The article compares two AI‑driven coding assistants, grill‑me and superpowers, by having them each build the same web‑based endless‑runner game, then analyzes their questioning styles, workflow ownership, generated artifacts, time consumption, and suitability for different project scales.
The author runs a side‑by‑side experiment feeding the same subway‑runner game requirement to Claude Code with either the Grill‑Me skill or the Superpowers plugin, then compares their questioning style, generated artifacts, development time, and long‑term maintainability to show when each tool shines.
The article argues that Codex membership isn’t a waste of money if you embed it into your development process, outlining its concrete capabilities, the types of developers who benefit most, scenarios where it shines, and who can safely postpone subscribing.
The article compares three popular AI‑coding frameworks—Superpowers, OpenSpec, and Spec‑Kit—explaining their core mechanisms, strengths, weaknesses, and ideal use‑cases, and provides a detailed decision matrix and practical guidance for selecting or combining them in real projects.
The article outlines a structured AI‑coding framework for React Native projects that turns product requirements, API specs, and Figma designs into a traceable development pipeline using prompts, sub‑agents, rule‑based gates, code generation, compile verification, visual audit, and experience deposition to ensure verifiable, high‑quality output.
AGENTS.md is a concise, project‑root file that guides AI coding assistants like Claude Code, Codex, and Cursor to behave like senior engineers by enforcing non‑negotiable rules, minimal changes, verification‑first execution, and clear communication, all distilled from Karpathy’s failure principles and Boris Cherny’s workflow.
The article analyzes the shift from single‑agent AI coding workflows to a multi‑agent collaboration model, proposing a spec‑driven orchestration framework, observable claims, and a review‑centric UI called Mexus to enable efficient parallel development, conflict resolution, and human oversight.
The article analyzes how AI coding agents are moving from answering questions to autonomously handling the entire development workflow, reshaping programmers' roles from manual implementation to defining, orchestrating, and validating tasks.
