Guardian Angels: LLM Personalization for Productivity and Security

Powerful LLMs will be deployed at global scale in the next few years, and will dominate the Internet, and increasingly, ordinary life. As of mid-2026, there is no coherent vision for how knowledge professionals, or ordinary people, will be able to harness these LLMs for large productivity increases, or how they will handle cybersecurity and cognitive security. I propose a goal of creating Guardian Angels (GA): digital twin LLMs which are personalized with the goal of providing not the stereotypical "assistant chatbot agent" persona, but emulating a single user's personality, values, and preferences. This weakly solves the principal-agent problem by unifying the principal and agent as much as possible. In a GA future, the focus of the "principal" user is on defining what is worth doing by the GA (agent) users, and not on what or how to do things, functioning as the CEO or 'board' of an 'AI corporation'. This allows them to deploy numerous agents to achieve desirable things and to handle security, like screening all messages for advanced attacks (like interlocking ecosystems of synthetic media for propaganda or spearphishing). They cannot solve larger AI alignment problems, but they can help individual humans as part of a society-wide defense-in-depth strategy. A GA persona is productive because it learns to emulate the principal's outputs but with higher quality. It is trustworthy because it is, by definition, allied with its principal and shares its values and goals. And it is secure in part by hardwiring a single, unique, situated user (for whom following a prompt attack would be absurd), avoiding 'confused deputy' problems, while periodic upgrades of the underlying model and the defenders' advantage allow GAs to keep up with attackers. Standard techniques like prompt programming of in-context-learning for "frozen" models will not create useful GAs due to the limitations of post-training, context windows and self-attention with frozen weights in compute-efficient-b