What Building AI Projects Taught Me Beyond the Prototype

<p><em>This is a submission for the <a href="https://dev.to/challenges/google-gemma-2026-05-06">Gemma 4 Challenge: Write About Gemma 4</a></em></p> <h3> Why I Wrote This </h3>

<h1> "SaaSpocalypse"? Real. "SaaS Is Dead"? SaaSinine. </h1> <p><strong>$300 billion vanished from software stocks in a week. The market is panicking about the wrong

<p>When we were given our project, CourierIQ, I knew I wanted to use it as an opportunity to learn something outside what I was already comfortable with.</p> <p>I was already more

<h2> From "Prove It in Code" to "Prove It in Judgment" </h2> <p>For decades, credibility in software came from what you built with your own hands. Writing robust systems required

<p>If you’ve been learning programming for a while and still feel stuck, you are not alone.</p> <p>Most beginners don’t fail because coding is too hard.</p> <p>They fail because

<p>Let's be real: the current AI coding workflow is tedious. </p> <p>You hit a bug. You copy your code. You tab out to ChatGPT/Claude. You paste it. You copy the fix. You paste it

<p>Over the past year I shipped four things mostly solo: spectr-ai (an AI smart-contract auditor), Scry (chat with any EVM contract), Argus (a transaction-firewall extension), and

<p>A game called Pathogenic launched on July 16. It's a roguelike where you play as a parasite inside the human body. By launch day, I had a full wiki for it live: guides,