Deterministic reflex runtime
Nothing fast stops to think.
Animals develop reflexes to survive. Athletes develop them to win. Reflexes exist because reasoning is too slow to repeat. Cerebellum records the path your agent worked out once, collapses it into a reflex, and replays it without the reasoning model.
First run · reasoning
23.0 s · 5 model calls23.0 s elapsed — one reasoning step before every tool call
Run 100 · reflex
≈ 650 ms · no reasoning steps×11 runs — one fired every 2 s here, though 35 would fit in the time the first run takes one. Same tool calls, same tool time; each thin mark is a ~30 ms round trip to Cerebellum.
Reflexes start guided, handed to your model as a plan, and graduate to executed once they have proved themselves. The lower lane is an executed reflex, which is where Cerebellum is heading; guided reflexes come first, and save tokens while the model still drives every step.
Stimulus → local reflex → propagation → collective response
No fish sees the whole school. Each one reacts to its neighbours, and the response crosses the group faster than any of them could stop to think. Switch the reflexes off to see what thinking it over costs.
How a reflex forms
Nobody writes the reflex. The work does — and you approve it.
- 01 / OBSERVE
Every run is recorded
The tools called, the order, the arguments, the outcome. A hundred runs of the same task leave a hundred traces, and the failed ones are kept too: they are what stops a bad routine becoming a reflex.
- 02 / COLLAPSE
The reasoning steps drop out
What repeats every time is kept. What only existed to decide the next step is discarded.
- 03 / REPLAY
One fixed path, run as code
Same five tool calls, no reasoning between them. When something unexpected appears, the model is called back in.
More than a lookup
What Cerebellum does that a classifier can't.
- 01
Finds the routine for you
Transcripts from every run are normalised and compared, and repeated tool sequences surface as candidates. Nobody has to notice the pattern.
- 02
A person approves it
Nothing becomes a reflex without a developer's sign-off, and every version is immutable once approved. A change is a new version and a new approval.
- 03
Earns its autonomy
A reflex starts guided, handed to your model as a plan, while its adherence and success rate are measured. Only one that proves itself is promoted to executed, where no reasoning model is involved.
- 04
Every tool call is gated
Policy is checked before any side effect, including each step of a reflex: allow, deny, modify, ask a human, escalate. Every decision is recorded with its reason.
- 05
Knows when to stop
Unexpected output, low confidence or a changed policy hands the task back to your model with the completed steps attached, so nothing runs twice.
- 06
Stays out of the model path
Your harness keeps talking to its own model and tools with its own credentials. Cerebellum is called at three points: before the task, before each tool call, and after the task.
Two paths, one stimulus
A brain doesn't think about everything.
- Reasoning
- The signal climbs into the cortex and searches for a path, one step at a time. It gets there, but slowly, and by a different route each time.
- Learned reflex
- Repetition wears a path. Once the cerebellum has learned the response, the same signal turns there and goes straight back down: no search, no pause, the same path every time.
Cerebellum in figures
- faster on the five-step example above
- ≈ 35×
- reasoning steps on the known path
- zero
- tool call checked against policy first
- every
- path, every run
- same
Illustrative, not a benchmark: the speed-up is the worked example at the top of this page.
Why give your agents reflexes
Repeated work stops costing what novel work costs
Reasoning is priced per token and per second. A reflex is priced like code.
The same input stops producing a different plan
A reflex is a fixed path. You can test it, audit it and trust it to behave the way it did yesterday.
Your models go back to doing the hard part
When routine work runs itself, frontier reasoning is spent on the exceptions that actually need it.
Security
Built to sit in front of your tools.
Your credentials stay in your harness
Tools and model steps run where they always have, with your keys. Cerebellum decides what happens next; it never holds the means to do it.
Strict tenant isolation
Every query, cache key and workflow is scoped to your organisation and project, taken from the authenticated context and never from the request.
An audit trail that cannot be edited
Approvals, policy decisions and key changes are written to an append-only log, enforced in the database itself and not only in application code.
Give your agents a cerebellum.
Keep frontier models for the work that genuinely requires frontier reasoning.