Four days of research, one clear lesson: distribution beats features. I thought about building my own email service, then reality hit. Here is what I did instead.

I have six live projects and a few concepts. The problem is not having ideas — it is figuring out which ones deserve more time and which ones need to evolve. Here is how I am mapping what I have built against what the market actually pays for.

After two days of research, the conclusion is clear: focus on Build Fast, Ship Fast, and Teach Fast. Here is why these three categories capture the real money in AI.

Day 2 of the build-in-public series. The framework I am using to pick what to build next, filtered through Day 1 lessons on distribution, niche, moats, and what indie builders actually ship for $10–$99/mo.

A field guide to where AI money is actually being made right now. Who is winning, who is failing, what categories of indie products print revenue, how distribution beats features, and the make-money-online plays that work beyond AI tools.

The journey from observation to algorithmic trading — how I developed custom indicators, solved problems one by one, managed trading psychology, and built a startup around trading insights without any formal training.

A practical breakdown of 1000+ Twitter insights on AI tools, frameworks, and strategies that are reshaping how solo developers and indie hackers build products in 2026.

A practical guide to building a router pattern in Claude Code that automatically assigns tasks to the best model. Route research to Gemini, frontend to Kimi, backend to GPT, reviews to Opus—and cut your costs by 40-60% while improving output quality.

A complete guide to configuring Claude Code to work with GPT-5, Gemini, DeepSeek, and other models via OpenRouter for task-specific optimization.