Building
Shipping software with Claude Code and agentic, spec-driven workflows — the stuff that worked and the stuff that quietly broke.
6 pieces in Building
Building collects 6 pieces published between April 2026 and June 2026. It spans AI Tools, AI Income, AI Agents, and AI Skills. All 6 are researched explainers built from primary sources rather than personal claims. The most recent is "AI Coding Assistants: How to Actually Build Faster With Them," from June 2026.
AI Coding Assistants: How to Actually Build Faster With Them
Three leading tools—GitHub Copilot, Cursor, and Claude Code—can accelerate development by 35–45%, but only when paired with rigorous code review, security discipline, and a clear workflow. Here's what the research shows and how to use them without introducing technical debt.
Read →June 3, 2026 · 6 min readAI Side Hustles: Realistic Ways to Earn on the Side With AI
A working man can leverage AI tools to build sustainable side income—not overnight wealth, but $500–$8,000 monthly with discipline. Here's what actually works, what the platforms cost, and how long it takes.
Read →May 19, 2026 · 6 min readThe Best AI Tools for a Small Business (and How to Use Them)
A practical guide to AI applications that reduce overhead, unlock new revenue, and avoid vendor lock-in—without breaking the bank or exposing customer data.
Read →May 6, 2026 · 7 min readHow to Build an AI Agent: A Practical Primer for Builders
An AI agent is an LLM-powered system that perceives its environment, plans actions, and executes tools in a loop. Here's what separates a working agent from a failed one—and how to start building.
Read →April 24, 2026 · 9 min readHow to Make Money With AI: Honest Paths That Actually Work
Five realistic ways to earn with AI tools—from productized services to building agents. What the math actually looks like, the real effort required, and which income claims are just hype.
Read →April 10, 2026 · 6 min readPrompt Engineering: A Practical Guide to Getting Better AI Output
Master the techniques that separate mediocre AI responses from genuinely useful ones—clear instructions, context, examples, role assignments, and systematic iteration. These are skills every man working with AI should develop.
Read →More Building, when it's worth sending
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