The author of this text is sharing their experience and lessons learned while building GraphQL servers. They started by discussing the importance of optimizing human time, not machine time, and realized that premature optimization can lead to hard-to-maintain code. Instead, they focused on choosing the right abstractions, including models and connectors, which helped structure their code in a more maintainable way. The author also emphasized the need to measure performance twice before making any optimizations, as different factors come into play at scale. They developed a custom GraphQL tracer tool to help identify bottlenecks and performance issues in their server. By sharing these insights, the author aims to help others avoid common obstacles when building GraphQL servers.