Design Hermes as a Self-Improving AI Employee

Hermes is designed to become more useful as it works with a specific person or organization. Its value comes not only from completing a task, but from capturing what was learned about the task and reusing that learning later.

This creates a self-improvement loop. When Hermes discovers how a user edits videos, writes in a preferred tone, evaluates apartments, prepares a briefing, or performs another repeated process, it can save that process as a reusable skill. Corrections can also become part of the learned procedure, allowing future executions to reflect the improved method.

The loop has five practical stages:

1. The user assigns a task.
2. Hermes performs the task with the available model, tools, context, and permissions.
3. The result exposes a useful pattern, a better method, or a correction from the user.
4. Hermes records the reusable procedure as a skill or updates relevant memory.
5. A later task invokes the improved procedure instead of starting from zero.

The system also includes curation rather than indiscriminate accumulation. During ongoing interaction, Hermes periodically evaluates what it has learned. A curator process can clean up old skills, improve them, and archive material that is no longer useful. This matters because a system that stores everything without maintenance becomes noisy, contradictory, and difficult to use.

The apartment-search example illustrates the difference. After observing a preference for high-rise apartments within a particular budget, Hermes can surface similar options in later searches without requiring the same preference to be restated. The useful outcome is not merely remembering a sentence. It is applying an inferred working preference to a future task.

A generic chatbot repeatedly pays the cost of re-explanation. A self-improving agent compounds experience. The more often a stable workflow is performed and corrected, the more precisely the agent can match the user's way of working.

This is especially important for tasks whose quality depends on style and judgment rather than a single factual answer. Writing tone, content formats, editing conventions, project-update habits, meeting-preparation preferences, and visual standards become more valuable when they can be reused.

The self-improvement loop also changes the user's role. The user is not only issuing commands. The user is training an operating relationship through examples, corrections, and approval decisions.

When Hermes completes a process successfully, explicitly ask it to turn the process into a skill. The best candidates have three characteristics:

1. The task will recur.
2. The sequence is stable even when the input changes.
3. The output has reached a quality level worth preserving.

A morning briefing is a strong example. The underlying information changes every day, but the procedure remains consistent: inspect the calendar, identify urgent email, summarize team activity, collect relevant documents, note preparation tasks, and deliver a concise report through the preferred channel. Once the format is refined, the procedure can be packaged as a skill and attached to a cron job.

Corrections should be concrete. Instead of saying only that an output is bad, specify what should change: lead with the answer, remove long explanations, include links to drafts, use a particular carousel layout, or place B-roll above the on-camera subject. Concrete correction gives Hermes material that can be incorporated into the reusable procedure.

Periodically inspect the skill library. Keep procedures that are current, improve procedures that are almost correct, and archive workflows that no longer reflect the way work is done.

Self-improvement is only as useful as the signals it receives. If the user accepts weak work without correction, the learned procedure may preserve weak work. If preferences change, old procedures must be updated or archived. A large skill library is manageable because Hermes uses an index to find relevant skills, but the contents still need coherent names and purposes.

Self-improvement also does not remove human responsibility. A learned process can make an error more repeatable if it is automated before it is validated.

Use every successful task and every correction as training material, then convert stable, validated procedures into reusable skills that compound over time.