LLMs as Tools, Not Replacements: Why Software Teams Need Guardrails

While LLMs show promise for hobbyists and low-stakes projects, the industry lacks established practices for safely deploying them in large teams and critical systems. The author argues that unchecked AI-assisted code generation poses real risks—from production database corruption to code shipping without proper review—and that sustainable adoption requires clear boundaries and oversight. This tension between AI's apparent productivity gains and engineering discipline will likely define how the tech industry matures its relationship with generative AI.