Self-reported logs are not enough
Dashboards and internal audit trails help operators, but a serious reviewer needs evidence that can survive outside the system being challenged.
Evidence independenceG‑14 Research
Research for proof-carrying agentic control.
G‑14 research starts from one evidence problem: when autonomous AI action, communication, or scientific reconstruction is challenged, the reviewer needs more than the system account of what happened.
ProceedRepairRejectWitnessReceiptVerify
Research thesis Evidence boundary
Communication can be certifiable
When agent collectives reconstruct evidence or exchange scientific claims, the communication path needs proceed, repair, reject, and witness states.
Semantic receiptsAction is the compliance boundary
Tool calls, data writes, deployments, robot commands, workflow approvals, and scientific reliance need evidence at runtime, not only after-the-fact review.
Runtime admissionPhysical AI is one proof point
TargetLock applies the pattern to robot action. The same external control model generalizes to enterprise action and agent-derived conclusions.
General thesisFoundations
Certifiable agent communication is the same control problem in another domain.
TargetLock gates physical action. The research path generalizes the same architecture to agent collectives reconstructing evidence, exchanging scientific claims, and deciding when to proceed, repair, or reject with a witness.
Dashboards and internal audit trails help operators, but a serious reviewer needs evidence that can survive outside the system being challenged.
Evidence independenceWhen agent collectives reconstruct evidence or exchange scientific claims, the communication path needs proceed, repair, reject, and witness states.
Semantic receiptsTool calls, data writes, deployments, robot commands, workflow approvals, and scientific reliance need evidence at runtime, not only after-the-fact review.
Runtime admissionTargetLock applies the pattern to robot action. The same external control model generalizes to enterprise action and agent-derived conclusions.
General thesisWorking thesisBetter dashboards do not solve a broken evidence channel.
Read docs path The verifier should bind the proposal, evidence, repair path, decision, and outcome boundary.
The record has to be useful to customers, auditors, insurers, regulators, operators, and incident responders.
G‑14 language should state what a packet supports and what it does not certify.
Agentic systems now call APIs, write data, trigger workflows, move machines, and shape scientific reliance.
Public outputs
The public result is a clearer evidence standard.
The site should make the category legible without exposing protected internals or naming pending proposals. The standard is proof-carrying verification for consequential AI.
Evaluation path
Use the research to evaluate one proof-bearing workflow.
Start with the evidence problem, inspect the proof model, then choose one action or communication path where a receipt has to survive outside the UI.