Fold cmux and herdr agent-multiplexer patterns into TAC loop-engineering guidance. Treat the primary agent as orchestrator over panes/tabs via CLI + socket (no MCP required), pane as isolation boundary, and multiplexer state (working/idle/blocked) as the feedback signal. Keep TAC invariants: deploy stays signed-action-only via git-proxy:8099/deploy, peer agents remain insider-threat candidates with least privilege and receipts, multiplexer driving shells does not grant a raw-command deploy path.
Fold the three-video business, macro, and AI-learning synthesis into TAC loop-engineering guidance. Convert market stories, money-flow narratives, and AI demos into small receipt-bound operating loops with niche/distribution, money-flow, AI-amplifier, and seven-day experiment checks.
Capture the Security Fest talk in TAC loop-engineering guidance. Treat agents with file, tool, code, or deploy access as insider-threat candidates and require least privilege, no raw secrets, sandboxing, supply-chain checks, human approval for business-impacting actions, receipts, and promotion attestation.
Capture the AI-era role archetype discourse as delivery activity modes rather than permanent job titles. Add Prototyper, Grower, Sweeper, Reviewer/Taster, Architect/Primitive keeper, and Operator/SRE invariants while preserving the guardrail that role collapse does not make expertise obsolete.
Deepen the Codex product-work guidance with explicit artifact stages, production-readiness receipts, model-timing assumptions, and a deletion/simplification review criterion so cheap implementation does not create ungoverned prototype slop.
Capture the Codex product-work interview in TAC loop-engineering guidance. Preserve PRD/spec discipline, prototypes, human taste/systems review, receipt-gated background agents, and explicit ownership even when implementation gets cheaper.
Ground TAC loop-engineering guidance in external production references: NVIDIA Secure Agent Workspace, Infisical Agent Vault, Anthropic agent evals, and OWASP AI Agent Security. Lock signed-action-only deploy posture and research markers with pytest.
Capture the NanoClaw autonomous work-agent blueprint in the TAC loop-engineering meta-prompt. Require plans to distinguish shared agent factories from personal work agents, isolate each agent, separate credentials through vault/proxy injection, define access policies, and include management/revocation surfaces. Tests lock the new markers.
Capture the GLM 5.2 harness video in the loop-engineering meta-prompt. Require portable context, report/review phases, quality gates, and model/cost notes so TAC plans can run on lower-cost or open-source models without relying on frontier-model taste.
Capture the Sean's AI Stories loop-engineering video in the TAC meta-prompt. Require plans to name harness context, memory, guardrails, traces, evals, and promotion criteria, and lock those markers with pytest.
artale