10 beginner mistakes and how to avoid them

Everyone's first ten AI-built projects hit the same walls. Here are the mistakes we see most in the community, and the cheap way around each one. Mistake one: prompting features instead of outcomes. "Add a dashboard" produces a generic dashboard. "Show me which of my products sold best this week" produces your dashboard. Mistake two: the mega-prompt. Twenty requirements in one message means the agent satisfies twelve, and you cannot tell which. One feature per prompt, review, repeat. Mistake three: never reading the plan. Most tools explain what they are about to change. The thirty seconds it takes to skim is the cheapest bug prevention available. Mistake four: building for a week without deploying. Deploy on day one; a live URL surfaces environment problems while they are still small and keeps motivation honest. Mistake five: treating errors as failure. Errors are the agent's food. Paste them verbatim and the fix is usually one round-trip away. Mistake six: skipping version checkpoints. When (not if) an iteration goes sideways, "restore and re-prompt" beats "fix the fix of the fix". Mistake seven: polishing before anyone has used it. One real user's confusion is worth more than another evening of pixel-pushing. Ship, watch, then polish what actually needs it. The pattern behind all seven: keep the loop small. Small prompts, frequent deploys, early feedback. Vibe coding rewards rhythm over heroics.