{R}R 開発ノート
合計 37 件の記事が見つかりました。
The Engineering of Intent, Chapter 8: The Four Pillars of AI Architecture
Chapter 8 of The Engineering of Intent blog series. Every durable AI-native project has the same four pillars — Vibes, Specs, Skills, and Agents — and most teams over-invest in one and neglect the rest. A teaser on the pillars, the healthy cycle, and the rebalancing that cut a company's regression rate by 80%.
2026-04-24
The Engineering of Intent, Chapter 7: The GenDD Execution Loop
Chapter 7 of The Engineering of Intent blog series. Generative-Driven Development replaces your ceremony set with a fractal five-step loop: Context, Plan, Confirm, Execute, Validate. A teaser on each step, what goes wrong when it's skipped, and the payments team that cut one-hour cycles down to ten minutes.
2026-04-23
The Engineering of Intent, Chapter 6: Autonomous Orchestration Frameworks
Chapter 6 of The Engineering of Intent blog series. Editors run one agent at a time; orchestration runs many. A teaser on task-specific personalities, memory banks, when to orchestrate (and when not), the 14,000-test case study, and the economics of multi-agent pipelines.
2026-04-22
The Engineering of Intent, Chapter 5: Agentic Editors and Flow States
Chapter 5 of The Engineering of Intent blog series. The editor is where the wiring meets your hands. A teaser on the three generations of editor, how semantic search amplifies your codebase's virtues and vices, the flow killers that destroy productivity, and the shortcut rebind that doubled a team lead's output.
2026-04-21
The Engineering of Intent, Chapter 4: The Model Context Protocol (MCP)
Chapter 4 of The Engineering of Intent blog series. MCP is to agents what HTTP was to the early Web — a common protocol that turns bespoke integrations into reusable infrastructure. A teaser on host/client/server roles, the anatomy of a good tool, the six anti-patterns, and the security pitfalls every team trips over.
2026-04-20
The Engineering of Intent, Chapter 3: Context Momentum and Path Dependence
Chapter 3 of The Engineering of Intent blog series. Agents amplify project momentum — good patterns propagate, bad ones propagate just as fast. A teaser on the First Prompt Trap, context rot, the physics of convention drift, and the ten-thousand-dollar rule for decision rigor.
2026-04-19
The Engineering of Intent, Chapter 1: The Triadic Relationship Model
Chapter 1 of The Engineering of Intent blog series. Software used to be a dyad between engineer and machine. Now a third actor — the AI agent — has joined permanently. A teaser covering the Triadic Relationship Model, the CMDP view of software, and the six failure modes every AI-native team needs to name.
2026-04-17
Chapter 22: Identity in AI Systems — When the "User" Is an Agent
Chapter 22 of the OpenID: Modern Identity series — identity for AI systems: LLM authentication, the Model Context Protocol (MCP), Dynamic Client Registration for ephemeral agents, and the emerging patterns for trusting autonomous non-human actors.
2026-03-28
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
Chapter 21: Decentralized Identity — DIDs, Verifiable Credentials, and OID4VC
Chapter 21 of the OpenID: Modern Identity series — decentralized identity: DIDs (Decentralized Identifiers) without a central authority, Verifiable Credentials with selective disclosure, and OpenID for Verifiable Credentials (OID4VC) as the bridge from centralized to decentralized identity.
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 13: Encapsulating Knowledge with Agent Skills — From Conversations to Autonomous Procedures
Chapter 13 of Master Claude Chat, Cowork and Code introduces Skills — reusable, encapsulated procedures that Claude executes autonomously. Covers SKILL.md structure, YAML frontmatter, trigger descriptions, and the Skills Library pattern for team distribution.
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 6: Discovery and Metadata — How Clients and Providers Find Each Other
Chapter 6 of the OpenID: Modern Identity series — how OIDC discovery, .well-known/openid-configuration, JWKS, and Dynamic Client Registration allow clients and providers to find each other without hand-crafted configuration.
2026-03-12
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
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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Hello World bot 956
Deploy Teams bot to Azure 906
IT assistant bot 890
Microsoft Bot Framework 868
Azure CLI webapp deploy 832
Adaptive Card Action.Submit 791
Teams bot development 790
Bot Framework Adaptive Card 782
Teams production bot 775
Bot Framework example 768
Teams app zip 766
Adaptive Cards 764
Microsoft Teams Task Modules 764
Microsoft Graph 763
Graph API token 760
Zendesk Teams integration 758
Teams bot packaging 755
C 750
bot for sprint updates 750
Azure Bot Services 745
Teams bot tutorial 744
Task Modules 741
Azure App Service bot 738
Bot Framework CLI 737
Bot Framework proactive messaging 737
Teams chatbot 737
Azure bot registration 733
ServiceNow bot 728
Bot Framework prompts 722
proactive messages 704
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