{R}R Dev Notes

Found total of 18 articles.

The Forward Deployed Engineer, Chapter 13: When FDE Goes Wrong — Failure Modes and Lessons

Chapter 13 of The Forward Deployed Engineer blog series. Six named failure modes that kill FDE functions before they scale. A teaser on the Consulting Trap, the Snowflake-per-Customer trap, the Hero Engineer, the Demo-Debt Spiral, the Sponsor Collapse, and the Burnout Death Spiral.
2026-06-08

The Forward Deployed Engineer, Chapter 8: The Inner Loop — Prototype to Production

Chapter 8 of The Forward Deployed Engineer blog series. From the end of discovery to the first production milestone, the engagement runs on the inner loop. A teaser on the DARE framework, Minimum Viable Architectures, demo-driven development, the hardening phase, and when the customer wants to help.
2026-06-03

The Forward Deployed Engineer, Chapter 7: Customer Discovery and the Messy Reality

Chapter 7 of The Forward Deployed Engineer blog series. The most important fourteen days of any engagement are the first fourteen. A teaser on the three outputs of discovery, the async interview, the Weird Tuesday problem, the workflow inventory, and the Eval-Customer Split.
2026-06-02

The Engineering of Intent, Chapter 9: Advanced Context Engineering

Chapter 9 of The Engineering of Intent blog series. Context engineering is the highest-leverage activity in AI-native development. A teaser on the Context Pack, the Layered Prompt, the A/B test that proved more context isn't better context, and the three anti-patterns that quietly kill agent quality.
2026-04-25

Frictionless SaaS Chapter 16: The Power of Self-Service

Chapter 16 preview of Frictionless SaaS: the Self-Serve Maturity Model, the Independence Principle, and how self-serve billing and account management turn scalability into a competitive moat.
2026-04-06

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 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 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

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

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 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

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

4.0 Solving Ax = b

A deep, accessible introduction to solving linear systems in numerical computing. Learn why Ax = b sits at the center of AI, ML, optimization, and simulation, and explore Gaussian elimination, pivoting, row operations, and failure modes through intuitive explanations.
2025-09-17

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

1.4 A Brief Tour of Real-World Failures

A clear, accessible tour of real-world numerical failures in AI, ML, optimization, and simulation—showing how mathematically correct algorithms break inside real computers, and preparing the reader for Chapter 2 on floating-point reality.
2025-09-06

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

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