- Create patterns/ directory with README, manifest, and 10 initial patterns covering Ollama JSON fallback, API escaping, deprecation, PTY auth, queue-poll, LLM-as-parser, credential rotation, reverse proxy binding, human approval gates, and transient retry. - Wire pattern loading into architecture/pipeline.js based on task tags. - Update architecture/orchestrator.js to load patterns and surface them in the system prompt. - Update MEMORY.md, ARCHITECTURE.md, and CONTEXT.md to document the registry and record the decision.
34 lines
1.4 KiB
Markdown
34 lines
1.4 KiB
Markdown
# Pattern: Human Approval Gate for Risky Publish Operations
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## Symptom
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An automation publishes or sends content on behalf of the organization (LinkedIn post, client email, newsletter). A mistake in generated content, targeting, or timing causes embarrassment, compliance risk, or customer impact. Once sent, it cannot be recalled.
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## Affected Projects
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- LinkedIn content automation
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- Cyber Tips Newsletter pipeline
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- Email inbox triage agent (if it sends replies)
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- Monthly IT newsletter generator
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## Root Cause
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LLM-generated content is probabilistic and may contain hallucinations, wrong tone, outdated facts, or malformed formatting. Fully automated publishing removes the human sanity check.
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## Standard Fix
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1. Generate the draft and present it for human review before any publish/send action.
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2. Separate "draft" and "publish" stages in the workflow.
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3. Require explicit confirmation (button click, message reaction, approval field) for the publish step.
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4. Log who approved what and when.
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5. Provide an easy cancellation path before the deadline.
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## When to Apply
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- Any workflow that sends client-facing communications.
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- Any workflow that posts to public or branded channels.
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- Any workflow where content cannot be retracted after execution.
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## Verification
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- Draft stage produces reviewable content.
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- Publish step does not execute without explicit approval.
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- Audit log records approver, timestamp, and content hash/summary.
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## Related Patterns
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- None yet.
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