Agents
Interesting insights, especially this: Hermes starts off as any other agent does, inefficient and often not sure how to complete a task that…
Interesting insights, especially this: Hermes starts off as any other agent does, inefficient and often not sure how to complete a task that is training didnt have priors for. However, solve it once a
Interesting insights, especially this: Hermes starts off as any other agent does, inefficient and often not sure how to complete a task that is training didnt have priors for. However, solve it once and you unlock huge efficiency gains. I sometimes call this linearized RL, coming from a post training backround, where you would run a task dozens of times, and determine which runs won, and then train on it, this is strong parallels, but in one agent loop, and obviously, learned at test time, and locked in through skills and in context learning, rather than through weight updates.
Related
- Hermes Agent is an overnight success nine months in the making
- Hermes Agent is good. What makes it impressive is how performant it is with even small or locally hosted models. This used to be stuff that …
- Thank you for helping to make Hermes Agent amazing.
- Hermes Agent Tip💡 Hermes supports dedicated auxiliary models for eight task types: 1. vision 2. web_extract 3. compression 4. session_searc…
Source: Nous Research (X) | 2026-04-19