{R}R Dev Notes

Found total of 14 articles.

The Engineering of Intent, Chapter 34: Language-Specific Field Notes

Chapter 34 of The Engineering of Intent blog series. Every programming language produces its own Vibe Coding texture. A teaser with field notes on TypeScript, Python, Go, Rust, Java/Kotlin, Ruby, C#, and Shell — including the cross-language pattern that fixes agent default-to-stale-idiom in any language.

2026-05-20

The Engineering of Intent, Chapter 33: Building Your Personal Vibe Coding Operating System

Chapter 33 of The Engineering of Intent blog series. Every sustainable Vibe Coder has a personal operating system — tools, files, conventions, and habits that turn the practices in this book into your own durable system. A teaser on the five files, the three models, the two editors, the one discipline, and the wonder to keep.

2026-05-19

OpenClaw Engineering, Chapter 7: The Skill Ecosystem

Bundled skills vs workspace skills, skill discovery and context, publishing to ClawHub, managing 13,000+ community skills without collision, semantic search, and the meta-skills that let agents improve themselves.

2026-03-22

OpenClaw Engineering, Chapter 1: The OpenClaw Paradigm

The first chapter teaser in a new series on OpenClaw Engineering. Why autonomous agents need a different foundation, the four-layer architecture (Gateway, Nodes, Channels, Skills), and the three principles that hold it all together.

2026-03-16

Chapter 6: What Is Claude Cowork? — The Desktop Agent That Touches Your Files

Chapter 6 of Master Claude Chat, Cowork and Code introduces Claude Cowork — a sandboxed desktop agent that automates file management, data extraction, and cross-application workflows on your local machine.

2026-03-07

Chapter 5: Rapid Prototyping with Artifacts — From Conversation to Live Application

Chapter 5 of Master Claude Chat, Cowork and Code explores how Claude Artifacts collapse the feedback loop between idea and execution — turning conversations into live, interactive applications in seconds.

2026-03-06

Master Claude, Chapter 4: Context Persistence with Claude Projects — Solving the AI Amnesia Problem

Chapter 4 of Master Claude Chat, Cowork and Code explains how Claude Projects solve the AI amnesia problem with persistent context — custom instructions, knowledge bases, and shared team workspaces that remember your architecture, conventions, and patterns across every conversation.

2026-03-05

Master Claude, Chapter 3: Understanding Entropy and Prompting Fundamentals — Why Your Prompts Fail and How to Fix Them

Chapter 3 of Master Claude Chat, Cowork and Code explains why some prompts work and others fail — through the lens of entropy and probability. Covers XML-structured prompting, chain-of-thought reasoning, multishot examples, and a standard prompt template you can use immediately.

2026-03-04

Art of Coding, Chapter 5: Consistency and Style

Consistency is kindness. How coding standards, formatters, and idiomatic style shape code that teams can actually live with.

2025-12-29

5.4 Practical Examples

Hands-on LU decomposition examples using NumPy and LAPACK. Learn how pivoting, numerical stability, singular matrices, and performance optimization work in real systems, with clear Python code and practical insights.

2025-09-26

5.3 LU in NumPy and LAPACK

A practical, in-depth guide to how LU decomposition is implemented in NumPy and LAPACK. Learn about partial pivoting, blocked algorithms, BLAS optimization, error handling, and how modern numerical libraries achieve both speed and stability.

2025-09-25

2.4 Vector and Matrix Storage in Memory

A clear, practical guide to how vectors and matrices are stored in computer memory. Learn row-major vs column-major layout, strides, contiguity, tiling, cache behavior, and why memory layout affects both speed and numerical stability in real systems.

2025-09-11

1.2 Floating-Point Reality vs. Textbook Math

Floating-point numbers don’t behave like real numbers. This article explains how rounding, cancellation, and machine precision break AI systems—and why it matters.

2025-09-04

Numerical Linear Algebra: Understanding Matrices and Vectors Through Computation

Learn how linear algebra actually works inside real computers. A practical guide to LU, QR, SVD, stability, conditioning, and the numerical foundations behind modern AI and machine learning.

2025-09-01

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