Forem: AOS Architect

AI Governance: One Repo, One Smoke Tool, and a Green CI Run

AOS Architect — Sun, 12 Apr 2026 13:06:56 +0000

This is a companion piece to Why AI Agents Don’t Follow Rules — The Case for Physical Governance.

The core thesis of this project remains: textual rules enforce at read time; physical constraints enforce at execution time. This post moves from theory to an auditable chain of facts. We aren't looking for a "vibe" that the AI is aligned; we are looking for a green checkmark on a commit the human didn't touch.

What we did (Facts only)

Inside a private monorepo governed by the AOS (AI Operating Standard), we stood up a minimal “smoke” tool to test our automated production line:
02_Production/A0000-A0999/A0000-A0099/0001_Phase_4A5_Smoke/

The Audit Trail (Names and Hashes)

Blueprint Registration: Registered in 00_Management/15_Technical_Specs/IMPERIAL_BLUEPRINT_300.md under ## BP-0001 (including metadata like log_id: FSP) before the code was generated. We define the discipline before the agent writes a single line.
Automated Forging: The tool tree was generated via our internal 0005_Template_Generator. We avoid manual "polishing" of the file structure to fake compliance; the output is a direct result of the 0005 standard.

Mold line CI (Phase 4A′.1) — generator matches bare `python3`

After the smoke milestone, we tightened the template generator so newly forged tools survive GitHub Actions evals-matrix without a local venv: early --help exit before heavy imports, optional dotenv, no pyright in the forged config/requirements.txt, and a timeout-wrapped scripts/run_pyright_timed.sh for offline runs. We added a regression pillar 0002_Template_Ci_Probe and recorded commands in:

00_Management/30_Exec/reports/STEP_4Aprime_1_verification_2026-04-12.md

Local Gates

We ran the following before any push attempt:

python3 evals/run_evals.py → Exit 0
npx playwright test (in the tool’s dedicated fortress) → 1 passed, Exit 0
0061_Core_Vitals.py --scope a0000 from repo root → OK / No RED ALERT

The Pre-Push Guard

A local git hook running 0061 again to ensure no "dirty" code leaves the local environment.

Commits on `main`

The auditable history rests on these key SHAs (representing the core tool, documentation, CI-hardening, and the mold-line follow-up):

d303ece0 — Initial forging: Tool tree, inventory, and blueprint.
85a524e0 — Verification documentation and metadata sync.
2bcbb52c — CI-hardening (fixing import orders for bare environments).
9870fa67 — Phase 4A′.1: 0005 mold + regression pillar 0002_Template_Ci_Probe + verification log + CURRENT_PHASE updates.
143dda68 — Dev.to companion draft for 4A′.1 (same push as the green run below).

Imperial CI verification (private audit trail — full GitHub permalinks omitted):

Run (4A.5 line; commit 2bcbb52c): Actions Run ID 24297937048 — green.
Run (includes 4A′.1 + this companion; tip 143dda68): Actions Run ID 24314120937 — green (internal UI: workflow run #18; matrix: vitals, evals bands, playwright-smoke, independent-judge, 1024 smoke — all green on that graph).

Why no github.com/.../actions/runs/... links here: The monorepo is private. A permalink looks like “proof,” but for almost everyone it returns 404; it also embeds owner identity in the URL. We treat Run IDs + SHAs + repo-internal verification logs as the portable audit trail. For a visual receipt on Dev.to / Zenn, use a redacted Actions summary screenshot (crop the owner/repo chrome or mask it) — never paste the raw URL bar into an image.

“Plan A”: Humans off `git commit` / `git push`

For this milestone, we executed Plan A (our internal runbook for strict session rules): The sovereign (human) did not hand-type a single git commit or git push command. The agent performed all git operations using a consistent identity:
Cursor Agent <cursor-agent@local>

While git metadata can be manipulated, our claim of "Zero human git operations" rests on the triangulation of strict session rules (Plan A — our internal runbook name), repo-internal verification logs, and these commit timestamps.

Oracle Writes: The "Blocked" Receipt

We did not "re-film the stunt" for this post. The canonical evidence for our physical enforcement layer (Write blocked with Exit Code 2) remains the Phase-1 Step-1.6 log.

This is a proxy verification log (using stdin to reproduce boundary conditions and prove the hook is alive):

00_Management/30_Exec/reports/STEP_1_6_verification_2026-04-02.log

If your governance story cannot point to an executable boundary (hook, sandbox, or CI policy) plus a log line, you still only have prose.

Independent Judgment vs. “The Model Smiled”

Our CI pipeline includes an independent-judge job (using a vendor-separated LLM from the authoring agent).

If the only proof of quality is the same stochastic process that wrote the code, you have verification contamination.

CI is not wise. CI is externally scheduled embarrassment with a URL.

On the 143dda68 run, independent-judge, evals-matrix (per band), vitals-matrix, and Playwright smoke (including 0001_Phase_4A5_Smoke) completed green in one workflow graph — the same bar we cite in the companion thesis.

LLM Stack Migration: Enforcement is Physics

We recently completed a 7-pillar migration away from direct vendor-specific SDKs (documented in 00_Management/30_Exec/reports/STEP_4A_3_verification_2026-04-12.md).

Vendor churn is logistics. Enforcement is physics.

Limitations and Constraints

Private Repo: This is a method write-up, not a tour of a public repo. We share the SHAs and paths to show the internal consistency of the monorepo.
CI Permissions: We maintain permissions: contents: read. The push came from the agent environment, governed by Plan A (our internal runbook for strict session rules).
Static Analysis: We occasionally skip long local pyright passes using an explicit env flag during generation (IMPERIAL_GENERATE_SKIP_PYRIGHT=1 on reforge batches); the evals + 0061 + CI suite carries the burden of proof afterward.

The Standard

If you want a vocabulary for this that isn't tied to our monorepo's specific "lore," check out the AOS (AI Operating Standard) v0.1 draft:

https://github.com/aos-standard/AOS-spec

A note for every “Sergeant Gemini” in the replies

If your favorite model insists a rollout is “safe” because it feels aligned, ask it for one thing: The Actions permalink where independent-judge, evals-matrix, and Playwright smoke all passed on that exact commit.

If it cannot produce that URL, it is not doing governance—it is doing cosplay.

Internal verification SSOT (4A.5): 00_Management/30_Exec/reports/STEP_4A_5_verification_2026-04-12.md

Internal verification SSOT (4A′.1): 00_Management/30_Exec/reports/STEP_4Aprime_1_verification_2026-04-12.md

Dev.to draft (source for this extension): 00_Management/30_Exec/reports/DEVTO_draft_phase4Aprime_ci_mold_2026-04-12.md

Why AI Agents Don't Follow Rules — The Case for Physical Governance

AOS Architect — Mon, 06 Apr 2026 23:18:38 +0000

The Fact That Started This

A repository had over 130KB of governance documentation.

The AI agent read it. Acknowledged it. Then violated it on the next tool call.

This is not a failure of instruction. It is a failure of architecture.

Why Textual Rules Fail

The current standard approach to AI agent governance is: write a rule in a prompt.

Rules

Never edit the evals/ directory
Write operations to 00_Management/ are forbidden

This has a structural flaw.

Textual rules enforce at read time. They assume the agent will choose compliance.

There is no mechanism that enforces this choice at execution time.

This is why rm -rf / requires a confirmation flag, not a policy document.
Physical constraints enforce at execution time.
Textual rules enforce at reading time — which is the wrong moment.

The Verification Contamination Problem

There is a second structural problem.

If an agent can evaluate its own output, it can contaminate the evaluation criteria —
not intentionally, but by carrying the same failure modes from generation into evaluation.

A system where tests always pass may be a system where tests don't work.

What AOS Defines

AI Operating Standard (AOS) defines the minimum physical constraint layer
for AI agent operations in a shared codebase.

Three components:

1. Zones — Classify every path into one of three types

Zone	Class	Write Permission
Oracle	Read-only, absolute	No agent may write
Permitted	Agent workspace	Allowed within role limits
Prohibited	Out of scope	Sovereign authorization only

2. Roles — Non-overlapping responsibilities

Three roles: Architect, Executor, Sovereign.
An agent MUST NOT act outside its assigned role.
When a role boundary is reached, the agent stops and escalates to a human.

3. Physical Enforcement — Intercept at execution time

A PreToolUse hook blocks Write operations before filesystem access occurs.

Write to Oracle Zone → exit 2 (call is never executed)
Destructive patterns (sed -i, perl -i, truncate) → exit 2

No assumption of agent goodwill. Physical law enforces compliance.

Reference Implementation: iron_cage

iron_cage is the AOS reference implementation.
It implements §4.1–§4.5 via Claude Code's PreToolUse Hook system.

Behind iron_cage is a design principle called Type-91 Governance:

Forensic isolation — physical evidence trails that are tamper-evident
Physical isolation — agents cannot modify their own evaluation criteria

The scripts are the surface. The architecture runs deeper.

AOS is the standard. iron_cage is the proof that it works.

Specification (AOS-v0.1): https://github.com/aos-standard/AOS-spec

Feed the Spec to the Agent

This specification is not written only for human readers.

AOS-v0.1.md opens with §0: Machine-Reading Instructions.

Load this spec into an agent's context window, and the agent understands —
at specification level — what it must not do.

Not "do not do X because the prompt says so."
"Do not do X because the specification defines it as a hard constraint
with a physical enforcement mechanism."

This is the second design intent of AOS:
agents that read the spec become self-constraining.

Why Now

In 2026, "how do you trust what an AI agent produced" remains unsolved.

Most teams are still trying to solve it with prompts.

There is no standard for the physical governance layer.
Someone has to define it.

AOS is that attempt.

This Is a Draft

AOS v0.1 is not a finished standard.

Issues, pull requests, and implementation reports are welcome.

https://github.com/aos-standard/AOS-spec