Structure Over Intelligence: Why Most AI Code Agents Actually Fail

Most developers fail with AI code agents because they hand off vague goals instead of specific, tightly-scoped tasks—resulting in code that compiles but shatters in production when implicit decisions misalign with existing patterns. The real gap between 'occasionally helpful assistant' and 'reliable force multiplier' isn't model quality: it's how precisely you structure work before delegation. Proper task definition, explicit constraints, and comprehensive context loading are what transform AI agents from productivity drains into trustworthy development partners.