Video: "Build & Automate ANYTHING With Hermes Agent" by Julian Goldie on YouTube.
The use cases that actually hold up
Hermes Agent handles repetitive, structured work well. Summarising long documents or email threads is one area where it is consistently useful — give it a clear goal and a long context window and it produces decent output with minimal prompting. Managing recurring tasks (daily research summaries, scheduled data pulls, monitoring a set of URLs for changes) is another solid area because Hermes's goal-locking feature keeps it on task without needing a nudge at each step.
Website builds are more mixed. Hermes can coordinate a multi-agent swarm where one agent plans the site structure, another writes the copy, a third generates the HTML, and a fourth reviews it. The output is workable for simple brochure sites. For anything requiring specific brand decisions, technical precision, or performance considerations, you need a human reviewing before anything goes live.
App building without any development background is possible in the way that assembling flat-pack furniture is possible: Hermes will work through the steps, but if you do not understand what it is producing you will have no idea whether it is right or broken until someone tries to use it. The tool is better positioned as a co-pilot for a developer than as a replacement for one.
What the persistent memory and goal-locking actually change
The feature that separates Hermes from most agent tools is not the swarm capability — it is the combination of persistent memory and /goal locking. Persistent memory means Hermes stores what it learns in a skill file it references on future runs. The first time you ask it to write a certain kind of report it is slow and rough. The fifth time it is noticeably faster and more accurate because it is not starting from scratch.
Goal locking (/goal command in v0.13) keeps the agent working on a target until it is done rather than stopping and asking what to do next. For a task like building a fifty-page site or completing a keyword cluster, that means you can set it running before you leave for the day and come back to something finished rather than something half-done and waiting for input. That matters practically — the difference between an AI that runs while you sleep and one that stops after ten minutes is significant if you are using it for real work.
The inbox and messaging integrations
One area Goldie covers that does not get enough attention is Hermes running inside Telegram and Discord. Rather than opening a separate interface, you message the agent in an app you already have open. Ask it to summarise yesterday's emails, pull information from a site, or draft a reply — all through a chat window. For small teams that live in messaging apps, this framing is more practical than a browser dashboard.
In practice the integration is reasonably smooth once it is configured. The main friction is the initial setup, which requires some comfort with API keys and configuration files. Once it is running it is close to invisible — you ask, it does, you get back an answer. Not quite there yet for a non-technical person setting it up independently, but fine for a team with one person who can configure things.
Where to be careful
Hermes does not know when it is wrong. That is the honest answer to the question of what it cannot do. It will produce confident-sounding output for tasks it is not equipped for — code that does not run, copy that misses the brief, plans based on incorrect assumptions. The self-improving skill loop helps over time but it cannot fix a fundamentally bad first attempt on its own.
The other thing to watch: the skill library grows. If you use Hermes across many different task types without occasionally reviewing what it has stored, you end up with a library full of noise that slows it down and introduces drift. A focused agent with a clean, relevant skill set performs better than a cluttered general-purpose one. Worth spending twenty minutes every couple of weeks reviewing what it has written about itself.
Where this connects to NordSys
We set up and configure Hermes Agent for clients — including getting the right model in place, building a clean skill library around your specific workflows, and making sure goal-locking is configured sensibly before it starts running on anything consequential. If the 'automate anything' framing sounds appealing but you want an honest conversation about what it will and will not do for your particular situation, our AI Agents service is the right place to start.
See our AI Agents service →