01What Hermes Agent 5X Faster Update Is and How It Works

The Hermes Agent 5X faster update introduces a new method called segmented tool batch dispatch. This change makes your agent swarms run parallel tool calls much faster. Before, Hermes would only run tool calls in parallel if every single call in the batch was safe to run together.

If any one call was risky, the whole batch slowed down to one-at-a-time mode. Now, each tool call is checked individually. Safe calls fire at the same instant.

The few calls that must wait are held back. The results from all calls are merged later. This gives you a major speed boost without breaking anything.

02Main Features of the Hermes Agent Speed Update

This update has three big features. First, segmented tool batch dispatch lets multiple tool calls run at the same time as long as they don't conflict. Reading a file does not interfere with another read, so both go in parallel.

Second, the system automatically identifies which calls are safe. A read is safe. A write that the next step depends on is not.

Third, the update gives you up to a 5X speed increase compared to the old one-at-a-time approach. You can ask your agent to handle five independent jobs – like checking a calendar, reading three files, and pulling fresh data – and all of them can start in the same second. Only the job that must wait holds, so you get the list done in a fraction of the time.

03How to Get Started with the Hermes Agent Update

  1. Open your terminal or command line interface.
  2. Run the command: Hermes update to download the latest version of Hermes.
  3. Restart your Hermes agent service to apply the update.
  4. Verify the update by checking the version number or running a simple parallel test with two independent tool calls (e.g., read two different files).
  5. If you use free local models, make sure your model is compatible – most modern local agentic models work fine.
  6. Start using your agent swarms as before; the speed improvement happens automatically on safe parallel tool calls.

04How to Use the New Parallel Tool Dispatch in Hermes

To use this update, simply give your agent a task that involves multiple independent tool calls. For example, you can ask it to read a file, search the web, fetch a URL, check a calendar, and list directory contents all in one request. The agent will examine each tool call.

Every call that is safe triggers at the same moment. The one call that depends on a previous result is held until the others finish. All results merge into a single output.

In the episode, Julian showed an example where a Hermes agent called Hermes Oracle pulls trending Twitter news, sorts it by popularity, and publishes content to a website. That workflow uses many tool calls. With the old system, even one slow call would force the whole batch to run one by one.

Now, all independent calls run together, so content gets drafted and posted much faster.

05Results and Speed Comparisons from the Episode

In the episode, Julian explained the speed difference with a simple example. If each tool call takes two seconds, the old one-at-a-time method would need 10 seconds for five tasks. The new parallel system can finish all five tasks in about two seconds, because all five start at the same time.

That is a 5X speedup for that batch. Real tool calls may be slower or faster, but the proportional gain remains similar. Julian also showed a Kanban board inside the agent OS where multiple agent workflows run concurrently.

Because no single risky call blocks the whole swarm, tasks loop around quicker, and you get more work shipped in the same amount of time. The update does not change the final results – it just makes the wait much shorter.

06Tips, Limits and Mistakes to Avoid with Hermes Agent

Do not assume every call can run in parallel. Calls that write data that another call depends on must still wait. The system handles that automatically, but you should structure your agent prompts to keep independent tasks separate.

For example, combine read-only requests together and put write operations after. Another tip: token usage may increase if you run many parallel calls, but you can use the token minimization playbook from the AI Profitable Boardroom to reduce costs. Hermes also offers many free models that work with this update, so you can test speed gains without spending money.

A common mistake is to keep using the old one-at-a-time flows out of habit. Update your agent scripts to take advantage of batch dispatch. Finally, if you wait to start learning agents until this update is stable, you fall behind – people already building with Hermes improve daily.

07Who Should Use the 5X Faster Hermes Agent Update

This update is for anyone who builds AI agent swarms that rely on multiple tool calls. If you use agents for research, file editing, lookups, report generation, or content publishing, you will see a big speed gain. Julian mentioned that multi-step jobs make up most of what an agent actually does.

Cutting the wait on every step changes the whole feel of working with an agent. Beginners can start with free local models. Advanced users can integrate the update into their existing production pipelines.

The faster agent response makes you more productive and lets you ship more features. As agent technology moves quickly, using this update now keeps you competitive against others who adopt slower methods.

08How Segmented Tool Batch Dispatch Changes Agent Workflows

The core idea behind segmented tool batch dispatch is that a batch of tool calls is split into safe and risky groups. Safe calls – like reading a file, fetching a URL, or checking a list – fire all at once. Risky calls – like writing a file that later steps need – are held back until the safe ones finish.

Then all results merge. In the episode, Julian described an example with five jobs: check calendar, read three files, and pull latest information. None depend on each other, so all five fire simultaneously.

The only thing that must wait is a task that changes something the others are counting on. This system makes the agent way faster and way more efficient. It works inside the agent OS Kanban board, where multiple agent profiles and workflows run together without one slow call blocking the whole system.