10 articles exploring claude code
Production AI systems are 98% harness, 2% model. New research reveals why architecture, permissions, and safety matter more than model capability - and how to build systems that actually work.
AI writes 80% of my code. I still review 100% of these 5 file types. A blast-radius framework ranking what to review line-by-line, and what to trust.
Smaller, constrained AI models force clarity and structure. I build faster with Haiku than Opus because constraints eliminate bad habits. Here's why.
Most AI coding tool comparisons still reward the wrong things. A workflow-first breakdown of Claude Code, Cursor, Copilot, Windsurf, and Antigravity through the lens that actually matters: how teams ship under real constraints.
AI-generated code feels fast, but the maintenance cost appears later. Why AI creates locally correct but globally fragile systems, and the engineering standards that fix it.
Why one-off prompting does not compound, and how to move from isolated prompts to repeatable AI workflows using playbooks, MCP data sources, and action layers.
A practical blueprint for structuring Claude Code projects so they stay predictable as they grow. From folder layout and .claudeignore to prompts, skills, and AI-friendly component patterns.
The MCP servers that matter most for real AI leverage: analytics, email, calendar, GitHub, databases, observability, SEO, social, docs, and file storage. Plus practical playbooks for turning them into repeatable workflows.
The 10 Claude Code skills that now separate developers who merely generate from those who ship differentiated products. From UI taste and frontend structure to brand systems and skill creation.
16 concrete strategies to reduce token consumption by 60–90% while keeping Opus and Sonnet actively predicting. From .claudeignore to multi-agent architectures.