Mario Sanchez

Software Engineer

[Paul Graham @paulg]

Don't drop out of college to start or work for a startup. There will be other (and probably better) startup opportunities, but you can't get your college years back.

[Calvin French-Owen @calvinfo]

Some reflections: https://t.co/3UQQuFy0sl

[Y Combinator @ycombinator]

Andrej Karpathy's (@karpathy) keynote yesterday at AI Startup School in San Francisco.

[Mario Sanchez @mariosanchezfc]

@freddier 🙌 Genial

[Mario Sanchez @mariosanchezfc]

@platzi Me lo perdí. Lo subirán a Platzi o en algún lado?

[Bryan Johnson @bryan_johnson]

Today, plan your week out:

. what time you'll go to bed
. when you'll turn off screens
. the days you'll exercise

Then achieve 100% of your goals and be proud of yourself.

[Lex Fridman @lexfridman]

Here's my conversation with @ThePrimeagen, a programmer who has educated, entertained, and inspired millions of people to build software and have fun doing it.

It's here on X in full, and is up everywhere else too (see comment).

Timestamps:
0:00 - Introduction
0:42 - Love for programming
10:15 - Hardest part of programming
12:31 - Types of programming
20:08 - Life story
30:12 - Hardship
31:44 - High school
37:30 - Porn addiction
47:16 - God
1:02:59 - Perseverance
1:12:55 - Netflix
1:25:23 - Groovy
1:30:27 - Printf() debugging
1:36:49 - Falcor
1:46:19 - Breaking production
1:49:04 - Pieter Levels
1:53:34 - Netflix, Twitch, and YouTube infrastructure
2:05:36 - ThePrimeagen origin story
2:20:52 - Learning programming languages
2:29:55 - Best programming languages in 2025
2:34:50 - Python
2:35:30 - HTML & CSS
2:36:20 - Bash
2:37:00 - FFmpeg
2:43:42 - Performance
2:46:15 - Rust
2:51:03 - Epic projects
3:04:27 - Asserts
3:13:41 - ADHD
3:21:49 - Productivity
3:26:13 - Programming setup
4:01:43 - Coffee
4:08:47 - Programming with AI
4:51:31 - Advice for young programmers
5:03:03 - Reddit questions
5:10:35 - God

[Andrew Ng @AndrewYNg]

Some people today are discouraging others from learning programming on the grounds AI will automate it. This advice will be seen as some of the worst career advice ever given. I disagree with the Turing Award and Nobel prize winner who wrote, “It is far more likely that the programming occupation will become extinct [...] than that it will become all-powerful. More and more, computers will program themselves.”​ Statements discouraging people from learning to code are harmful!

In the 1960s, when programming moved from punchcards (where a programmer had to laboriously make holes in physical cards to write code character by character) to keyboards with terminals, programming became easier. And that made it a better time than before to begin programming. Yet it was in this era that Nobel laureate Herb Simon wrote the words quoted in the first paragraph. Today’s arguments not to learn to code continue to echo his comment.

As coding becomes easier, more people should code, not fewer!

Over the past few decades, as programming has moved from assembly language to higher-level languages like C, from desktop to cloud, from raw text editors to IDEs to AI assisted coding where sometimes one barely even looks at the generated code (which some coders recently started to call vibe coding), it is getting easier with each step.

I wrote previously that I see tech-savvy people coordinating AI tools to move toward being 10x professionals — individuals who have 10 times the impact of the average person in their field. I am increasingly convinced that the best way for many people to accomplish this is not to be just consumers of AI applications, but to learn enough coding to use AI-assisted coding tools effectively.

One question I’m asked most often is what someone should do who is worried about job displacement by AI. My answer is: Learn about AI and take control of it, because one of the most important skills in the future will be the ability to tell a computer exactly what you want, so it can do that for you. Coding (or getting AI to code for you) is a great way to do that.

When I was working on the course Generative AI for Everyone and needed to generate AI artwork for the background images, I worked with a collaborator who had studied art history and knew the language of art. He prompted Midjourney with terminology based on the historical style, palette, artist inspiration and so on — using the language of art — to get the result he wanted. I didn’t know this language, and my paltry attempts at prompting could not deliver as effective a result.

Similarly, scientists, analysts, marketers, recruiters, and people of a wide range of professions who understand the language of software through their knowledge of coding can tell an LLM or an AI-enabled IDE what they want much more precisely, and get much better results. As these tools are continuing to make coding easier, this is the best time yet to learn to code, to learn the language of software, and learn to make computers do exactly what you want them to do.

[Original text: https://t.co/HdI3Jb9HmF ]

[arman @armankhon]

I created a roadmap to learn artificial Intelligence and machine learning in 2025.

I recently transitioned to working in ai/ml as a software engineer.

Here are the best free resources and roadmap I used to prepare for interviews and land a job. https://t.co/i4uZxiZU52

[Freddy Vega @freddier]

DeepSeek R1 confirma lo que veíamos venir desde Llama 2.

AI no será un juego cerrado de un par de mega compañías como lo fue search. AI será investigación abierta multinacional.

Hoy, el modelo más avanzado (OpenAI o3) aun es cerrado, pero es cuestión de tiempo.

¿Qué tiene que hacer una empresa o un país para ser parte de la carrera? Invertir en educación matemática profunda y ciencias de la computación de toda la vida.

Eso fue lo que optimizó DeepSeek.

[TK • 木下 @wordsofteekay]

These are the resources I've been using:

Mathematics
> math for ml book: https://t.co/m7XIV2w5qg
> why machines learn book: https://t.co/qIO8OuSOIV
> math for ml course: https://t.co/JOsq5Sv3qp
> @_MathAcademy_

Machine Learning

> Intro to statistical learning: https://t.co/8qDfxxrTWV
> Regression problems: https://t.co/RIYl10NNvc
> Classification problems: https://t.co/rU7nJTB0yq
> Designing Machine Learning Systems: https://t.co/V4xCXexLa8

Deep Learning

> Understanding Deep Learning: https://t.co/9cOvux8nlz
> Building A Neural Network from Scratch with Mathematics and Python: https://t.co/q1iSKO4BWz
> Building A Deep Neural Network from Scratch: https://t.co/BBZP4vLj6v
> Deep Learning specialization: https://t.co/bwjRcwgDVa

And some additional resources for inspiration:

> Machine Learning Research: https://t.co/yKNjawriYI
> Getting Started with Machine Learning by sumit: https://t.co/95Ngh9da1H
> How I'd learn ML in 2025 by Boris: https://t.co/SpqhfAibcb
> How They Became Leading AI Researchers in Just 1 Year: https://t.co/BvNlFubXev

https://t.co/yKNjawriYI

[Andrej Karpathy @karpathy]

The Transformer is a magnificient neural network architecture because it is a general-purpose differentiable computer. It is simultaneously:
1) expressive (in the forward pass)
2) optimizable (via backpropagation+gradient descent)
3) efficient (high parallelism compute graph)

[Gergely Orosz @GergelyOrosz]

The slow, then sudden decline of Stack Overflow.

Full article (cont'd)

[Andrej Karpathy @karpathy]

I still do this most days and I think it works great. My morning brain (right after 1hr exercise and 1 coffee) is quite eager to work and I go directly to the one top priority item. The energy decreases over time and with every distracting item loaded into the context window.

[Mente Masculina @YounesLatensa]

Si tus hábitos no cambian, no tendrás un nuevo año, sólo tendrás otro año.

[Vive con Propósito. @PropositoyVida]

RECUERDA:

[Charlie Holtz @charlieholtz]

I put Gemini 2.0 inside a desktop app and gave it access to my screen, terminal, clipboard, and the internet:

[Andrej Karpathy @karpathy]

💯 Love this post on “info finance”. Prediction markets are an early special case of info finance - the use of markets to create distillations of more expensive mechanisms (eg predictions of voting outcomes). Multiple generalizations. At scale a possible revenue stream for AIs.

[Andrej Karpathy @karpathy]

This is fun! I wasn’t sure what was going to come out of the chatgpt memory feature, but if you left it accumulating memories for many months it seems to be able to get a pretty good sense of you from all your queries and over time. I saw other versions of it too, e.g. “tell me something I may not know about myself” etc. Mix of fun/interesting, maybe slightly unnerving.

(At each query the model has the opportunity to write down notes about you in text, and these memories you can view delete or just disable)

[Mario Sanchez @mariosanchezfc]

Ok here we go. Nvim!