Héctor Iván Montaño Uribe

Emprendedor.

[Héctor Iván Montaño Uribe @himu09]

"I am not sure that I exist, actually. I am all the writers that I have read, all the people that I have met, all the women that I have loved; all the cities I have visited." - Jorge Luis Borges

[Berryxia.AI @berryxia]

Stanford 这堂 2 小时 AI 系统构建课，直接把 Claude 所有教程和 Prompting Thread 秒了！

强烈推荐：
“比你刷过的所有 Claude 教程都实用 10 倍”

里面讲的不是 prompt 技巧，而是 Stanford 真正教工程师如何从零构建可靠 AI 系统的完整方法论。

周末就刷这一个，绝对是你这周最有生产力的事！

我已经将其翻译为中英 文双语视频直接戳这里👇

[Jen Zhu @jenzhuscott]

Study as much maths, physics, neuroscience as you can.

Write on your own, daily.

Read poetry, philosophy, history, classical masterpieces.

Go to museums/galleries to stare at art every now & then.

Daily immersion in nature, even for 10 min only.

Run w/out headsets or phone, only your thoughts.

Listen to slow music.

[Avinash Singh @AvinashSingh_20]

https://t.co/7YmaTYvSeY

[Boring_Business @BoringBiz_]

This 40 minute lecture from Peter Thiel at Stanford will teach you more about business competition than a 2 year MBA program

[Wealth Hatch🧠📈 @WealthHatch_]

10 BOOKS EVERY MAN SHOULD READ

1. NO MORE MR. NICE GUY

[Math Cafe @Riazi_Cafe_en]

NASA's An Introduction to Tensors for Students of Physics and Engineering
by Joseph C. Kolecki

PDF: https://t.co/yLvxYrftgz

[Sr. Lobo · Hábitos Millonarios @LoboEstrategia]

La gente rica colecciona relojes lujosos.

Yo colecciono modelos mentales útiles: reglas generales atemporales que simplifican las decisiones.

Los 12 modelos mentales más poderosos (y peligrosos) que he encontrado:

1. El poder de caminar

[Tom Dörr @tom_doerr]

Guide for building neural networks and LLM systems from scratch

https://t.co/u31gF15Qb5

[Rohit @rohit4verse]

https://t.co/eJMI1VVrCg

[Strace @straceX]

https://t.co/1gIR8O9eox

[vixhaℓ @TheVixhal]

https://t.co/8QMuGgh98i

[Charlie L ⚡️ @charliesbot]

Este post me encantó, y es algo que aplica a cualquier herramienta multiplataforma. También es algo que me tocó experimentar

Los frameworks que prometen un solo codebase para todo siempre suenan genial. Cuando empiezas tu app, es una etapa de luna de miel ver tu proyecto corriendo en todas las plataformas

Cuando tu app madura, los usuarios comienzan a pedir features a los que están acostumbrados en su OS: widgets, sincronización entre devices, y más

Aquí comienza la parte de crear código único por OS, y donde el sueño multiplataforma se cae

[Mariano Rentería @marianorenteria]

Aquí el artículo del WSJ que se volvió viral https://t.co/hLdPsetDMY

[Sam Altman @sama]

GPT-5.2-Codex launches today.

It is trained specifically for agentic coding and terminal use, and people at OpenAI have been having great success with it.

[Julián Campos @juliancamposes]

4 libros que todo programador debería leer si quiere evitar el burnout.

No van de lenguajes.

Ni de frameworks.

Van de cómo piensas, trabajas y te cuidas para programar bien durante años.

Estos libros ayudan justo ahí👇

[Krishna Agrawal @Krishnasagrawal]

Stop wasting hours trying to learn AI. 📘📚

I have already done it for you.

With one list. Zero confusion. And no fluff

📹 Videos:

1. LLM Introduction: https://t.co/Avq3pNZxWY

2. LLMs from Scratch: https://t.co/nGJGCQYi89

3. Agentic AI Overview (Stanford): https://t.co/1JbA2JypnJ

4. Building and Evaluating Agents: https://t.co/02o8b7RAS2

5. Building Effective Agents: https://t.co/Jw0cd23A3K

6. Building Agents with MCP: https://t.co/9uvcpin1j9

7. Building an Agent from Scratch: https://t.co/QiYCLK48tn

8. Philo Agents: https://t.co/TCSX4hnKRf

🗂️ Repos

1. GenAI Agents: https://t.co/VdfLWAA3wW

2. Microsoft's AI Agents for Beginners: https://t.co/3SpFdnMcQa

3. Prompt Engineering Guide: https://t.co/4W7Eh6NKaE

4. Hands-On Large Language Models: https://t.co/LEtKGYBdgU

5. AI Agents for Beginners: https://t.co/3SpFdnMcQa

6. GenAI Agentshttps://lnkd.in/dEt72MEy

7. Made with ML: https://t.co/sL3gbmGUky

8. Hands-On AI Engineering:https://t.co/J79go1Ivlo

9. Awesome Generative AI Guide: https://t.co/xXF08rY8zP

10. Designing Machine Learning Systems: https://t.co/Q39XZLn50b

11. Machine Learning for Beginners from Microsoft: https://t.co/vfkyHL1Gnx

12. LLM Course: https://t.co/wuDkhQ0572

🗺️ Guides

1. Google's Agent Whitepaper: https://t.co/BSjthrG81u

2. Google's Agent Companion: https://t.co/wdzh5zuSvp

3. Building Effective Agents by Anthropic: https://t.co/HmYVgMIA7l.

4. Claude Code Best Agentic Coding practices: https://t.co/H3JpJWlpp3

5. OpenAI's Practical Guide to Building Agents: https://t.co/G1TL1Z2TR3

📚Books:

1. Understanding Deep Learning: https://t.co/EEqkGL7lHe

2. Building an LLM from Scratch: https://t.co/8Ehn91NNxE

3. The LLM Engineering Handbook: https://t.co/yzvXeQAgtV

4. AI Agents: The Definitive Guide - Nicole Koenigstein: https://t.co/FKEzpBewe4

5. Building Applications with AI Agents - Michael Albada: https://t.co/nvBaoR6FxZ

6. AI Agents with MCP - Kyle Stratis: https://t.co/u0M1GfBlsL

7. AI Engineering: https://t.co/A2QxhrpmDc

📜 Papers

1. ReAct: https://t.co/Vbc3vWxQHO

2. Generative Agents: https://t.co/PvNHYnqsOD.

3. Toolformer: https://t.co/HFdds582DI

4. Chain-of-Thought Prompting: https://t.co/GxX5BxXLzV.

🧑🏫 Courses:

1. HuggingFace's Agent Course: https://t.co/zhizqjunzS

2. MCP with Anthropic: https://t.co/LqDZ0oCRfj

3. Building Vector Databases with Pinecone: https://t.co/ncqSVaVHqH

4. Vector Databases from Embeddings to Apps: https://t.co/JOl7SIlguq

5. Agent Memory: https://t.co/5m0UrGwDM9

Repost for your network ♻️
&follow for more stuff on building AI Agents.

[Neo Kim @systemdesignone]

If you want to become a world-class software engineer (in 2026), read these 12 books... 🧵

[Oxford Mathematics @OxUniMaths]

Many people think mathematics lives on the dark side.

Turns out they were right.