Interview preparation
UNDERSTAND. EXPLAIN. REPEAT.

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Explained questions for the decisions developers make.

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660 questions

Python DSA basics

DSA with Python·Python implementations

Common Python structures

Foundation2 min read

Arrays and strings in Python

DSA with Python·Python implementations

Common questions

Foundation2 min read

Hashing and maps in Python

DSA with Python·Python implementations

Why it matters

Foundation2 min read

Linked list in Python

DSA with Python·Python implementations

Node structure

Foundation2 min read

Stack and queue in Python

DSA with Python·Python implementations

Stack

Intermediate2 min read

Recursion and backtracking in Python

DSA with Python·Python implementations

Common questions

Intermediate2 min read

Trees and BST in Python

DSA with Python·Python implementations

Tree node

Intermediate2 min read

Heap and priority queue in Python

DSA with Python·Python implementations

Built-in heapq

Intermediate2 min read

Graphs in Python

DSA with Python·Python implementations

Graph representation

Intermediate2 min read

Dynamic programming in Python

DSA with Python·Python implementations

Common questions

Intermediate2 min read

Binary search and greedy in Python

DSA with Python·Python implementations

Binary search

Intermediate2 min read

Sliding window and two pointers in Python

DSA with Python·Python implementations

Common questions

Intermediate2 min read

Important Python interview topics

DSA with Python·Python implementations

1. List vs tuple vs set vs dict

Intermediate2 min read

Best Python DSA practice list

DSA with Python·Python implementations

Must know

Advanced2 min read

Overview

Deterministic AI Workflows·Foundations & responsibility boundaries

One of the most important lessons I learned while working with AI-powered workflows is that an LLM does not need to make every decision.

Foundation2 min read

Why Not Let the LLM Control the Entire Workflow?

Deterministic AI Workflows·Foundations & responsibility boundaries

An LLM is useful for interpreting natural language, but its output is probabilistic. Two similar messages can produce different wording or interpretations. This is acceptable for many conversational tasks, but it becomes risky when the syst

Foundation2 min read

The Architecture at a Glance

Deterministic AI Workflows·Foundations & responsibility boundaries

The critical separation is between interpreting language and making business decisions.

Foundation2 min read

What the LLM Does

Deterministic AI Workflows·Foundations & responsibility boundaries

The LLM acts as an information extraction layer, not as the authority for workflow execution.

Foundation2 min read

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