{R}R 開発ノート


合計 96 件の記事が見つかりました。

Chapter 9: Claude Code Fundamentals — The CLI Agent That Rewrites Your Codebase

Chapter 9 of Master Claude Chat, Cowork and Code introduces Claude Code — a CLI agent that reads, analyzes, and modifies codebases directly from the terminal. Covers architecture, multi-file refactoring, Git worktrees, and permission management.
2026-03-10

Chapter 8: Scheduled Tasks and Autonomous Execution — Making Claude Work While You Sleep

Chapter 8 of Master Claude Chat, Cowork and Code covers scheduled automation with Claude Cowork — cron-based recurring workflows, sleep/connectivity handling, error strategies, and applying GTD principles to AI task automation.
2026-03-09

Chapter 3: Core Concepts — The Vocabulary of OpenID Connect

Chapter 3 of the OpenID: Modern Identity series — the IdP/RP/user triangle, claims and JWTs, the three OIDC token types, consent and scopes, sessions vs tokens, and the boundary between authentication and authorization.
2026-03-09

Chapter 2: From OpenID to OpenID Connect — How the Industry Got This One Right

Chapter 2 of the OpenID: Modern Identity series — tracing how the industry moved from the original OpenID and SAML through OAuth 2.0 to OpenID Connect, and when to reach for each standard.
2026-03-08

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 1: Why Identity Is Hard — The Trust Problem Behind Every Login

Chapter 1 of the OpenID: Modern Identity book series — why identity is a trust problem first and a technology problem second, and why authentication and authorization must never be conflated.
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

OpenID: Modern Identity for Developers and Architects — A 22-Part Blog Series

Introduction and index for the 22-part blog series based on OpenID: Modern Identity for Developers and Architects by Sho Shimoda — with links to every chapter from Why Identity Is Hard through Identity in AI Systems.
2026-03-06

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

Master Claude, Chapter 2: The Three Pillars of Claude — Chat, Cowork, and Code

Claude is not one product — it is three. Chat for reasoning, Cowork for desktop automation, Code for terminal-based development. Chapter 2 of Master Claude Chat, Cowork and Code explains the architecture of each and the decision framework for choosing the right one.
2026-03-03

Master Claude, Chapter 1: The Evolution of Large Language Models — From Markov Chains to Context Engineering

Chapter 1 of Master Claude Chat, Cowork and Code traces the journey from statistical text prediction to reasoning engines — and explains why context engineering, not bigger models, is where the next leap in AI productivity comes from.
2026-03-02

Art of Coding, Part VII: Beyond Today

Introduction to Part VII. As AI writes more code, what becomes the engineer's irreplaceable role? A look at how automation transforms—but doesn't diminish—the craft.
2026-01-14

Art of Coding, Part V: Tools and the Ecosystem

Tools shape the culture of how teams code. The right ecosystem amplifies clarity and craftsmanship; the wrong one creates friction and distraction.
2026-01-07

Art of Coding, Chapter 11: Architectural Thinking

Architectural thinking is the discipline of designing systems that survive real-world growth. It means asking how your code will feel to live in years from now.
2026-01-06

Art of Coding, Chapter 8: Performance without Sacrificing Clarity

Chasing speed too early blinds you to real bottlenecks. Clarity first, measurement second, optimization third—that's the order.
2026-01-02

Art of Coding, Chapter 7: Error Handling and Resilience

Designing for failure, not avoiding it. How graceful error handling, clear logging, and balanced defense build systems that endure.
2026-01-01

Art of Coding, Chapter 6: Abstraction and Modularity

Drawing boundaries that make systems stronger. How to abstract without over-engineering, and design interfaces that last.
2025-12-31

Art of Coding, Chapter 4: Maintainability and Scalability

How to build code that bends instead of breaks, systems that grow without collapsing, and anticipate change without over-engineering.
2025-12-28

Art of Coding, Chapter 3: Readability First

Readability first: how naming, structure, and visual rhythm make code habitable for teams and time.
2025-12-27

Art of Coding, Chapter 2: The Philosophy of Clean Code

Clean code is a philosophy, not a rulebook. Explore simplicity vs. cleverness, expressiveness as communication, and code as a form of writing.
2025-12-25

Art of Coding, Chapter 1: Code That Speaks

Chapter 1 of the Art of Coding series. Why beauty in code is not decoration but survival — clarity, empathy, efficiency, and what separates code that works from code that lasts. Plus: what AI-generated code means for craftsmanship.
2025-12-24

7.1 Gram–Schmidt and Modified GS

A clear, practical, book-length explanation of Gram–Schmidt and Modified Gram–Schmidt, why classical GS fails in floating-point arithmetic, how MGS improves stability, and why real numerical systems eventually rely on Householder reflections. Ideal for ML engineers, data scientists, and numerical computing practitioners.
2025-10-02

6.2 Memory Advantages

A detailed, intuitive explanation of why Cholesky decomposition uses half the memory of LU decomposition, how memory locality accelerates computation, and why this efficiency makes Cholesky essential for large-scale machine learning, kernel methods, and statistical modeling.
2025-09-29

5.2 Numerical Pitfalls

A deep, accessible explanation of the numerical pitfalls in LU decomposition. Learn about growth factors, tiny pivots, rounding errors, catastrophic cancellation, ill-conditioning, and why LU may silently produce incorrect results without proper pivoting and numerical care.
2025-09-24

3.4 Exact Algorithms vs Implemented Algorithms

Learn why textbook algorithms differ from the versions that actually run on computers. This chapter explains rounding, floating-point errors, instability, algorithmic reformulation, and why mathematically equivalent methods behave differently in AI, ML, and scientific computing.
2025-09-16

3.3 Conditioning of Problems vs Stability of Algorithms

Learn the critical difference between problem conditioning and algorithmic stability in numerical computing. Understand why some systems fail even with correct code, and how sensitivity, condition numbers, and numerical stability determine the reliability of AI, ML, and scientific algorithms.
2025-09-15

3.2 Measuring Errors

A clear and intuitive guide to absolute error, relative error, backward error, and how numerical errors propagate in real systems. Essential for understanding stability, trustworthiness, and reliability in scientific computing, AI, and machine learning.
2025-09-14

Chapter 3 — Computation & Mathematical Systems

A clear, insightful introduction to numerical computation—covering norms, error measurement, conditioning vs stability, and the gap between mathematical algorithms and real implementations. Essential reading for anyone building AI, optimization, or scientific computing systems.
2025-09-12

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

1.0 Why Numerical Linear Algebra Matters

A deep, practical introduction to why numerical linear algebra matters in real AI, ML, and optimization systems. Learn how stability, conditioning, and floating-point behavior impact models.
2025-09-02

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

Use Case: Project Management Assistant Bot|Mastering Microsoft Teams Bots 6.2

Explore how to build a Project Management Assistant Bot for Microsoft Teams that delivers task summaries, reminders, and updates directly in the chat. Learn how this bot improves team productivity by integrating with tools like Jira or Trello and surfacing key information within the Teams workflow.
2025-04-19

Teams App Manifest and Packaging|Mastering Microsoft Teams Bots 5.2

Transform your bot into a full Teams app. This section walks through how to create a Teams app manifest, add branding, define scopes, and package your bot into a distributable .zip file for sideloading, internal use, or submission to the Microsoft App Store.
2025-04-16

Deploying to Azure|Mastering Microsoft Teams Bots 5.1

Learn how to deploy your Microsoft Teams bot to Azure for production use. This section walks through setting up an Azure App Service, configuring environment variables, connecting to Bot Channels Registration, and testing your bot in the cloud.
2025-04-15

Message Extensions|Mastering Microsoft Teams Bots 4.3

Learn how to build search- and action-based Message Extensions in Microsoft Teams. This section shows how to let users interact with your bot directly from the message composer — to search records, fill forms, or insert rich cards — all without leaving the chat.
2025-04-13

Proactive Messaging|Mastering Microsoft Teams Bots 4.2

Learn how to build bots that initiate conversations in Microsoft Teams. This section explains proactive messaging — including when and how to use it, how to store conversation references, and best practices to ensure your bot helps without interrupting.
2025-04-12

Task Modules|Mastering Microsoft Teams Bots 4.1

Learn how to use Task Modules in Microsoft Teams to embed rich, interactive modal experiences inside your bot. This section explains how to launch, return data from, and design secure webviews that turn chat into structured user interaction.
2025-04-11

Conversation Flow and Dialogs|Mastering Microsoft Teams Bots 3.3

Learn how to build intelligent conversation flows in Microsoft Teams bots using dialogs. This section explains how to guide users through multi-turn interactions, manage state, use prompts and waterfalls, and decide when to use dialogs versus Task Modules.
2025-04-10

Rich Responses with Adaptive Cards|Mastering Microsoft Teams Bots 3.2

Learn how to create rich, interactive messages in Microsoft Teams using Adaptive Cards. This section explains how to design, send, and handle cards in your bot — making your bot feel less like a chat and more like a true app experience inside Teams.
2025-04-09

Message Handling|Mastering Microsoft Teams Bots 3.1

Learn how to build responsive and intelligent Microsoft Teams bots by handling messages effectively. This section covers activity types, keyword detection, mentions, markdown formatting, conversation context, and tips for scaling from simple replies to powerful, workflow-driven bots.
2025-04-08

Bot Authentication and Identity|Mastering Microsoft Teams Bots 2.3

Learn how Microsoft Teams bots authenticate users and access secure data. This section covers SSO, OAuth 2.0, and the Microsoft Graph API, giving your bot the ability to understand identity and act on behalf of users—safely and seamlessly.
2025-04-07

Hello World Bot|Mastering Microsoft Teams Bots 2.2

Build your first Microsoft Teams bot with a simple Hello World response. This hands-on section walks you through using the Bot Framework SDK, setting up a local project with Node.js or .NET, using Ngrok to expose your endpoint, and testing your bot directly in Teams.
2025-04-06

Overview of Microsoft Teams Bot Capabilities|Mastering Microsoft Teams Bots 1.3

Explore the full range of capabilities bots can offer in Microsoft Teams. This section breaks down interactive contexts, features like Adaptive Cards, proactive messaging, user authentication, Graph API integration, and what limitations still exist. Get a developer’s guide to what’s possible.
2025-04-04

Overview of Microsoft Teams Architecture|Mastering Microsoft Teams Bots 1.2

Get a developer-friendly introduction to how Microsoft Teams is built. This section explains Teams architecture—channels, tabs, bots, messaging extensions, and Graph API—and shows how each component fits into the broader platform. A must-read before building your first bot.
2025-04-03

Mastering Microsoft Teams Bots: A Complete Developer’s Guide

The definitive guide to building bots for Microsoft Teams—from fundamentals to deployment. Learn how to build intelligent and interactive bots using the Microsoft Bot Framework, integrate Adaptive Cards and Task Modules, send proactive messages, authenticate users with Teams SSO, and deploy securely on Azure. Packed with practical examples and real-world use cases, this book will help you automate workflows, enhance collaboration, and deliver smart experiences inside Teams.
2025-04-01