{R}R 開発ノート

合計 118 件の記事が見つかりました。

Chapter 15 – Managing Context Rot and Entropy

Chapter 15 of Master Claude Chat, Cowork and Code tackles the silent failure mode of long-running AI sessions — context rot. Learn strategies for context compression, structured state management, and thinking like an operations team to keep Claude sharp over time.
2026-03-16

Chapter 10: Single Sign-On at Scale — Identity as Infrastructure

Chapter 10 of the OpenID: Modern Identity series — running identity at organizational scale: corporate IdPs (AD, Entra ID), the CIAM vendor ecosystem (Okta, Auth0, Entra ID), multi-tenant isolation, account linking, and external user access.
2026-03-16

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 9: SPA and Mobile Patterns — Auth in Hostile Environments

Chapter 9 of the OpenID: Modern Identity series — SPAs and mobile apps in hostile environments: XSS and CSRF defense, PKCE in the browser, the Backend-for-Frontend pattern, native app patterns, and refresh token rotation with reuse detection.
2026-03-15

Chapter 8: Securing Backend APIs — Bearer Tokens, Scopes, and Service-to-Service

Chapter 8 of the OpenID: Modern Identity series — securing backend APIs with bearer tokens, scope design for least privilege, token introspection versus local JWT validation, and the three mechanisms for service-to-service authentication.
2026-03-14

Chapter 12: CLAUDE.md — Designing Guardrails That Shape How Claude Thinks

Chapter 12 of Master Claude Chat, Cowork and Code explores CLAUDE.md as a living constitution for AI behavior — positive constraints over prohibitions, complete financial and startup examples, instruction decay, hierarchical files, and anti-patterns to avoid.
2026-03-13

Chapter 7: Your First OpenID Application — The Handshake, End to End

Chapter 7 of the OpenID: Modern Identity series — building a real OIDC login end to end: the minimal flow, state and nonce, strict redirect URI matching, sessions from tokens, and the three flavors of logout.
2026-03-13

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 7: Plugins and Domain Specialization — Turning Claude Into Your Organization's Expert

Chapter 7 of Master Claude Chat, Cowork and Code explores how plugins transform Claude from a generalist into a domain expert — with pre-built plugins for Sales, Finance, Marketing, and Legal, slash commands, and organization-managed customization.
2026-03-08

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 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 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

Master Claude Chat, Cowork and Code – The Complete Blog Series

The complete index for the Master Claude Chat, Cowork and Code blog series — 20 chapter teasers covering everything from prompting fundamentals to multi-agent architectures, security governance, and the future of AI-powered work.
2026-03-01

Art of Coding, Chapter 19: Why I Still Code

The final chapter. A personal reflection on why the act of writing code remains meaningful—and why craftsmanship endures even as everything else changes.
2026-01-17

Art of Coding, Chapter 17: AI, Automation, and the Role of the Engineer

How AI changes engineering roles. Why automation removes drudgery but makes human judgment more valuable, and what "curation" means for the future programmer.
2026-01-15

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, Chapter 16: Ethics and Longevity

How ethics and longevity intertwine in code. Why the systems you write today remain your responsibility for years, and how empathy shapes sustainable software.
2026-01-13

Art of Coding, Chapter 15: Code as a Team Sport

Code as a team sport: shared ownership, documentation as craft, and respecting the reader. The human practices that make software sustainable and teams thrive.
2026-01-12

Art of Coding, Part VI: The Human Side of Code

The human side of code: collaboration, culture, and the practices that make software sustainable. How teams thrive when they value people as much as process.
2026-01-11

Art of Coding, Chapter 14: Code Reviews and Pair Programming

Code reviews as mentorship and collaboration. How to write for reviewers, offer critique with respect, and build a team culture grounded in feedback.
2026-01-10

Art of Coding, Chapter 13: Testing as a Design Discipline

Testing is a design discipline. How well-written tests reveal awkward APIs, improve code clarity, and become the most reliable documentation of system behavior.
2026-01-09

Art of Coding, Chapter 12: Version Control as a Storytelling Tool

Git is not just a backup system—it's a narrative tool. How clean commits and thoughtful branching strategies turn version control into a form of storytelling.
2026-01-08

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 10: Anti-Patterns to Avoid

Anti-patterns are the structural traps that silently erode codebases. Learning to recognize them early is one of the most valuable skills a developer can have.
2026-01-05

Art of Coding, Chapter 9: Design Patterns as a Language of Developers

Design patterns compress complex architectural ideas into shared language. But they're tools for solving problems, not decorations for code.
2026-01-04

Art of Coding, Part IV: Patterns, Anti-Patterns, and Architecture

Part IV explores design patterns as language, anti-patterns as warning signs, and architecture as the invisible skeleton enabling system growth.
2026-01-03

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, Part I: Why Code is an Art

Introducing the Art of Coding blog series: a 26-week exploration of what makes code beautiful, maintainable, and enduring in the age of AI.
2025-12-23

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

5.3 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

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

3.1 Norms and Why They Matter

A deep yet accessible exploration of vector and matrix norms, why they matter in numerical computation, and how they influence stability, conditioning, error growth, and algorithm design. Essential reading for AI, ML, and scientific computing engineers.
2025-09-13

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

2.3 Overflow, Underflow, Loss of Significance

A clear and practical guide to overflow, underflow, and loss of significance in floating-point arithmetic. Learn how numerical computations break, why these failures occur, and how they impact AI, optimization, and scientific computing.
2025-09-10

2.2 Machine Epsilon, Rounding, ULPs

A comprehensive, intuitive guide to machine epsilon, rounding behavior, and ULPs in floating-point arithmetic. Learn how precision limits shape numerical accuracy, how rounding errors arise, and why these concepts matter for AI, ML, and scientific computing.
2025-09-09

Chapter 2 — The Computational Model

An introduction to the computational model behind numerical linear algebra. Explains why mathematical algorithms fail inside real computers, how floating-point arithmetic shapes computation, and why understanding precision, rounding, overflow, and memory layout is essential for AI, ML, and scientific computing.
2025-09-07

1.3 Computation & Mathematical Systems

A clear explanation of how mathematical systems behave differently inside real computers. Learn why stability, conditioning, precision limits, and computational constraints matter for AI, ML, and numerical software.
2025-09-05

1.1 What Breaks Real AI Systems

Many AI failures come from numerical instability, not algorithms. This guide explains what actually breaks AI systems and why numerical linear algebra matters.
2025-09-03

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

Use Case: Sales Assistant Bot｜Mastering Microsoft Teams Bots 6.3

Learn how to build a Sales Assistant Bot for Microsoft Teams. From surfacing leads to logging calls and syncing with CRMs, this section shows how bots can empower sales teams to move faster, close deals, and automate follow-ups — all within Teams.
2025-04-20

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

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