This article explains why Architecture Decision Records (ADRs) are essential, defines them as a “black box” for recording decisions, outlines their value, formats, lifecycle, creation process, management tools, and provides concrete ADR examples such as using JWT for authentication and Kafka for messaging.
The article argues that many technical managers fail because they rely on engineering skills instead of developing true management capabilities, illustrating common pitfalls such as micromanaging code, ignoring people, and neglecting upward communication, and offers concrete advice for becoming a competent leader.
The article analyzes how AI coding dramatically boosts individual output but fails to improve organizational delivery, exposing hidden communication bottlenecks and proposing an AI‑Native redesign—three core design principles, a multi‑layered Harness system, and AI Agents—to transform engineering teams into high‑throughput, low‑friction production pipelines.
This article explains what an Architecture Committee is, why enterprises need one, its typical composition, decision processes, daily operations, common pitfalls, and key success factors for effective enterprise‑level architecture governance.
This article explains what an architecture review is, outlines its types and value, details the preparation of documents and participants, provides a step‑by‑step review agenda—including opening, solution presentation, Q&A, and summary—offers tactics for handling challenges, supplies template materials, and defines acceptance criteria for a successful review.
The article explains that truly great technical leaders appear less busy because they focus on anticipating future failure points and controlling system complexity, rather than merely reacting to immediate issues, which leads to more stable systems, smoother teams, and faster project delivery.
The article details the challenges of the legacy Py4OH‑1.0 toolchain for OpenHarmony, explains how Huawei Cloud CodeArts (Py4OH) was used to completely refactor the project with spec‑driven development, AI‑assisted code generation, automated review, and secure, cross‑platform deployment, dramatically reducing code size and development friction.
The Requirement‑Decomposition skill transforms vague PRDs into a 12‑dimension, structured analysis that automatically highlights concurrency, boundary, and permission risks, generates ready‑to‑use test‑case reports, and enforces four safety red‑lines to keep testing effort accurate and reusable.
The article explains why reviewers criticize a lack of related‑work discussion, shows why a simple promise to add citations is inadequate, and provides a structured rebuttal template that categorizes prior work, clarifies its relation to the paper, and highlights the novel contribution.
The article explains why technology selection is a daily, critical task for architects, outlines common scenarios such as choosing languages, databases, caches, and messaging systems, presents a step‑by‑step decision‑making process with criteria, weighting, scoring tables, highlights typical pitfalls, and offers practical guidelines to make informed, demand‑driven choices.
The article explains why vague limitation statements fail in rebuttals, shows common weak replies, and provides a concrete three‑part framework—detailing ability boundaries, potential risks, and future work—to craft specific, persuasive responses to reviewers.
The article uses a classic story of a diligent developer who over‑designed a system to illustrate the dangers of excessive architecture, then outlines agile principles such as YAGNI, KISS, MVP, just‑in‑time design, evolutionary practices, technical‑debt management, and a decision checklist to help teams build just‑enough, maintainable solutions.
The article explains why simply citing strong experimental results does not satisfy reviewers who question a method's theoretical justification, and provides a structured rebuttal strategy that clarifies core mechanisms, underlying assumptions, and the method's applicability limits.
Anthropic’s Claude Code team reports an eight‑fold increase in engineer code output, but the article explains that the real shift is from writing code to verification, with specs stored in repos, routines that merge feedback, PRs and metrics, a bad/sad quality taxonomy, six concrete interfaces, and new challenges around context switching, accountability and role boundaries.
The article analyses the rise of Vibe Coding, its hidden entropy costs for teams, and proposes Spec‑Driven Development (SDD) as a deterministic, context‑engineered alternative, detailing its philosophy, lifecycle, tooling ecosystem, practical adoption steps, and metrics for measuring engineering productivity.
The article explains why simply restating a paper’s motivation is ineffective against reviewer doubts about unclear motivation and insufficient importance, and provides a concrete three‑step response framework—illustrating the problem’s real‑world scenario, the cost of ignoring it, and how the proposed method directly addresses the issue.
The article explains how a scenario view—acting as the dynamic "+1" in the 4+1 model—uses use‑case‑plus‑context scenarios to validate architecture, improve communication, guide testing, prioritize key business flows, and drive development through BDD and test case generation.
The article explains the Stage‑Gate System (SGS) and its IPD‑based implementation, detailing its core concepts, the distinction between "doing the right project" and "doing the project right", and the four foundational ideas that make the process flexible, reusable, and structured for effective product development.
This article provides a detailed walkthrough of every official Superpowers skill—including identifiers, trigger rules, applicable scenarios, execution logic, and manual commands—and demonstrates how to combine these skills in multiple real‑world development workflows such as new feature delivery, urgent bug fixes, parallel task development, PR review remediation, core code refactoring, and multi‑demand parallel development.
The interview with Fiona Fung reveals how Anthropic’s Claude Code boosted engineer output eight‑fold, reshaped coding from a bottleneck to a ubiquitous skill, and forced teams to rethink verification, agency, accountability, and the loneliness that arises when working alongside AI agents.
