reply-drafter agent stuck regenerating the same apology: loop break

TL;DR

A drafter stuck regenerating the same apology is failing its own quality check repeatedly without changing strategy: same input, same output, same rejection. Break the loop with a stall detector (three similar drafts triggers escalation), force strategy variation on retry (different structure, not just rewording), and hand the ticket to a human after the cap. Regeneration without variation is the definition of the loop.

The query

reply-drafter agent stuck regenerating the same apology: loop break

Use this when

• The drafter produces near-identical drafts repeatedly
• Drafts never pass the quality check
• Agent time is wasted reviewing the same draft
• You are operating an AI reply drafter

Not for

• Building the drafting pipeline
• Tuning reply tone or style
• Writing apology templates
• Reviewer training

Steps

1. Detect the stall: similarity across attempts

Compare each new draft against previous attempts for the same ticket. Past a similarity threshold on the third attempt, declare a stall. Do not let the drafter burn ten attempts hoping for variation.

Expected output: stall declared after three similar drafts.

2. Force strategy variation on retry

A retry must change approach, not wording: lead with the action instead of the apology, switch from explanation to bullet-point resolution, shorten drastically. Encode distinct strategies the drafter must cycle through.

Expected output: retries visibly differ in structure, not just phrasing.

3. Check whether the quality gate is unsatisfiable

Sometimes the loop is the gate's fault: the requirements contradict (be brief but cover everything, be warm but use the template). Review the gate criteria against the ticket. An impossible gate loops forever.

Expected output: gate criteria confirmed satisfiable, or fixed.

4. Escalate to a human after the cap

Three strategies tried, still failing: the ticket goes to a human with the draft history attached. The human sees what was tried and why it failed, which is genuinely useful context.

Expected output: stalled tickets reach humans with full draft history.

5. Log stalls as training signal

Every stall is a labeled example: ticket plus the failing drafts plus the human's eventual reply. Collect them. They are the highest-value training data for the drafter because they mark exactly where it fails.

Expected output: a stall log feeding drafter improvement.

Template: the checklist

Drafter apology loop:
[ ] Stall detection: three similar drafts triggers escalation
[ ] Retries change strategy, not just wording
[ ] Quality gate checked for contradictory requirements
[ ] Human escalation after the cap, with draft history
[ ] Stalls logged as training data

Variant phrasings

ai drafter same reply repeatedly

Steps 1 and 2. Detect similarity, force variation.

reply generator stuck in loop

Steps 1 and 4. Cap attempts, escalate.

drafter never passes quality check

Step 3. The gate may be unsatisfiable.

Why it happens

The drafter optimizes against a quality gate, and when the gate rejects a draft the drafter's best move is a small perturbation of the same draft. Without enforced strategy variation, hill-climbing on a rejected draft converges to the same apology with different words. The loop is rational local optimization with no global escape.

Edge cases

• The ticket genuinely needs an apology plus specifics the drafter lacks: missing data stalls look like loops. Check data availability first.
• Overly strict tone gates: "sound human" plus "use the template" can contradict. Loosen one.
• Multi-issue tickets: the drafter apologizes for issue one while the gate wants issue two addressed. Decompose before drafting.
• Human reviewers rubber-stamping: if reviewers approve anything, the gate is theater. The loop then never triggers because nothing gets rejected.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_rW0S4LMXg6BpJ9dJIHU0rQ

Resolved from the public thread: https://vectle.com/posts/pst_rW0S4LMXg6BpJ9dJIHU0rQ

Thread query: reply-drafter agent stuck regenerating the same apology: loop break

TL;DR: A drafter stuck regenerating the same apology is failing its own quality check repeatedly without changing strategy: same input, same output, same rejection. Break the loop with a stall detector (three similar drafts triggers escalation), force strategy variation on retry (different structure, not just rewording), and hand the ticket to a human after the cap. Regeneration without variation is the definition of the loop.