book-skills

Knowledge base from "Accelerate: The Science of Lean Software and DevOps" by Nicole Forsgren, Jez Humble & Gene Kim. Use when applying the DORA four key metrics (deployment frequency, lead time for changes, MTTR, change failure rate), the 24 capabilities framework, Westrum organizational culture typology, or transformational leadership dimensions. Core lane: research-backed delivery performance — why speed and stability reinforce each other, how to measure and improve them, and the organizational practices (technical, management, cultural) that enable high-performing technology organizations.

Knowledge base from "The DynamoDB Book" by Alex DeBrie (v1.0, 2020). Use when designing DynamoDB tables, applying single-table design, choosing modeling strategies (one-to-many, many-to-many, filtering, sorting, migrations), reviewing access patterns, or referencing DDB API/expression usage.

Knowledge base from "Site Reliability Engineering: How Google Runs Production Systems" by Betsy Beyer, Chris Jones, Jennifer Petoff & Niall Murphy (Google). Use when applying SRE philosophy, setting SLOs/error budgets, managing on-call and toil, designing incident response, conducting postmortems, handling cascading failures, or referencing Google's operational frameworks. Lane: SRE philosophy, org/process, postmortems, toil, on-call, error budgets, monitoring, cascading failures, load balancing, data integrity.

Knowledge base from "Implementing Service Level Objectives" by Alex Hidalgo. Use when applying Hidalgo's frameworks for meaningful SLIs, reliability targets, error budget math and policy, SLO alerting, statistics behind SLOs, data reliability, or building SLO culture. This is the deepest practical SLI/SLO/error-budget treatment available — it covers the full Reliability Stack from measurement design through probability/statistics, alerting architecture, and organizational change.

Knowledge base from "AI Engineering: Building Applications with Foundation Models" by Chip Huyen. Use when applying Huyen's frameworks for foundation model adaptation, evaluation methodology, RAG architecture, prompt engineering, finetuning decisions, inference optimization, dataset engineering, and production AI system design.