Campaign Overview
The Grace automation framework is a compelling “product evolves itself” story. Eight bash scripts orchestrate a closed-loop system where quality metrics trigger campaign activation, which generates platform-aware content, which feeds back into refinement recommendations. The proof point: domain-map improved 0.305 → 0.853 (+179%) via the H5→H8→H3 loop. This is technical-founder material (Hacker News, builder communities) with secondary angles for ops/DevOps (Weekly monitoring, quality gates, safety infrastructure).Content Angles
Automation-as-Product: “Quality gates and campaign loops”
Register: Protocol-native (HN, r/programming, stratt.engineer) Angle: Technical deep-dive on the 8-taskset architecture. How quality metrics automatically gate campaign activation. How the closed-loop refinement cycle ensures improvements are validated before promotion. Register-aware content generation (5 platform variants per trail). Hook: “I built a system that improves itself. Here’s the safety infrastructure that keeps it from breaking everything.”Founder Workflow: “Automation that respects ADHD”
Register: Builder-native (Bluesky, solopreneurship communities) Angle: Solo founder perspective. Autonomous refinement causes anxiety → dry-run default + explicit--execute gates. No cron jobs. All decisions logged. Audit trail in git. The system gets faster every week because AJ reviews suggestions once, system executes 5 times.
Hook: “My automation doesn’t run amok because humans review the diffs before they become permanent.”
Quality Metrics as Product: “0.305 to 0.853”
Register: Enterprise/SaaS (LinkedIn, product tweets) Angle: Quantified self-improvement. Conformance, completeness, efficiency scoring. How the heuristic predicted the problem (low completeness) and validated the fix. Applicable to prompt tuning, unit refinement, quality assurance in AI systems. Hook: “179% quality improvement via systematic measurement and closed-loop feedback.”Campaign Trail Alignment
- CT-04 SOL_LOG: Weekly operational status including automation cycle results and quality improvements
- CT-05 PROTOCOL_NATIVE: Deep technical thread on execution traces + quality scoring + refinement loops
- CT-03 AEROSPACE_BRIDGE (stretch): “I verified avionics software. Now I verify my AI’s improvements before they ship.”
Distribution Plan (14-day cycle)
| Day | Platform | Content | Register | Link |
|---|---|---|---|---|
| 1 | Bluesky + X | Announcement: “New automation framework live” | Builder-native | No |
| 3 | Blog | Technical deep-dive: H1-H8 architecture | Protocol-native | Yes |
| 4 | HN | Show HN: Grace automation + quality metrics | Protocol-native | No |
| 5 | r/programming | Close to Show HN: diffs, learnings, code | Protocol-native | No |
| 7 | Bluesky + X | ”Domain-map improved 179% via closed-loop refinement” | Metrics angle | No |
| 10 | Enterprise angle: quality gates in AI systems | Enterprise | Yes | |
| 12 | stratt.engineer | Full doctrine release: 5 doctrines + learnings | Protocol-native | Yes |
| 14 | Bluesky + X | ”One week later: automation ran 2 cycles, 3 units improved” | Founder workflow | No |