to the Five Core Modules of AI Agent Development
Deep dive into Andrew Ng's viral AI Agent course covering five core modules: Reflection, Planning, Tool Use, Multi-Agent Collaboration, and Memory, with practical learning paths for LLM agent development.
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