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ZyVOP14h ago · 18 min read

Algorithms You'll Actually Use: Sorting, Searching, Recursion, and Beam Search

An algorithm is just a step-by-step recipe for solving a problem. "To find a name in a phone book, open it in the middle, decide which half the name is in, and repeat" is an algorithm. You use them al

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ZyVOP1d ago · 21 min read

Data Structures for AI Engineers: Arrays, Hash Maps, Trees, Graphs, and Heaps

Welcome to Track B, the computer science fundamentals. In Post 15 we saw that picking the right data structure can make code thousands of times faster, and nothing else we tried came close. This post

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ZyVOP5d ago · 17 min read

Performance & Memory: Profiling, Vectorization, and How Python Manages Memory

This is the last post in our Python track, and it's about making code faster and lighter. It's core, but with one big warning that I'll repeat several times: don't optimize until you've measured. Prog

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ZyVOP6d ago · 16 min read

Concurrency: Threads, Processes, and asyncio (and Why LLM Apps Love Async)

Imagine you need to ask a language model 100 questions. Each answer takes about two seconds to come back. If you ask them one at a time, that's over three minutes of your program mostly sitting still

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ZyVOPOct 24 · 16 min read

Testing with pytest: Fixtures, Fake Models, and Properties

Here's a feeling you'll know soon enough. You change one small thing in your code, and you're not sure what else you just broke. So you run the program by hand, try a couple of inputs, and hope. Tests

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ZyVOPOct 23 · 14 min read

Packaging & Environments: Modules, Virtual Environments, and pyproject.toml

Every programmer eventually says the same sentence: "But it works on my machine." Usually it means two computers have different versions of Python, or different libraries installed, or both. This post

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ZyVOPOct 21 · 10 min read

Decorators & Context Managers: The @ and with You Keep Seeing

Open almost any modern Python project and you'll spot two things quickly. Lines that start with @, like @app.get("/hello"). And blocks that start with with, like with torch.no_grad():. They look like

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ZyVOPOct 21 · 11 min read

Iterators, Generators & Comprehensions: How Python Handles Streams of Data

When you chat with an AI model and the answer appears word by word, instead of all at once, something specific is happening in the code. The text is arriving in small pieces, and your program is handl

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ZyVOPOct 21 · 10 min read

Functions in Depth: Scope, Closures, and Passing Functions Around

In Post 4 you wrote simple functions that take an input and return an output. That's the easy part. This post goes into the parts that confuse people later, and the parts that show up everywhere in AI

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ZyVOPOct 21 · 10 min read

Built-in Data Structures: Lists, Dicts, Sets, and Tuples

In the last post you stored single values: a name, a number, a piece of text. Real programs deal with collections. A list of chat messages. A dictionary of settings. A pile of documents where you need

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Algorithms You'll Actually Use: Sorting, Searching, Recursion, and Beam Search

Data Structures for AI Engineers: Arrays, Hash Maps, Trees, Graphs, and Heaps

Performance & Memory: Profiling, Vectorization, and How Python Manages Memory

Concurrency: Threads, Processes, and asyncio (and Why LLM Apps Love Async)

Testing with pytest: Fixtures, Fake Models, and Properties

Packaging & Environments: Modules, Virtual Environments, and pyproject.toml

Decorators & Context Managers: The @ and with You Keep Seeing

Iterators, Generators & Comprehensions: How Python Handles Streams of Data

Functions in Depth: Scope, Closures, and Passing Functions Around

Built-in Data Structures: Lists, Dicts, Sets, and Tuples