AI tools like Claude Code are displacing junior developers by handling boilerplate and basic tasks, while simultaneously flooding codebases with unoptimized, context-unaware code. Companies now seek senior engineers to clean up AI-generated messes. Using a real-world AWS SQS event ordering problem as a case study, the author demonstrates how a mid-level developer blindly accepted an AI-suggested Postgres advisory lock solution — ignoring architecture guidelines and a better alternative (SQS FIFO queues with deduplication IDs). The core advice: use AI to explore problem space and architectural alternatives, not to generate final code. Developers who own the decision-making and can explain every line of code will remain valuable; those who copy-paste AI output without understanding it will not.