Formerly "Ops with Skill", now officially upgraded. Fully dedicated to AI, we share both the why (fundamental insights) and the how (practical implementation). From technical operations to breakthrough thinking, we help you understand AI's transformation and master the core abilities needed to shape the future. ShugeX: boundless exploration, skillful execution.
This article analyses a hidden flaw in OpenSpec’s review step, refactors the review instruction to four dimensions, adds a task‑granularity dimension to verify, implements a text‑summary tool, uncovers a lazy‑loading bug, and shares the lessons learned from the end‑to‑end workflow.
An analysis of five rounds of OpenSpec experiments shows that content rules in the instruction field work, but structural rules do not, and source‑code inspection reveals that the template field is the authoritative structure, explaining the failure and guiding a corrective redesign.
This article details how the OpenSpec v1.3.1 project upgraded its UI visual layer with a new color palette, icons, and animations, uncovered why AI‑generated tasks.md ignored schema instructions, fixed the issue by editing the template, and verified the changes through a full apply‑verify‑archive cycle.
In this fourth OpenSpec case study, the author refactors the home page layout by introducing a category‑based tab navigation skeleton that replaces a scrolling long list, detailing the exploration of four design options, the chosen implementation using React, TypeScript and Tailwind, and the full TDD‑driven development, testing, verification and archiving workflow.
This article walks through a complete UI/UX redesign of the OpenSpec project, detailing the exploratory audit of nine visual issues, design‑system decisions on colors, fonts and tokens, the Propose and Apply steps with concrete code changes, verification pitfalls, and lessons learned for future visual changes.
The article analyses OpenSpec’s default core workflow, explains why the five‑command core profile can feel limiting, and walks through a four‑step process to unlock six additional expanded commands, then compares three workflow modes that suit different development rhythms.
The article analyzes Karpathy’s three common LLM coding pitfalls, presents four concrete guidelines—Think Before Coding, Simplicity First, Surgical Changes, and Goal‑Driven Execution—implemented in a 65‑line Markdown file, and shows how to install and validate them across Claude Code and Cursor.
This article documents a step‑by‑step OpenSpec workflow that starts with requirement exploration, generates proposal, design, specs, review and task artifacts, executes them to scaffold a React 19 + TypeScript + Vite + Tailwind project, handles GitHub integration, validates the build, and archives the change while sharing practical lessons and pitfalls.
The article analyzes three rounds of lab experiments that reveal task‑granularity as the key lever for AI‑generated code quality, introduces the 2/8 rule, and details a three‑step configuration (config.yaml, schema fork with upgraded instruction, and review artifact) that raises quality scores to about 80% without modifying OpenSpec source code.
The article walks through three hands‑on labs—bare‑run, adding Rules + Explore + Validate, and customizing the schema with a Review artifact—to experimentally verify five quality‑upgrade directions for OpenSpec, comparing outputs, task granularity, rollback plans, testing coverage, and offering practical recommendations.
