{R}R Dev Notes
Found total of 18 articles.
The Engineering of Intent, Chapter 37: Context Scaling — Just-In-Time Retrieval for Million-Line Codebases
Chapter 37 of The Engineering of Intent blog series. Hand-authored Context Packs don't scale past a million lines. A teaser on Just-In-Time Context, retrieval via MCP, the three governors that prevent runaway retrieval, and a concrete pipeline from a 3.8M-line codebase.
2026-05-23
The Engineering of Intent, Chapter 22: A Day in the Life — A Narrated Session
Chapter 22 of The Engineering of Intent blog series. A narrated recreation of a real, medium-complex working day — hour by hour — because average days are where practice gets tested. A teaser of the hourly shape, and the single rule behind all of it: agents are leverage on thinking you've done.
2026-05-08
The Engineering of Intent, Chapter 13: VibeOps and CI/CD Evolution
Chapter 13 of The Engineering of Intent blog series. Static CI/CD was built for human-paced commits. AI-native velocity needs dynamic, context-aware, agent-literate pipelines. A teaser on VibeOps, context preservation across deployments, merge queues at velocity, and the ten-minute pipeline contract.
2026-04-29
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 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 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 2: Cognitive Load and Material Disengagement
Chapter 2 of The Engineering of Intent blog series. When the agent does most of the typing, the real failure mode is the engineer who has stopped engaging. A teaser on material disengagement, impressionistic scanning, the autocomplete trap, decision fatigue, and the seven habits of engaged engineers.
2026-04-18
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
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 12: Detecting Disengagement and Structured Win-Back
Chapter 12 preview of Frictionless SaaS: the Disengagement Detection System, the four-touch Win-Back Sequence, and why value rediscovery beats discount offers every time.
2026-04-02
Frictionless SaaS: The Complete Series Index — Your Guide to All 24 Chapters
The complete reader's guide to the Frictionless SaaS blog series. An introduction to the thesis — that in the AI era, features are commoditized and experience is the only lasting competitive advantage — plus direct links to all 25 posts across the 24 chapters of the book.
2026-03-20
Chapter 14: Hardening Your Identity Stack — Setting the Defaults That Keep You Safe
Chapter 14 of the OpenID: Modern Identity series — hardening defaults that neutralize common attacks: strict redirect URI matching, audience validation to solve the confused deputy problem, token lifetime tuning, and refresh token binding, rotation, and revocation.
2026-03-20
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
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 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
Art of Coding, Part VII: Beyond Today
Introduction to Part VII. As AI writes more code, what becomes the engineer's irreplaceable role? A look at how automation transforms—but doesn't diminish—the craft.
2026-01-14
6.3 Applications in ML, Statistics, and Kernel Methods
A deep, intuitive explanation of how Cholesky decomposition powers real machine learning and statistical systems—from Gaussian processes and Bayesian inference to kernel methods, Kalman filters, covariance modeling, and quadratic optimization. Understand why Cholesky is essential for stability, speed, and large-scale computation.
2025-09-30
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