Plan: TAC RSI Loop Engineering with Plan F3
+ +Process > Tools
+Encode engineering taste into the plan fabric, then let the loops run under receipts and signed actions.
+Purpose
+Create a Plan F3 implementation plan for turning the current TAC Product Factory into a truthful loop-engineering system: HTML-first plans, signed deploy boundaries, verification receipts, event-driven operation, and carefully scoped RSI claims.
+Problem
+The repo already has pieces of RSI and Product Factory behavior, but the product narrative can drift into overclaiming. Factory-level deploy loops are operational, while broader agent-level auto-patch remains unproven except for tracked canary recovery evidence. The system needs a boring, machine-checkable plan that prevents future agents from confusing evidence, aspiration, and production truth.
+Solution
+Use Plan F3 as the canonical planning fabric. Encode the four loops directly in product metadata and receipts, validate plan/deploy/RSI truth in tests, and keep the deploy surface signed-action-only through git-proxy:8099/deploy. The lazy win: constants, receipts, and tests; no new framework.
Relevant Files
+Existing Files
+-
+
- existing
products/product_factory.py— central metadata, plan, receipt, dashboard generation.
+ - existing
pipeline/test_product_factory.py— locks product factory claims and deploy route.
+ - existing
products/DASHBOARD.md— published product truth surface.
+ - existing
products/AGENT_PRODUCTS.md— product/control-plane documentation.
+ - existing
deploy_webhook.py— signed action allowlist and deploy execution boundary.
+ - existing
skill_health.py— RSI cron/self-diagnosis loop.
+ - existing
adw_modules/adw_pipeline.py— ADW phase runner for agent loop.
+ - existing
skills/individual/planf3/— vendored Plan F3 skill.
+
New Files
+-
+
- new
specs/tac-rsi-loop-engineering-planf3.html— this implementation plan.
+ - new
plans/meta-prompts/loop_engineering.md— optional follow-up: compact rules every future plan must include.
+
Implementation Phases
+IMPORTANT: Execute every phase and task step by step, in order, top to bottom.
+Status markers: [] idle · [wip] in progress · [x] complete · [f] failed.
[x] Phase 1: Lock Current Truth
+ Normalize Product Factory truth into constants and tests.
+1.1 RSI claim constants
+-
+
[x]KeepRSI_DECISION = healthy_but_autopatch_unproven.
+ [x]Keepauto_patch_proven = falseuntil degraded-skill recovery receipt exists.
+ [x]Trackrsi_canary_recovery_evidence = trueseparately from broad autonomy.
+
1.2 Testing Strategy
+Use pytest to lock the claim model.
+-
+
[x]uv run --with pytest pytest -q— proves current factory tests pass.
+
[x] Phase 2: Encode Four Loops
+ Expose the loop-engineering model as metadata, not prose-only marketing.
+2.1 Product metadata
+-
+
[x]Addloop_engineering.agent_loop: ADW phases run tools until completion.
+ [x]Addloop_engineering.verification_loop: plan validation, pytest, verifier_result, receipts.
+ [x]Addloop_engineering.event_driven_loop: webhooks, cron, JSONL events, dashboard refresh.
+ [x]Addloop_engineering.hill_climbing_loop: signed patch requests, rollback, receipts.
+
2.2 Testing Strategy
+Assert loop metadata exists in generated spec and receipt.
+-
+
[x]uv run --with pytest pytest pipeline/test_product_factory.py -q— proves metadata is emitted.
+
[x] Phase 3: Preserve Signed Deploy Boundary
+ Prevent future agents from reintroducing raw shell deploy through product flows.
+3.1 Deploy route assertions
+-
+
[x]Assert all product outputs usegit-proxy:8099/deploy.
+ [x]Keepdeploy-webhook:8098only as legacy/internal note.
+ [x]Confirm deploy payloads remain signed actions such aspatch_skill_from_pr.
+
3.2 Testing Strategy
+Run product and deploy-webhook tests without live VPS calls.
+-
+
[x]uv run --with pytest pytest pipeline/test_product_factory.py pipeline/test_deploy_webhook.py -q— proves local signed deploy contract.
+
[x] Phase 4: Add Plan F3 Meta-Prompt
+ Make future plans inherit the loop model automatically.
+4.1 Meta-prompt file
+-
+
[x]Createplans/meta-prompts/loop_engineering.md.
+ [x]Require all Product Factory plans to include deploy route, receipts, RSI claim scope, and four-loop mapping.
+ [x]Reference this meta-prompt from generated plan templates or docs.
+
4.2 Testing Strategy
+Use existing plan validator checks; keep it file-based.
+-
+
[x]uv run --with pytest pytest pipeline/test_plan_validator.py -q— proves strict plan validation still works.
+
Validation Commands
+Execute these commands to validate the entire plan is complete:
+-
+
[x]uv run --with pytest pytest -q— all repo-scoped tests pass.
+ [x]rg -n "git-proxy:8099/deploy|auto_patch_proven|loop_engineering" products pipeline plans— expected truth markers exist.
+ [x]rg -n "command\"\s*:" deploy_webhook.py dark_factory.py trigger_webhook.py adw_modules products— no raw command deploy payload in product path.
+
Notes
+Loop 1: Agent
ADW planner/build/test/review/document/ship phases are the existing agent loop. Keep it boring.
Loop 2: Verification
Plan validation, pytest, verifier_result, and receipts prevent confident wrong output.
Loop 3: Event-driven
GitHub webhooks, cron, JSONL events, and dashboards move work out of manual invocation.
Loop 4: Hill-climbing
SkillOpt/skill_health can request signed patches, but receipts and rollback decide what is true.
Tradeoffs
+-
+
- Skipped a new orchestration framework; constants and tests are enough. +
- Skipped live deploy probing; local contract tests are safer unless explicitly requested. +
- Separated canary evidence from broad auto-patch proof to avoid RSI overclaim. +
References
+-
+
- disler/planf3 +
- Anthropic: When AI builds itself +
products/receipts/rsi-proof-20260619T093724Z.md
+ products/AGENT_PRODUCTS.md
+
Amendments
+2026-06-28T00:00:00Z — Initial Plan F3 creation
+Created an HTML-first Plan F3 artifact for TAC RSI loop-engineering hardening.
+2026-06-28T00:00:00Z — Execution completed
+Filled local SVG image slots, opened the plan in browser, added loop_engineering metadata and meta-prompt, resolved the planf3 skill collision, and verified pytest passed.
+