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#tutorial

@AYi_AInotes: https://x.com/AYi_AInotes/status/2069399806502453264

X AI KOLs Timeline · 9h ago Cached

A beginner-friendly tutorial on how to set up persistent memory for an AI Agent in 30 minutes, using the open-source EverOS tool to store memory as editable Markdown files, without requiring Docker or vector database clusters.

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#tutorial

@zodchiii: https://x.com/zodchiii/status/2069366611371241944

X AI KOLs Timeline · 11h ago Cached

A guide on building a reusable Claude Code Agent loop that can be pointed at different tasks like bug fixing, speed optimization, or cost reduction by swapping check scripts.

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#tutorial

@bozhou_ai: The Codex tutorials on the market are too scattered. Official documentation, videos, and various bloggers are all separate pieces. For beginners who want to get started systematically, it takes a lot of time just to stitch these together. So my teammates and I spent ten days compiling a 'Codex Orange Book'. Today it's free and open source—take it directly. A 206-page PDF, from...

X AI KOLs Timeline · 19h ago Cached

The 'Codex Orange Book' is a free and open-source 206-page PDF guide that systematically introduces the installation, configuration, core features, and practical cases of OpenAI Codex, aimed at Chinese beginner developers.

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#tutorial

@loganthorneloe: This is a excellent explanation of JAX. Understanding how ML frameworks work internally gives you a massive advantage w…

X AI KOLs Timeline · yesterday Cached

This article explains in detail the core ideas of JAX, including function purity, immutability, explicit state management, and JIT compilation, helping readers shift from object-oriented thinking to functional programming to optimize machine learning performance.

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#tutorial

How to create my own AI real estate analysis agent?

Reddit r/AI_Agents · yesterday

A guide on building a custom AI agent for real estate market analysis.

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#tutorial

@avrldotdev: The best guide for anyone to dive how an HTTP server works & build one yourself. This article will help you learn: 0. N…

X AI KOLs Timeline · yesterday Cached

A comprehensive guide on how an HTTP server works, covering networking protocols, chunked encoding, state machines, parser writing, and concurrency basics, with instructions to build one yourself.

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#tutorial

@iximiuz: https://x.com/iximiuz/status/2069036148077293614

X AI KOLs Timeline · yesterday Cached

A visual guide to SSH local and remote port forwarding, explaining how to access private services and expose local ports via SSH tunnels, with practical examples and configuration tips.

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#tutorial

@0xMortyx: https://x.com/0xMortyx/status/2069002136873058485

X AI KOLs Timeline · yesterday Cached

A detailed guide on using Claude Code's Dynamic Workflows pattern to orchestrate multiple parallel subagents from a single lead agent, with 9 steps covering task decomposition, isolation, and review.

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#tutorial

@wangdefou: https://x.com/wangdefou/status/2068971132615856302

X AI KOLs Timeline · yesterday Cached

This article introduces how to use a $6 VPS and an AI agent to build your own Hysteria2 proxy server, replacing shared proxy services, gaining control over network egress, and details the steps, security considerations, and usage principles.

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#tutorial

@Hesamation: Everything you must know for running LLMs locally at home and owning your AI. Highly Suggested Article.

X AI KOLs Timeline · 2d ago Cached

A thread recommending an article covering everything you need to know to run large language models locally at home and maintain ownership of your AI.

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#tutorial

(How to Write a (Lisp) Interpreter (In Python)) (2010)

Hacker News Top · 2d ago Cached

Peter Norvig's classic tutorial on implementing a Scheme interpreter in Python, explaining the core concepts of language interpretation and evaluation.

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#tutorial

@hwchase17: "Build your own Claude Code with Deep Agents" Good article by the community showing how to build a Claude Code-like age…

X AI KOLs Timeline · 2d ago Cached

An article explaining how to build a Claude Code-like coding agent using LangChain's Deep Agents library, covering the architecture and implementation.

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#tutorial

@portertech: https://x.com/portertech/status/2068646696096264320

X AI KOLs Timeline · 2d ago Cached

This article shares the complete process and experience of successfully applying for Oracle Cloud's permanent free VPS using domestic mobile data and a domestic debit card, including detailed steps and precautions.

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#tutorial

@ai_xiaomu: https://x.com/ai_xiaomu/status/2068613828687085699

X AI KOLs Timeline · 2d ago Cached

A detailed tutorial on GEO (Generative Engine Optimization), from concepts and principles to practical methods, explaining how to make AI recommend your product when answering questions, suitable for AI product entrepreneurs to learn.

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#tutorial

@touxnplayai: https://x.com/touxnplayai/status/2068596799888388373

X AI KOLs Timeline · 2d ago Cached

This tutorial explains how to install Codex++ and configure a DeepSeek API key to unlock the full features of Codex AI tool in China, bypassing the need for a ChatGPT account or subscription.

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#tutorial

@IamValhustle: Monica Lam (Stanford Professor): watch the full breakdown to copy all 5 prompts into Claude. save this post so the form…

X AI KOLs Following · 2d ago Cached

A tweet sharing Monica Lam's prompts for Claude AI, directing users to a full breakdown and encouraging them to save the formula.

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#tutorial

I wrote a free 15-part series on LLM internals — real math, real tensor shapes, real hardware constraints. All grounded in Gemma 4 12B's actual config.

Reddit r/LocalLLaMA · 3d ago

A comprehensive 15-part series covering LLM internals from tokenization to serving, grounded in Gemma 4 12B's actual config.

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#tutorial

@JaydevTonde: https://x.com/JaydevTonde/status/2068361821002846418

X AI KOLs Timeline · 3d ago Cached

A detailed tutorial on implementing CUDA Graphs in an LLM inference server Tokn, covering FastAPI server setup, engine initialization, and CUDA Graph capture for optimized decode phases.

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#tutorial

@_avichawla: 8 RAG architectures for AI Engineers: (explained with usage) 1) Naive RAG - Retrieves documents purely based on vector …

X AI KOLs Timeline · 3d ago Cached

A tweet thread explaining 8 different RAG architectures (Naive, Multimodal, HyDE, Corrective, Graph, Hybrid, Adaptive, Agentic) with their use cases, and hinting at an improved indexing technique.

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#tutorial

@yunxi0623: https://x.com/yunxi0623/status/2068171252595147166

X AI KOLs Timeline · 3d ago Cached

Introduces how to use Obsidian and Claude Code to build a local AI knowledge base, by creating folder structures, writing CLAUDE.md rule files, and step-by-step importing and organizing materials, to achieve long-term portable personal knowledge management.

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