Nil's Blog

An open, deceptively simple special case of stable matching.

Learn how sets & maps are built from scratch, and refine your knowledge of hashing.

Learn how monotonic stacks and queues are two sides of the same idea and how to leverage them in interviews!

A deeper look at this classic grid problem.

A walk through recurrences, memoization, and math tricks -- via Lego castles.

Why context engineering is becoming the name of the game for improving AI apps.

A comprehensive list of all free resources available from Beyond Cracking the Coding Interview, including chapters, tools, templates, and guides.

Learn how this fascinating data structure speeds up graph-related operations.

A new scandal is surrounding peer review.

Lessons from trying to automate redistricting.

The different approaches to finding the k smallest/largest elements in an array.

JS doesn't have built-in queues, which can be an issue if you have to implement a BFS. Here are the workarounds.

An optimal solution for a graph problem that comes up in the Wall Game.

A linear-time algorithm for a graph problem that comes up in the Wall Game.

An introduction to the Wall Game, my new project.

Designing the DB for the Wall Game.

How would you build a Lichess clone in 2025? My process for picking a tech stack.

The specs of the UI for the Wall Game and renders from frontend generators.

The backstory and thought process behind a fun paper from my PhD.

My grandparents' story during the Spanish Civil War.

A collection of arguments in favor of coding interviews.

A binary search recipe that works for every problem, explained without code.

The exact prompts used to create an interactive 3D torus visualization app with vibe coding.

Exploring the geometry of merging faces.

A problem walkthrough using the concepts from Beyond Cracking the Coding Interview.

A proof that heapify takes linear time without using complex equations.

A curious application of binary search.

Exploring the tradeoffs between lazy and eager implementations of common algorithms.

A comprehensive guide to different implementations of Dijkstra's algorithm, with code.

An extensive list of questions that can be solved with DFS.

Many greedy algorithms can be modified to make local rather than global choices while still producing the same solutions.

A step-by-step guide to understanding and implementing dynamic programming algorithms with practical examples.

A guide to implementing preorder, inorder, and postorder tree traversals iteratively.