# Production Readiness Report — First Agent Supervisor Chain (L3)

**Proof ID:** `first-agent-supervisor-chain`
**Subject:** Three-level *sequential* supervision is reconstructable from signed canonical events. The risk agent's authority traces THROUGH the reviewer THROUGH the human to root — agent-to-agent supervision encoded in the canonical event log itself. Each actor has a distinct narrow envelope; `approve_transfer` is held only by the human; the AI Risk Agent cannot delegate further.
**Date:** 2026-06-02
**Determination:** PROVEN IN OPERATION (scope: one root → human → AI Reviewer → AI Risk Agent supervision chain, three distinct envelopes, human-only final approval, leaf-node risk agent)
**Version:** 1.0 (Final)

---

## Strict wording

This is L3 — *Agent Supervisor Chain* — the first proof of true sequential agent supervision in the canonical event log. Proof #7 (L2) demonstrated a single bounded agent under a human. **This proof advances to L3 by adding a second AI principal that is delegated by — and operating under — the first AI principal, not in parallel.** The chain is `root → human → AI Reviewer → AI Risk Agent`, four levels deep with root, three delegation hops. The replay engine's `trace_provenance` walks every hop. Each principal carries a distinct, narrow envelope.

This is not multi-agent. This is not agent workflow. This is **agent supervision** — agents managing agents — proven in the canonical event log.

---

## Three claims (the 10-second read)

1. **Sequential agent-to-agent delegation is in signed canonical events** — the AI Risk Agent's `granted_by` is the AI Reviewer, not the human, not the root.
2. **Each actor has a distinct narrow envelope and approval authority is concentrated in the human** — `approve_transfer` is held by exactly one principal.
3. **The AI Risk Agent is a leaf — it cannot delegate further** — its scope contains no `delegate_*` capability, asserted by hard test failure if leaked.

---

## 01 — Problem

Real agentic workflows are not single agents under a human. They are *chains* — a senior agent supervises subordinate agents, which in turn supervise sub-sub-agents, all within bounds set by the human. Every layer must be auditable. A regulator asking "show me the chain that processed this transfer" must be able to reconstruct not only *who acted* but *who delegated their authority*, *what envelope each actor had*, *what they were forbidden to do*, and *why each was allowed to participate at all*.

L2 (Proof #7) proved a single bounded agent. **L3 proves that authority can be passed through multiple delegation hops without the chain breaking, without scope leaking, and without the human losing approval authority.**

---

## 02 — Environment

| Component | Detail |
|---|---|
| Reconstruction harness | `tests/agent_supervisor_chain_001.rs` in `scif-backend` at SHA `2d6ca36e7` |
| Storage | `PostgresEventLogSource` against `h33_production.canonical_auth_events` |
| Replay | `h33_xeon_api::agent_zero::astate_replay::replay_until` — `trace_provenance` walks the full 3-hop chain |
| Signing | Production PQ keys at `h33/production/canonical-event-signer` |

---

## 03 — Identity (four-level supervision chain)

| Level | Principal | Role |
|---|---|---|
| 0 — Tenant root | `princ_root_supervisor_chain_44962d9b-…` | issues the human's grant |
| 1 — Human Supervisor | `princ_customer_9` | sole holder of `approve_transfer` |
| 2 — AI Reviewer | `princ_ai_reviewer_001` | reviews + invokes the risk agent |
| 3 — AI Risk Agent | `princ_ai_risk_agent_001` | classifies and scores risk (leaf) |

---

## 04 — The supervision chain (three grants, sequential)

### Human's grant (root → human)

| Field | Value |
|---|---|
| `authority_id` | `auth_44962d9b-…_supervisor_chain` |
| `granted_by` | `princ_root_supervisor_chain_44962d9b-…` |
| `granted_to` | `princ_customer_9` |
| `scope` | `["approve_transfer", "revoke_agent_authority", "grant_agent_authority"]` |
| `policy_basis` | `pol_supervisor_chain_v1` |

### AI Reviewer's grant (human → AI Reviewer)

| Field | Value |
|---|---|
| `authority_id` | `auth_44962d9b-…_reviewer_chain` |
| `granted_by` | **`princ_customer_9`** |
| `granted_to` | `princ_ai_reviewer_001` |
| `scope` | `["review_transfer_request", "request_risk_analysis"]` |
| Cannot | `approve_transfer`, `move_assets` |
| `policy_basis` | `pol_ai_reviewer_chain_v1` |

### AI Risk Agent's grant (AI Reviewer → AI Risk Agent)

| Field | Value |
|---|---|
| `authority_id` | `auth_44962d9b-…_risk_agent_chain` |
| `granted_by` | **`princ_ai_reviewer_001`** |
| `granted_to` | `princ_ai_risk_agent_001` |
| `scope` | `["classify_risk", "score_risk"]` |
| Cannot | `approve_transfer`, `move_assets`, `delegate_authority`, `review_transfer_request` |
| `policy_basis` | `pol_ai_risk_agent_chain_v1` |

The Risk Agent's `granted_by` is the AI Reviewer — an *agent*, not a human. `trace_provenance` walks: Risk Agent grant → finds Reviewer's grant whose `granted_to == princ_ai_reviewer_001` → walks the Reviewer's grant → finds human's grant whose `granted_to == princ_customer_9` → terminates at root.

---

## 05 — Replay (the reconstructed state)

```
state_id = 5aefda52359ce9d93f6264780bcc95048fbb7483250063a9c7f8265daca5026d
```

Byte-identical across two runs. `snapshot.verify_state_id()` = `true`. Verdict `Valid`, 3 active grants, 0 excluded.

**Per-authority explanations** (the *why* each actor participated):

```text
human    → "Granted by princ_root_supervisor_chain_44962d9b-… to princ_customer_9;
            policy pol_supervisor_chain_v1; chain to root verified."
reviewer → "Granted by princ_customer_9 to princ_ai_reviewer_001;
            policy pol_ai_reviewer_chain_v1; chain to root verified."
risk     → "Granted by princ_ai_reviewer_001 to princ_ai_risk_agent_001;
            policy pol_ai_risk_agent_chain_v1; chain to root verified."
```

The risk agent's explanation **names the AI Reviewer as its grantor** — agent-to-agent supervision is forensically explicit, not implicit.

---

## 06 — The supervision invariants (asserted with hard failure messages)

| Invariant | Result |
|---|---|
| `approve_transfer` held by exactly ONE principal (the human) | ✓ TRUE |
| AI Risk Agent's `granted_by` = AI Reviewer (agent-to-agent in event log) | ✓ TRUE |
| AI Risk Agent's scope contains NO `delegate_*` capability | ✓ TRUE |
| AI Reviewer's scope does NOT contain `approve_transfer` or `move_assets` | ✓ TRUE |
| AI Risk Agent's scope does NOT contain `approve_transfer`, `move_assets`, `delegate_authority`, or `review_transfer_request` | ✓ TRUE |
| Determinism r1.state_id == r2.state_id | ✓ TRUE |

Hard failure messages baked into the test:

```text
FINAL-AUTHORITY FAILURE: approve_transfer must be held by exactly one principal (the human)
REVIEWER ENVELOPE FAILURE (leaked): `Y` MUST be outside reviewer envelope
RISK ENVELOPE FAILURE (leaked): `Y` MUST be outside risk-agent envelope
```

---

## 07 — The regulator's seven facts (answered by reconstruction)

| # | Question | Reconstructed answer |
|---|---|---|
| 1 | Who reviewed? | `princ_ai_reviewer_001` |
| 2 | Why were they allowed to review? | Granted by `princ_customer_9` under `pol_ai_reviewer_chain_v1`; chain to root verified |
| 3 | Who scored risk? | `princ_ai_risk_agent_001` |
| 4 | Why were they allowed to score risk? | Granted by `princ_ai_reviewer_001` under `pol_ai_risk_agent_chain_v1`; chain to root verified |
| 5 | Who approved? | `princ_customer_9` |
| 6 | Why were they allowed to approve? | Granted by tenant root under `pol_supervisor_chain_v1`; chain to root verified |
| 7 | What policies governed each actor? | `pol_supervisor_chain_v1` · `pol_ai_reviewer_chain_v1` · `pol_ai_risk_agent_chain_v1` |

All seven derive from the replay output — `granted_to` + `scope` + `policy_basis` + the `trace_provenance`-walked chain — and they appear in the reconstruction artifact's `regulator_seven_facts` field.

---

## 08 — Known limitations

1. **Reconstruction-only, not live multi-agent execution.** No live agentic workflow has actually invoked through this chain end-to-end. This proof guarantees the supervision chain is *correct* and *replayable*, not that *every endpoint enforces it at request time*.
2. **Three levels of delegation, not arbitrary depth.** Real production agent trees may be deeper (root → human → coordinator → reviewer → risk → compliance → sub-agents). The `trace_provenance` engine supports up to 64 hops. L4 (next proof) generalizes this into arbitrary-depth tenant-scoped agent graphs.
3. **No search/sort over the agent graph.** L3 reconstructs a single chain. L4 will add the ability to query the graph (find all agents under principal X, find all leaf agents, find all agents with capability Y).
4. **No PQ signature verification at replay ingestion** (Phase E lock; same as all current proofs).
5. **Tenant isolation is per-tenant; cross-tenant supervision is not modeled.** This proof exercises one tenant; the multi-tenant isolation proof (#3) demonstrates the boundary holds.

---

## 09 — Evidence appendix

| Field | Value |
|---|---|
| `state_id` | `5aefda52359ce9d93f6264780bcc95048fbb7483250063a9c7f8265daca5026d` |
| Replay-until T (ms) | `1800000000000` |
| Tenant ID | `tenant_supervisor_chain_44962d9b-25f5-5622-bd9a-98d5580bb8a2` |
| Tenant root | `princ_root_supervisor_chain_44962d9b-…` |
| Human Supervisor | `princ_customer_9` |
| AI Reviewer | `princ_ai_reviewer_001` |
| AI Risk Agent (leaf) | `princ_ai_risk_agent_001` |
| Chain depth (with root) | 4 |
| Agent-to-agent delegation hops | 1 (Reviewer → Risk Agent) |
| Sole holder of `approve_transfer` | `princ_customer_9` |
| Reconstruction artifact | [`reconstruction.json`](reconstruction.json) |
| Harness | `tests/agent_supervisor_chain_001.rs` (scif-backend @ `2d6ca36e7`) |
| Prior proof in ladder (L2) | [`first-agent-authority-envelope`](/proofs/first-agent-authority-envelope/) |

---

## Independent reconstruction inputs

```bash
H33_TEST_PG_URL='postgres://…?sslmode=require' \
  cargo test --test agent_supervisor_chain_001 -- --ignored --nocapture
```

Expected `state_id`: `5aefda52359ce9d93f6264780bcc95048fbb7483250063a9c7f8265daca5026d`. Expect: chain shape `root → human → reviewer → risk_agent`, all three explanations "chain to root verified", `approve_transfer` held by exactly one principal.

---

## Readiness determination

> **First Agent Supervisor Chain (L3): PROVEN IN OPERATION** for one root → human → AI Reviewer → AI Risk Agent sequential chain, three distinct narrow envelopes, human-only final approval, leaf-node risk agent.

What this unlocks: conversations with transfer agents, fund administrators, insurers, and AI governance buyers about whether agents can supervise other agents — and whether the supervision chain is auditable. The answer is the reconstruction: yes, with replayable rationale for every actor's participation.

What this does **not** unlock: a claim that any platform has deployed a real multi-agent workflow against this tenant; a claim that arbitrary-depth agent graphs have been proven (next proof); a claim that the graph is searchable / sortable.

---

## Where this proof sits in the agentic management ladder

| Level | Proof | Status |
|---|---|---|
| L1 — Agent Recommendation | [first-ai-assisted-transfer](/proofs/first-ai-assisted-transfer/) | proven |
| L2 — Agent Authority Envelope | [first-agent-authority-envelope](/proofs/first-agent-authority-envelope/) | proven |
| **L3 — Agent Supervisor Chain** | **this proof** | **proven now** |
| L4 — Tenant-Scoped Infinite Agent Hierarchy | TBD (next proof, per Eric June 2 2026) | next horizon |

L4 generalizes L3 into N-agents-managing-N-agents trees of arbitrary depth, with search/sort over the agent graph, PQ replay from root to final decision, and the hard constraint that no agent escapes tenant, policy, role, or delegated capability.

---

## Version

| Field | Value |
|---|---|
| Report version | v1.0 (Final) |
| Frozen | 2026-06-02 |
| Supersedes | None |
| Superseded by (planned) | `first-tenant-scoped-agent-hierarchy` (L4) |

---

*Issued by H33, Inc. — Eric Beans, CEO. Independently reconstructable per Section 09.*