For agent & autonomy teams

Useful autonomy.
Controlled progression.

A control boundary between agent outcomes, delegated authority, experience, and live update activation.

AgentDelegationExperienceUpdateVersionRollback
Best fit
AI AgentsMulti-AgentTool UseDelegated AuthorityExperience MemoryUpdate CandidatesProduction Autonomy
Start withONE AGENT PATHOne action · delegation · or update candidate
2-minute review · concrete example

Agent proposes a new routing rule

Not a theory page. Watch one outcome become—or not become—a live update.

01 · Observe
RECURRING FAILURE
Support cases routed badly
Agent detects a pattern
02 · Agent
NEW RULE
Auto-route similar cases
Update candidate proposed
03 · Evidence
WORKED BEFORE
Success ≠ permission
Positive outcome evidence exists
04 · LimFlex
HOLD
Applicability? Authority? Rollback?
DO NOT ACTIVATE YET
05 · Validate
N+1
Validated Update Candidate
Conditions · scope · expiry · rollback
06 · Host
ACTIVATE
Versioned · bounded
Host governance layer activates
07 · Runtime
MONITOR
Expire · invalidate · rollback
OUTCOME ≠ LIVE RULE
1 / 7
Why LimFlex
Outcome
Update Candidate
Experience
Conditional Experience
Delegation
Bounded Authority
Update
Versioned Activation
How it plugs in
Agent Runtime
Action / Update Candidate
LimFlex Control API
Host Orchestrator / Governance
Outcome → Governed Update Candidate
Integration image
const result = await limflex.evaluateUpdate({
  candidate,
  outcomeEvidence,
  delegatedAuthority,
  applicability,
  rollback
});

if (result.state === "ACTIVATE") {
  await host.activate(result.version);
}

Example response
{
  "state": "HOLD",
  "missing": ["rollback_condition"],
  "candidate_version": "N+1",
  "next": "validate"
}
PositionControl planeAbove agent progression
BoundaryBefore live activationAction · delegation · update
Commercial entryOne agent pathAction, delegation, or update sequence
Details · closed by default

Open only what you need.

What “conditional experience” means here
  • Past outcomes may inform later control
  • Applicability conditions remain explicit
  • Non-applicability and expiry may remain explicit
  • Experience does not automatically become a universal rule
What a first evaluation needs
  • One agent action, delegation, or update path
  • Current authority owner
  • Available non-confidential outcome evidence
  • Activation condition
  • Rollback, expiry, or Human Gate condition
What this public page does not claim
  • Unrestricted recursive self-improvement
  • Automatic self-modification of model weights
  • Replacement of the agent runtime or orchestrator
  • Production validation unless specifically documented
Useful contact vocabulary

“Can this sit between agent outcome and update activation?”

update candidatedelegated authorityconditional experienceversion activationrollback