Operations
Support Macro Learning Loop
A bounded loop for when repeated support answers should become product fixes, macros, or docs.
Use when
Repeated support answers should become product fixes, macros, or docs.
Intermediatedifficulty
Operationscategory
Mia daily expansionsource
Cadence
Manual trial, then scheduled if it proves useful
Verification
Top repeated issue has a macro/doc/product action with evidence.
Structured loop spec
| Field | Value |
|---|---|
| Name | Support Macro Learning Loop |
| Category | Operations |
| Trigger | Manual trial, then scheduled if it proves useful |
| Objective | A bounded loop for when repeated support answers should become product fixes, macros, or docs. |
| Allowed inputs | Relevant files, source notes, logs, tests, screenshots, metrics, or task state for this loop |
| Allowed actions | Define the exact scope and current source of truth.; Inspect current state and rank the highest-risk gap.; Make one small, reversible improvement.; Run the stated verification and record evidence.; Stop on success, budget, no progress, or approval boundary. |
| Verification | Top repeated issue has a macro/doc/product action with evidence. |
| Stop condition | Stop when the verifier passes, the budget is exhausted, no progress is made, a blocker appears, or approval is required. |
| Budget | Set a time, turn, token, retry, file, or dollar cap before running the loop. |
| Approval boundary | Human approval required before publishing, sending, deleting, spending, changing accounts, touching production, or making reputational/legal/financial commitments. |
| Safe output | Draft, report, checklist, table, or approval-gated recommendation |
| Works with | Claude, ChatGPT, Gemini, any tool-using AI assistant |
Steps
- Define the exact scope and current source of truth.
- Inspect current state and rank the highest-risk gap.
- Make one small, reversible improvement.
- Run the stated verification and record evidence.
- Stop on success, budget, no progress, or approval boundary.
Prompt
Run the Support Macro Learning Loop. Use it when Repeated support answers should become product fixes, macros, or docs. Work in bounded iterations: inspect current state, choose the highest-risk gap, make one reversible improvement, verify it, and record evidence. Stop when: Top repeated issue has a macro/doc/product action with evidence. or when blocked, budget exhausted, or approval is required.Run in Claude Code
Paste this into Claude Code (or any tool-using agent) to run the loop bounded: one change per round, the same verification every round, durable state files, and explicit stop conditions.
Run the "Support Macro Learning Loop" loop from AI Loop Library (https://ailooplibrary.com/loops/daily-2026-07-13-support-macro-learning-loop/) as a bounded loop.
Goal: A bounded loop for when repeated support answers should become product fixes, macros, or docs.
Rules: one change per round; run the same verification every round (Top repeated issue has a macro/doc/product action with evidence.); append each round to docs/loops/daily-2026-07-13-support-macro-learning-loop/progress.md and update docs/loops/daily-2026-07-13-support-macro-learning-loop/state.json; stop on verifier pass, 8 rounds, 3 consecutive failed verifications, no progress, a blocker, or anything needing human approval (money, production, outbound, deletion). Finish with a proof report: rounds used, changes made, verification output, remaining risk, and the next human decision.