{R}R Dev Notes

Found total of 8 articles.

The Forward Deployed Engineer, Chapter 11: Palantir — The Original Playbook

Chapter 11 of The Forward Deployed Engineer blog series. The Palantir teardown — founding conditions, the Delta and Echo split, the long years of operational refinement, the AIP pivot, the AI FDE, and the three lessons for founders.

2026-06-06

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 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

Frictionless SaaS Chapter 13: SaaS Metrics, Cohort Analysis, and the North Star

Chapter 13 preview of Frictionless SaaS: the SaaS Metrics Pyramid, Net Revenue Retention, cohort-based optimization, and how to choose a North Star that actually drives retention and revenue.

2026-04-03

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

3.3 Conditioning of Problems vs Stability of Algorithms

Learn the critical difference between problem conditioning and algorithmic stability in numerical computing. Understand why some systems fail even with correct code, and how sensitivity, condition numbers, and numerical stability determine the reliability of AI, ML, and scientific algorithms.

2025-09-15

3.2 Measuring Errors

A clear and intuitive guide to absolute error, relative error, backward error, and how numerical errors propagate in real systems. Essential for understanding stability, trustworthiness, and reliability in scientific computing, AI, and machine learning.

2025-09-14

Hello World Bot｜Mastering Microsoft Teams Bots 2.2

Build your first Microsoft Teams bot with a simple Hello World response. This hands-on section walks you through using the Bot Framework SDK, setting up a local project with Node.js or .NET, using Ngrok to expose your endpoint, and testing your bot directly in Teams.

2025-04-06

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