The fastest Hermes agent is the one that reads less.
I didn’t make Hermes 10x faster by changing the model.
I made it faster by removing the tax I was charging it on every task:
bad structure.
Hermes was powerful already.
The problem was that I had built my workspace for a human brain, then expected an agent to navigate it like it had memory, taste, and intuition.
It doesn’t.
It searches.
And when your files are arranged by how you think, not how the agent moves, Hermes burns tokens opening the wrong docs before the real work even starts.
That was my mistake.
I had folders like:
Articles
Research
Assets
Strategy
Old drafts
Clean for me.
Terrible for an agent.
A launch plan might need brand strategy, previous launches, voice rules, current articles, and promotion notes.
For me, that context is obvious.
For Hermes, it was scattered.
So I stopped optimizing the model and started optimizing the terrain.
The fix was stupidly small:
One folder per concern
Numbered folders for reading order
One INDEX.md at the root of every major folder
Archived files separated from active files
A clear “Where To Go” section so Hermes knows where to start
My INDEX.md became the map.
Not a giant table of everything.
Not documentation theater.
Just enough scaffolding to tell Hermes:
what exists
what matters
what is current
where to start
what to ignore unless asked
Before that, Hermes opened 7 files to find one current brief.
After that, it opened the index, followed the pointer, and got to work.
That is the real 10x.
Not “better prompting.”
Less wandering.
This is where loop engineering actually matters.
The video said it best:
“You were the loop.”
That line hit because it explains why most agent workflows still feel manual.
You are still checking.
You are still redirecting.
You are still telling the agent which file is current, which folder matters, and what done means.
Hermes gets powerful when you stop being the loop and start designing the loop.
The loop I’d build looks like this:
State: Hermes reads the folder index and current task state
Action: it opens only the canonical files
Feedback: tests, screenshots, diffs, or human notes tell it what happened
Verification: a gate decides whether the work is actually done
Termination: the task stops only when the done condition is met
For deterministic work, the gate is simple:
tests pass
build succeeds
deployment checks clear
For non-deterministic work, I’d use an adversarial loop:
one model builds
another model reviews
Hermes updates the skill when the reviewer finds a pattern
That is where Hermes becomes different.
It is not just running prompts.
It is carrying memory through files, using skills, checking its own work, and improving the process around the task.
The agent was never the slow part.
The missing map was.
A powerful agent inside a messy workspace becomes a very expensive intern.
A powerful agent inside a mapped system becomes leverage.
My new rule:
Before I ask Hermes to do more, I ask:
“Does it know where to look?”
Because most agents do not fail from lack of intelligence.
They fail from lack of scaffolding.
Build the scaffolding.
Let Hermes do the work.