I have been using Hermes Agent extensively over the past few days, and I really like it. At the moment, I am still building the infrastructure around it so that, in the future, I can maintain it at a relatively low cost.

Over the last 20 days, I noticed that I have been consuming a large number of tokens, so I am considering getting a subscription plan to make better use of the platform. I tried Z.GLM, but through the terminal it is painfully slow. Through Telegram (I am not sure why), it is much more usable.

Would you recommend a plan suitable for moderately heavy usage where I would not have to pay strictly per token consumption? I have searched around, but pricing plans nowadays are not very transparent, and I am also concerned about whether the integration with Hermes Agent is fully supported.

I’ve been working with Hermes Agent for the past 7–10 days, and I’m honestly struggling to make my workflows stay stable over time.

I started with cloud models through Telegram integrations — first using Claude Opus, which quickly became expensive due to token usage. Then I switched to Qwen 3.6+, which worked reasonably well, and now I’m running Kimi K2.5, which seems like the best balance between speed, cost, and reliability (maybe?).

This whole setup has been a learning project for me. I bought a dedicated second-hand desktop on eBay specifically to build an AI workflow environment and to learn it, with it- after all it is the future. Before this, I was running things on a Raspberry Pi using Nanoclaw, but I decided to migrate to Hermes Agent because it felt more mature and better suited for long-term automation.

With the help of Claude web, I upgraded the GPU, adjusted BIOS settings, and built a remote-access local machine. I installed Tailscale, Cockpit, Ollama WebUI via Docker, and Hermes Agent. I connected everything to Telegram bots and cloud models through the Nous Research portal. Mind that the overall progress is real but unstable.

At first, things seemed to work perfectly.

I migrated all my bots from Nanoclaw to Hermes Agent and assigned different Telegram bots/chats to different models — some cloud-based, some local Ollama models.

Then I started building workflows.

Workflow 1: Daily Digest Feed

A Python routine would fetch information from the previous day and send categorized updates. The cloud orchestrator delegated tasks to a local Ollama model. After a full day of building, it worked well:

• Correct formatting
• Reliable summaries
• Proper links
• Minimal hallucinations
• Delivered to the right Telegram channels

By the end of the day, everything worked perfectly.

I shut down the PC.

Next morning: broken.

Something in the workflow stopped working.

I fixed it by reopening Hermes, explaining what had worked the day before, debugging with it, and rebuilding pieces. MCP, telegram id chats, workflow, something was broken but we fixed it.

Then I moved on.

Workflow 2: WhatsApp → Telegram Approval Flow

I created a system where:

• WhatsApp messages were pulled into Telegram
• Hermes summarized batches of messages
• Draft responses were generated
• I could approve/edit/reject
• Approved messages routed back to WhatsApp

Again — by the end of the day — everything worked, now the two workflows worked.

Shut down the PC.

Next morning: broken again.

Either Workflow 1, Workflow 2, or both stopped functioning correctly.

I fixed them again.

Then I built Workflow 3.

Workflow 3: Daily Token Usage Report

A scheduled report that tracked approximate token usage and sent a summary to Telegram every evening.

Worked fine, not perfect due to accuracy issue - I don't really know which numbers can't exactly match but whatever, it worked fine.

Shut down the machine.

Next day: one or more workflows broken again.

This pattern keeps repeating. I am in between jobs so I have plenty of time but it is not sustainable like this!

I’ve been trying to understand how Hermes Agent manages memory, sessions, scripts, and persistence. I save scripts in folders, name them with a specific coding, close sessions properly, explicitly tell Hermes when a task is complete, and even ask it to remember things.

But every time I reboot the machine, something degrades or breaks. Ollama is hardcoding a model that is now missing, the daily digest feed is routing to another telegram channel or not running at all, or either missing, token api usage report is using a different script. Whatsapp is answering using a model rather then routing the messages to telegram. It is hard to say the least because I cannot see an end to it and money is getting burnt everyday.

To be honest I switched every two days the cloud models, does this break things? I also updated twice over the days hermes agent.

It feels like Hermes doesn’t truly “retain” operational context between sessions — or maybe I’m misunderstanding how persistence should be handled.

So my question for experienced users:

1. Is this normal behavior?
2. Are workflows supposed to be this fragile early on?
3. Am I relying too much on session memory instead of a more permanent structure? Or in Hermes Agent altogether? Is it too dangerous to just approve every command - even if cant understand all of them?
4. How do you make Hermes setups survive reboots consistently?
5. Is there a recommended architecture for persistence, workflows, or long-term stability?

I am a geek but far from being a developer so getting my hands on code will be difficult since it is not my expertise. I was relying a lot on this new technology but maybe I got too hyped. I really like Hermes Agent and I can see the potential, but after 10 days of rebuilding the same automations over and over, it’s starting to feel just too unreliable.

Would appreciate any advice or shared experiences.

I found today another post: https://www.reddit.com/r/hermesagent/comments/1t02jis/hermes_agent_not_fun_these_days/ I will take a look at it and see if it can help me in anyway.