{R}R Dev Notes

Found total of 26 articles.

The Forward Deployed Engineer, Chapter 9: The Outer Loop — Scaling Field Intelligence

Chapter 9 of The Forward Deployed Engineer blog series. The outer loop begins the moment a deployment goes into production. A teaser on gravel roads and paved superhighways, the productization decision, the platform commit, measuring leverage, and the two-team handshake.
2026-06-04

The Forward Deployed Engineer, Chapter 5: The AI and Agentic Frontier

Chapter 5 of The Forward Deployed Engineer blog series. The technical bar that the FDE shares with platform engineers — plus the AI-specific skills that separate the role in 2026. A teaser on agents beyond chatbots, RAG, multi-agent orchestration, evals as a discipline, and model-agnostic deployment.
2026-05-31

The Forward Deployed Engineer, Chapter 1: What Is a Forward Deployed Engineer?

Chapter 1 of The Forward Deployed Engineer blog series. The opening chapter of a new book — the operator's contradiction, the Palantir origin, the anatomy of the role, why the AI moment needs it now, and how the FDE differs from every sister role it gets confused with.
2026-05-27

The Engineering of Intent, Chapter 36: The Long View

Chapter 36 of The Engineering of Intent blog series. The long view. What happens to our craft, our profession, and our lives over the next ten years? A teaser on cycles and waves, three things that will endure, three that will change, and a final word on identity.
2026-05-22

The Engineering of Intent, Chapter 18: The Prompt Patterns Catalog

Chapter 18 of The Engineering of Intent blog series. Ten prompt patterns I use every day, with the design moves behind them. A teaser on Planning, Targeted Diff, Adversarial Review, Bug-Hypothesis, Scoping-Down, Consistency-Check, Teach-Back, Written-Down-Rule, Test-First, and One-Page-Design prompts.
2026-05-04

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

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 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 21: Operations and Scalability Without Friction

Why growing SaaS companies hit a wall that is not a product problem or a sales problem — it is an operations problem. A teaser for Chapter 21 of Frictionless SaaS covering the Event-Driven Operations Architecture and the Scalability Without Headcount Principle.
2026-04-11

Frictionless SaaS, Chapter 19: Self-Serve Monetization and Growth

The Self-Serve Growth Engine, the Expansion Revenue Framework, and the Seamless Handoff Principle — how to turn upgrades into a natural moment instead of a sales call.
2026-04-09

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

Frictionless SaaS, Chapter 4: The First Ten Minutes - Designing the Session That Decides Everything

Chapter 4 of the Frictionless SaaS blog series. The first ten minutes of a user's first session decide whether they activate or silently churn. The First Session Blueprint and the Empty State Opportunity are the two design patterns that separate products users love from products users forget.
2026-03-25

Frictionless SaaS, Chapter 2: The SAFE Journey — A Map of Where Your Users Actually Quit

Chapter 2 of the Frictionless SaaS blog series. The SAFE Journey Framework breaks the user lifecycle into Signup, Activation, Frequency, and Expansion — each with different friction, different metrics, and different fixes. Plus: why Time to Value is the most important retention metric in early-stage SaaS.
2026-03-23

Frictionless SaaS, Chapter 1: Silent Churn — The Users Who Leave Without Complaining

Chapter 1 of the Frictionless SaaS blog series. Silent churn is the most dangerous kind of churn — users who sign up, disappear, and never tell you why. A look at the Silent Churn Pattern and the Activation Gap.
2026-03-22

Frictionless SaaS, Part 0: How Users Actually Find, Judge, and Try Your Product

Kicking off a blog series based on the book "Frictionless SaaS." This first post introduces Chapters 0.1 through 0.3 — Discovery, the Landing Page, and Freemium & Entry Points — the three friction points every user hits before they ever sign up.
2026-03-21

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

Chapter 11: CI/CD Integration and Automation — Claude Code in Your Pipeline

Chapter 11 of Master Claude Chat, Cowork and Code shows how to deploy Claude Code into CI/CD pipelines — GitHub Actions, GitLab CI, automated PR reviews, security audits, documentation sync, cost management, and production safety patterns.
2026-03-12

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

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

3.1 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

2.4 Vector and Matrix Storage in Memory

A clear, practical guide to how vectors and matrices are stored in computer memory. Learn row-major vs column-major layout, strides, contiguity, tiling, cache behavior, and why memory layout affects both speed and numerical stability in real systems.
2025-09-11

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

2.1 Floating-Point Numbers (IEEE 754)

A detailed, intuitive guide to floating-point numbers and the IEEE 754 standard. Learn how computers represent real numbers, why precision is limited, and how rounding, overflow, subnormals, and special values affect numerical algorithms in AI, ML, and scientific computing.
2025-09-08

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

Numerical Linear Algebra: Understanding Matrices and Vectors Through Computation

Learn how linear algebra actually works inside real computers. A practical guide to LU, QR, SVD, stability, conditioning, and the numerical foundations behind modern AI and machine learning.
2025-09-01

Categories

Tags

Search Logs

Development & Technical Consulting

Working on a new product or exploring a technical idea? We help teams with system design, architecture reviews, requirements definition, proof-of-concept development, and full implementation. Whether you need a quick technical assessment or end-to-end support, feel free to reach out.

Contact Us