December 5, 2025
I built this site in a weekend by directing AI agents instead of writing most of the code myself. This isn't a revolutionary workflow yet—it's an experiment in how much I can focus on architecture while agents handle implementation.
I used Claude for complex logic and structural decisions, and Gemini for design feedback and UI refinement. The goal was to see if I could stay in "architect mode" and skip the usual back-and-forth with syntax.
The key was treating AI like junior developers who need clear specs. I couldn't just prompt and hope. I had to:
The bottleneck wasn't syntax anymore—it was whether I could articulate what I wanted clearly enough. When I was vague, the output was messy. When I was specific, it worked.
I acted as the architect and code reviewer. The AI acted as the implementer.
I started with a structured documentation phase: vision doc, audience doc, feature requirements, technical constraints. This gave the agents enough context to make reasonable decisions without constant correction.
For each feature, I'd describe what I wanted, review the generated code, and iterate. Sometimes the first pass was perfect. Sometimes it took three rounds to get the structure right.
Model assignments:
Built on Next.js 16, React 19, and Tailwind CSS 4, deployed on Vercel.
I chose these tools for fast deployment and minimal infrastructure management. The focus was on building features, not configuring servers.
The site is live and functional. It has a custom MDX content pipeline, theme system, and responsive design. It works.
The speed gain was real: what usually takes me weeks of nights and weekends took two days. But the tradeoff is that I had to be more deliberate upfront—loose specs produced loose code.
I built custom agents (@Researcher, @Planner, @Implementer) to orchestrate this workflow.
I'll document the agent setup and prompt patterns in the next log.