{R}R 開発ノート

合計 34 件の記事が見つかりました。

OpenClaw Engineering, Chapter 13: Hardening the Ecosystem

The final chapter: ecosystem security, the ClawHavoc incident, defending against malware in dependencies, confirming high-risk operations, and building auditing and disaster recovery systems.
2026-03-28

OpenClaw Engineering, Chapter 12: The Agentic Zero-Trust Architecture

Zero-trust security for autonomous agents: managing blast radius, implementing three-tier defense (pre-action, in-action, post-action), container isolation, and defending against indirect prompt injection attacks.
2026-03-27

OpenClaw Engineering, Chapter 11: Continuous Learning with OpenClaw-RL

How OpenClaw-RL extracts training signals from conversations and uses them to improve agent behavior continuously. From binary feedback to token-level distillation, agents learn from every interaction without retraining the base model.
2026-03-26

OpenClaw Engineering, Chapter 10: Multi-Agent Systems

Build teams of specialized agents that work in concert. Learn how to architect planners, coders, critics, and surveyors, coordinate them via channels, and use adversarial collaboration and taste gates for high-quality output.
2026-03-25

OpenClaw Engineering, Chapter 9: Scheduling and Deterministic Orchestration

Time-based automation for agents: cron jobs for simple periodic tasks and the Lobster workflow engine for complex, deterministic, resumable multi-step pipelines with human approval gates.
2026-03-24

OpenClaw Engineering, Chapter 8: Event-Driven Workflows

How OpenClaw agents spring into action automatically via hooks, webhooks, and TypeScript handlers—without waiting for human invocation. From internal events to CI/CD pipelines.
2026-03-23

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 6: Extending Capabilities with SKILL.md

The anatomy of SKILL.md files in OpenClaw: how to author reusable, versioned instruction sets with YAML frontmatter, dependencies, and explicit procedural guidance for agents.
2026-03-21

OpenClaw Engineering, Chapter 5: Connecting Multiple Channels

How to connect your OpenClaw agent to multiple messaging platforms (Telegram, WhatsApp, Discord, Slack) and manage multi-channel routing. Setup, configuration quirks, and troubleshooting for each platform.
2026-03-20

Chapter 19 – Measuring AI Effectiveness

Chapter 19 of Master Claude Chat, Cowork and Code tackles the question every team eventually asks: is our AI actually working? Learn to build metrics frameworks, structured evaluations, and workflow acceleration measurements that prove (or disprove) AI's value.
2026-03-19

Chapter 18 – Sub-Agents and Multi-Agent Collaboration

Chapter 18 of Master Claude Chat, Cowork and Code explores multi-agent architecture — how to decompose complex problems into specialized sub-agents, coordinate parallel execution, and synthesize results into coherent outputs.
2026-03-18

Chapter 17 – Guardrails and Governance

Chapter 17 of Master Claude Chat, Cowork and Code moves from understanding risks to implementing controls — permission isolation, tool allow-lists, human-in-the-loop approval workflows, validation hooks, and enterprise-grade audit logging.
2026-03-18

Chapter 16 – Execution Risks and Isolation

Chapter 16 of Master Claude Chat, Cowork and Code confronts the real security risks of AI systems that execute commands and manipulate files — from command injection to data exposure — and explains the isolation models that keep things safe.
2026-03-17

OpenClaw Engineering, Chapter 2: Anatomy of the Agent Brain

How OpenClaw agents think through their identity files, two-layer memory system, and proactive task scheduling. A deep dive into SOUL.md, AGENTS.md, USER.md, MEMORY.md, HEARTBEAT.md, and semantic memory via Supermemory.
2026-03-17

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 14 – Connecting Systems with the Model Context Protocol (MCP)

Chapter 14 of Master Claude Chat, Cowork and Code explores the Model Context Protocol — the universal bridge that lets Claude connect to Slack, GitHub, Jira, Google Drive, and more, turning isolated AI into a deeply integrated workflow partner.
2026-03-15

Chapter 5: Tokens in Depth — What's Actually in That JWT

Chapter 5 of the OpenID: Modern Identity series — what's really inside an ID Token, Access Token, and Refresh Token, how JWTs are structured, how to validate signatures correctly, and how DPoP and mTLS bind tokens to their legitimate holders.
2026-03-11

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

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 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

8.3 The QR Algorithm (High-Level Intuition)

A clear, intuitive, and comprehensive explanation of the QR algorithm—how repeated QR factorizations reveal eigenvalues, why orthogonal transformations provide stability, and how shifts and Hessenberg reductions make the method efficient. Ends with a smooth bridge to PCA and spectral methods.
2025-10-09

Chapter 7 — QR Decomposition

A deep, intuitive introduction to QR decomposition, explaining why orthogonality and numerical stability make QR essential for least squares, regression, kernel methods, and large-scale computation. Covers Gram–Schmidt, Modified GS, Householder reflections, and why QR is often preferred over LU and normal equations.
2025-10-01

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

4.3 Pivoting Strategies

A practical and intuitive guide to pivoting strategies in numerical linear algebra, explaining partial, complete, and scaled pivoting and why pivoting is essential for stable Gaussian elimination and reliable LU decomposition.
2025-09-20

4.2 Row Operations and Elementary Matrices

A deep but intuitive explanation of row operations and elementary matrices, showing how Gaussian elimination is built from structured matrix transformations and how these transformations form the foundation of LU decomposition and numerical stability.
2025-09-19

Use Case: Helpdesk Assistant Bot｜Mastering Microsoft Teams Bots 6.1

Explore how to build a Helpdesk Assistant Bot in Microsoft Teams. Learn how bots can reduce IT load by handling FAQs, logging support tickets, and notifying users — all within Teams. This section explains features, user experience, and implementation strategies.
2025-04-18

Monitoring, Logging, and Telemetry｜Mastering Microsoft Teams Bots 5.3

Learn how to monitor and support your Microsoft Teams bot in production using logging, Azure Application Insights, and alerts. This section shows how to track user events, diagnose failures, and create telemetry that makes your bot reliable and supportable.
2025-04-17

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

Why Build Bots for Microsoft Teams?｜Mastering Microsoft Teams Bots 1.1

Discover why Microsoft Teams bots are transforming the workplace. This section explores the real-world impact of building bots in Teams, from automating tasks and integrating external services to enabling context-aware digital assistants. Learn how bots can save time, boost productivity, and bring automation into the flow of daily work.
2025-04-02

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