What’s up beautiful people
Welcome to another edition of Sloth Bytes. I hope you’re enjoying summer.
Finally, an easy way to learn how AI actually works
Most people don't struggle to learn AI because they're not smart enough. They struggle because every resource is either too shallow, too scattered, or drowns you in math you didn't sign up for.
Intuitive AI Academy gives you one structured path to understanding how tools like ChatGPT, Claude, and Gemini actually work under the hood. You'll go from the basics like tokenization and attention, all the way to the state-of-the-art techniques that show up in real research: pre-training, fine-tuning, LoRA, RLHF, Mixture of Experts, and more. By the end, you'll build your own GPT model from scratch.
It's a great resource whether you're studying machine learning, SWE pivoting into the AI field, or just want to finally understand what's going on inside these models.
5 Free Resources to Actually Learn System Design
System design was never a class I took.
It wasn't in my CS degree, so the first time I heard "system design" was when I was preparing for new grad roles, and you can only imagine my reaction.
A whole other interview topic? With like 50+ important concepts I’m just supposed to know? And you’re telling me I have like 3 months to prepare? GG we’re cooked.
System design used to be a "you'll need this once you're senior" thing. You would never see it for interviews unless you were applying for those roles.
Yet when I went through my new grad job search, some companies had you do system design or at least an easier version of it.
That used to be unheard of for entry-level roles, and now I’m predicting internships will require them too.
I mean AI can essentially handle the syntax now, so I assume they’ll want people who have the system design knowledge to guide the AI. Which is why in today’s edition I want to share 5 resources that’ll help you with system design.
1. ByteByteGo
What is it: A wonderful newsletter and YouTube channel that covers important system design concepts. I think they’re currently the highest quality resource and easiest way to understand these concepts. They break down real systems, how Netflix's CDN actually delivers video, how Uber's dispatch engine matches riders to drivers, how Twitter builds its feed, and tie each one back to an important system design concept. The visuals alone make this worth it.
Why it's useful: You get a nice mental image of the concept, great definition, and useful examples to help you connect everything together. It’s a great place to get started with system design concepts. They also have some example system design questions, but not too many.
What is it: A GitHub repo that walks through every important system design concept. CAP theorem, DNS, load balancers, reverse proxies, CDNs, SQL vs NoSQL, caching strategies, message queues, a structured framework for approaching any design question, then applies that framework to system design interview questions. They also include diagrams and trade-off discussions for those questions.
Why it's useful: If you only have time for one resource on this list, make it this one. It's the rare resource that covers both the fundamentals, the interview questions, and how to answer them. I’ve already recommended this one in my GitHub repos post, but I'm recommending it again because it deserves it. I used this to prepare for my interviews and it’s a great starting point for the topic.
What is it: A YouTube channel from a genuinely smart ex-Google engineer. He’s built one of the most thorough free libraries of system design interview questions and case studies out there, walking through common system design problems and explaining in-depth concepts for distributed systems.
Why it's useful: I recommend watching his videos once you've got the basics down, he covers exactly how you would use these concepts in the real world and for interviews. Plus he’s super entertaining.
What is it: A GitHub repo that actually organizes all these real engineering blogs and conference talks into useful categories for system design. Scalability patterns, availability and failover, stability under load, plus a section on running AI and ML infrastructure at scale. Every entry links straight to the original write-up or conference talk from the team that actually lived through the system design problem.
Why it's useful: This is the resource for when you've had enough theory and just want some real examples. You get to learn what actually broke, how they fixed it, and what they’re going to do in the future. It helps you build that problem solving muscle for system design and helps you think of edge cases or possible scenarios that an interviewer could ask.
What is it: A learning platform built by two former Meta staff engineers, with a paid premium tier for mock interviews and AI-graded practice, but they have a lot of free content. The free content alone covers core concepts like consistent hashing, indexing, and caching patterns, plus full written breakdowns of real interview problems.
Why it's useful: You don't need to pay to get real value here. The free articles and practice problems alone are more than enough to learn the fundamentals or get some practice if you're just starting out. If you end up wanting the mock interviews and AI feedback later, that's there, but it's a "nice to have," not a requirement.
None of these will make you a system design master in a few days, but if you do put in the time, you’ll definitely be ready for those interviews.
That’s all from me!
Have a great week, be safe, make good choices, and have fun coding.
If I made a mistake or you have any questions, feel free to comment below or reply to the email!
See you all next week.
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