A year or two ago, if an AI feature wasn't performing well, teams often tried a better model, but today's frontier models are so capable that the model itself is no longer the biggest obstacle for most production applications. The real challenges begin after choosing the model, shifting from tweaking prompts to securing permissions, managing memory, controlling costs, investigating unexpected behaviour, and understanding an agent's decisions. A key security risk is prompt injection, where language models treat instructions and data as plain text and cannot naturally distinguish a user's legitimate request from malicious instructions hidden in content like webpages, emails, PDF documents, support tickets, shared documents, or external Slack messages. This risk cannot be solved with a stronger system prompt; the real defence comes from system design: treat all external content as untrusted data, restrict available tools, validate every high-risk action, and apply the principle of least privilege so that even if the model is tricked, it cannot perform harmful actions.