#LLM learning roadmap
236 related articles
·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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·6 min
Claude Code Chinese Guide: A Complete Path from Zero to an Efficient Workflow
A systematic Claude Code learning guide built for Chinese developers, covering ten core modules including Slash Commands, Memory, MCP, and Hooks, with a three-tier path to build an AI coding workflow in 11–13 hours.
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·6 min
AMD MI355X Running GLM5.2: Inference Costs at Half of NVIDIA Blackwell
AMD MI355X achieves 2,626 tokens/sec throughput running GLM5.2 at half the TCO of NVIDIA Blackwell. Deep analysis of the technical logic, ROCm ecosystem progress, and market implications.
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The Complete Guide to Local LLM Deploy…
·2 min
The Complete Guide to Local LLM Deployment: Tools, Hardware, and Model Selection
A complete guide to locally deploying open-source LLMs: covering VRAM requirements, quantization, tools like Ollama and LM Studio, and model selection tips for Llama, Qwen, and more.
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·6 min
Inside the AI Workday of Thomson Reuters' CEO: How Leaders Drive Enterprise Transformation by Example
Thomson Reuters CEO Steve Hasker shares his personal AI routine: analyzing documents, managing his calendar, and gaining insights every Monday. A look at how leaders drive real enterprise AI transformation through practice and continuous learning.
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·6 min
LangChain 1.0 Comprehensive Guide: Three Core Frameworks and Hands-On AI Application Development
Deep dive into LangChain 1.0's architecture: LangChain framework, LangGraph multi-Agent orchestration, and LangSmith observability platform, with hands-on RAG and intelligent customer service projects.
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Stronger Models, Worse Tools? The Hidd…
·4 min
Stronger Models, Worse Tools? The Hidden Pitfalls of Tool Calling in Claude's New Models
Developers found Claude's flagship models Opus and Sonnet perform worse with third-party editing tools than older versions — likely due to RL over-optimization on built-in tools degrading generalization.
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·6 min
Codex Beginner's Guide: Four Product Forms Explained, Plus Comparison with Claude Code and Cursor
In-depth analysis of OpenAI Codex's four usage forms, comparing Codex, Claude Code, and Cursor across price, stability, and frontend/backend fit to help developers choose the right AI programming tool.
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·3 min
LLM Development Learning Path: From Zero to Enterprise-Level Projects
A complete LLM development learning roadmap covering prompt engineering, RAG, AI Agents, and fine-tuning — helping beginners master LangChain, LlamaIndex, and more.
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·5 min
AI-Native Team Practices: How Anthropic Engineers Achieved an 8x Productivity Boost
Anthropic's Fiona Fung shares how AI tools drove an 8x increase in engineer code output, and how AI-native teams are rethinking management, quality, and collaboration.
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·4 min
Adding a 'Repair Layer' to Open-Source Models: How DeepSeek Can Outperform Claude Opus
Independent developer Ahmad Awais found that open-source LLM failures stem from Tool Calling bugs, not model capability. A deterministic repair layer + repair hints can make DeepSeek outperform Claude Opus.
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·6 min
OpenAI CFO Deep Dive: IPO Stance, Compute Shortage, and Jony Ive's New Hardware Revealed
OpenAI CFO Sarah Fryer discusses the $122B fundraise, IPO timeline, Anthropic rivalry, compute shortage crisis, and the mysterious Jony Ive hardware collaboration on the All-In Podcast.
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·7 min
AI Agent Development: A Four-Stage Competency Model from 15K to 40K RMB Salary Growth Path
A detailed four-stage competency model for AI Agent development: from Python/RAG basics (15K) to workflow orchestration (20K), inference optimization (30K), and Agent cluster governance (40K RMB).
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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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·6 min
Is Claude Fable 5 Real? Exposing the AI Reseller Service Scam
Anthropic never released a Claude Fable 5 model. This article analyzes fake AI promotions, exposes wrapper service scam tactics, and provides tips for verifying AI claims.
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·3 min
6-Week AI Agent Development Learning Roadmap: A Complete Guide from Zero to Project Deployment
A systematic 6-week AI Agent development roadmap covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and deployment for beginners to build production-ready agents.
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·4 min
AI Agent Learning Roadmap for Beginners: A Three-Stage Journey from Fundamentals to Hands-On Practice
A systematic AI Agent learning roadmap for beginners covering core theory, the ReAct paradigm, and multi-agent collaboration, with hands-on project suggestions.
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·4 min
AI Agent Development Learning Roadmap: A Complete Four-Stage Plan from Zero to Production
A systematic AI Agent development learning roadmap covering LLM fundamentals, ReAct paradigm, memory & tool calling, and multi-agent collaboration across four stages with project suggestions.
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·3 min
AI Large Language Model Learning Roadmap from Scratch: From Beginner to Enterprise-Level Practice
A systematic AI LLM learning roadmap from scratch, covering Python basics, Prompt Engineering, RAG, Agent development, and enterprise-level projects.
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·3 min
AI Agent Beginner's Guide: A Complete Four-Stage Learning Path
A complete learning path for AI Agent development from scratch, covering core theory, ReAct paradigm, multi-agent collaboration, Prompt optimization, and hands-on projects across four stages.
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