Core Insight
Prompt engineering is dead. The new paradigm is loop engineering: AI tries → self-checks → fixes → retries → marks done. You move from being in the loop to being outside the loop. This is only possible because new models (Claude Fable 5, GPT 5.6) are smart enough to self-evaluate.
A loop has four components: Goal (defined completion criteria), Checklist (definition of done), Inspector (self-review pass), and Budget (stop after N attempts).
Two Loop Types
Inner loop: Single task — try, inspect, fix, retry. AI self-corrects before delivering.
Outer loop: Recurring scheduled job that runs inner loops each iteration. Self-improves over time.
Implementation Gap Analysis
| Capability | Hermes Has | Loop Eng. | Gap |
|---|---|---|---|
| Scheduled recurring tasks | ✅ 17 crons | Outer loop | None |
| Self-review within task | ❌ Missing | Inner loop | BIG |
| Inspector/second pass | ❌ Missing | Grader model | BIG |
| Hard definition-of-done | ⚠️ Soft goals | Checklist | Medium |
| Skills auto-update from loops | ❌ Missing | Loop→skill | Medium |
| Per-task attempt budget | ⚠️ Repeat only | Stop after N | Small |
Implementation Plan
- P0 — Inner loop skill. Created
loop-engineerskill. Pattern: GOAL + DONE WHEN checklist + STOP AFTER budget → delegate_task → inspect → retry up to N. - P0 — Inspector pass. Five-point checklist before any subagent output reaches Dwad: exists, meets checklist, no hallucinations, correct format, passes sniff test.
- P1 — Upgrade crons. Add DONE WHEN checklists and STOP AFTER budgets to quality-critical cron jobs (audit-dojo, fabric-health-check first).
- P2 — Skills auto-update. Add to every LLM-driven cron prompt: "If you discover anything that would improve the [skill], patch it before delivering."
- P3 — Goal template library. Build reusable DONE WHEN checklists for recurring task types.