Books

A practical field guide for using AI assistants at work—and engineering them in production. Learn the standards that prevent “sounds right, wrong” outputs: specs, grounding, tools, evals, guardrails, and cost control.

PLEASE NOTE THAT THIS IS NOT THE FULL BOOK BUT JUST CHAPTER 1 and 2 because a simple topic like Simple Linear Regression became 20+ pages long. As a full-time frontend architect, I'm writing and releasing this book chapter by chapter, at a pace that fits around my day job and life. So, think of this as a journey we're taking together, one concept at a time. REST OF THE CHAPTERS WILL BE AVAILABLE AT REGULAR INTERVALS. So keep me motivated by subscribing :)

Written from experience, this book simplifies the chaos — cutting through noise to help you focus on clarity, storytelling, and structure. Each chapter walks you through how to position yourself, build confidence, and think like a product leader. It even shows how to use AI as a co-pilot for faster prep, sharper insights, and better results.This playbook captures the frameworks, mindsets, and lessons she wishes she had when starting her own PM interview journey.

Most companies are stuck in "pilot purgatory"—endless AI experiments that never scale. Teams spend weeks sharing clever prompts and one-off scripts, but nothing makes it into production. Budgets evaporate, engineers' enthusiasm curdles into cynicism, and executives start asking "we spent how much on this?" The problem isn't the AI tools—it's the approach. AI models are inherently non-deterministic (ask the same question twice, get different answers), while software engineering demands deterministic, reliable results. Without structure to bridge this gap, AI adoption fails spectacularly. This book introduces PIT™ (Plan Implement Test), a proven methodology that transforms unpredictable AI outputs into reliable engineering workflows. Built from thousands of hours of real development work, PIT™ channels AI's capabilities through structured planning, phased implementation, and comprehensive testing—delivering the consistency that production code demands.

LM Studio is a great tool for running LLM models locally on your own computer. Tech overviews and Python examples. Deep dive into using Model Context Protocol (MCP)

Learn how real databases work by following this practical guide to building your own in a programming language of your choice.Build a language from scratch- Create an interpreter that can parse, type check and run SQL queries. Start with running simple queries and build up to more complex ones.Learn SQL (the fun way) - Gain a deeper understanding of SQL. Cover the order of execution of queries, how SQL uses ternary logic and the techniques that databases use to join and group data efficiently. Compare your implementation with databases such as PostgreSQL, MySQL, SQLite and DuckDB.Improve as a programmer- The perfect project to practice how to structure and refactor code as you grow the feature set of your database server. The 200+ included test cases provide a safety net for refactoring your code, giving you freedom to experiment. Learn computer science topics including creating a recursive descent parser, building a type checker and implementing iterators.

Professionals require tools to perform their jobs effectively. Product designers, Salespeople, Managers, and Software Developers all have tools. What about Software Architects?

Get a solid foundation in machine learning and learn practical applications of LLM-based applications.

競技プログラミングを始めたいですか？ 難解なコードを読むのにうんざりしていませんか？ 次にどの問題を解決すれば良いか分からず、改善できないことに疲れていませんか？ 解いた問題からあまり学べていないですか？（「どの問題も全然違うように見える :( 」） そんなあなたをサポートします！ この本は競技プログラミングへの入門ガイドです！

Este libro explica la filosofía detrás de Leanpub, desde su origen en "un libro es una startup" hasta su forma actual. La Publicación Lean es el acto de publicar un libro en progreso utilizando herramientas ligeras y muchas iteraciones para obtener retroalimentación de los lectores, pivotar hasta que tengas el libro correcto y ganar tracción una vez que lo tengas.

Learn HTML and CSS, the hard way.

Crie uma simples app de vendas com o Angular. Agora com o Angular 17!

Ideas for projects when teaching Python as well as general inspiration ex. when building a hobby project. It sources use-cases from Reddit and is grouped in some 20 chapters.