{R}R 開発ノート

合計 16 件の記事が見つかりました。

The Engineering of Intent, Chapter 16: The Morning Routine

Chapter 16 of The Engineering of Intent blog series. The first thirty minutes of your workday set the upper bound on how much you will accomplish. A teaser on the five-step morning routine — reload, sync Specs, review memory bank, warm up, launch — and the anti-routine that destroys more productive days than any other pattern.
2026-05-02

The Engineering of Intent, Chapter 15: The Future of the Human Engineer

Chapter 15 of The Engineering of Intent blog series. Am I going to be replaced? The honest answer, after five years of watching the discipline evolve. A teaser on intent architecture, staying relevant, the economic reshaping of the senior-to-junior ratio, and craft in a craftless era.
2026-05-01

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

Frictionless SaaS, Chapter 8: Designing for Habit - Why Retention Is Your Real Growth Engine

Chapter 8 of the Frictionless SaaS blog series. Retention is the multiplier on every dollar of acquisition you'll ever spend. The Habit Loop Engine, the Return Reason Architecture, and the DAU/WAU signals that tell you whether you're building a habit or a one-night stand.
2026-03-29

Chapter 20 – The Next Decade of AI Coworkers

Chapter 20 of Master Claude Chat, Cowork and Code looks ahead — from conversational AI to embedded infrastructure, from chat interfaces to computer use, and the trust and responsibility questions that will define how AI reshapes work over the next decade.
2026-03-20

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 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

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

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

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

5.1 LU with and without Pivoting

A clear and practical explanation of LU decomposition with and without pivoting. Learn why pivoting is essential, how partial and complete pivoting work, where no-pivot LU fails, and why modern numerical libraries rely on pivoted LU for stability.
2025-09-23

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

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

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