Why do AI models perfectly understand instructions but then completely forget to wait for your feedback? In this post we will discuss adding more determinism to an AI-assisted project and how that can quickly tun into an over-engineered mess.
Tired of hitting token limits while web scraping with AI? Discover how I hacked the Playwright MCP server to slash token usage by 67% when scraping LinkedIn profiles, turning a frustrating workflow killer into a smooth AI-assisted briefing tool.
Complex codebases kill simplicity. When CMSes abandon documentation-as-code approaches, they create unmaintainable monsters. What's the solution? Enforce minimum viable complexity by treating content as living documentation - if you can't explain your workflow in markdown, it's too complex to continue with code.
Every CMS forces content creators to manipulate layout builders without ever declaring what they're trying to communicate. Just like "program to the interface, not the implementation," content management should capture intent first, then let AI assistants handle the visual details through collaborative design conversations.
Most open source content management systems claim no vendor lock in, but is that true? How can we ensure that you will still succeed when the system is down or you want to move on?