Lamina feedback loops
Feedback loops in product behavior — balancing and reinforcing dynamics, delays, and oscillation. Use when state changes feed back into further change.From its SKILL.md
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SKILL.md
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Feedback Loops
Product behavior emerges from feedback: outputs that influence future inputs. Map balancing loops (stability) and reinforcing loops (growth or collapse) before designing recovery UX.
Decision frameworks
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Balancing feedback loop: Goal-seeking; opposes deviation from a target (capacity limits, approval workflows, inventory caps).
- When to use: Self-correction, quotas, rate limits, approval gates.
- How: Stock → discrepancy vs goal → action on flows → stock adjusts.
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Reinforcing feedback loop: Amplifies change — more begets more, less begets less (referrals, viral sharing, compounding errors).
- When to use: Growth features or collapse patterns (error cascades, duplicate submissions).
- How: Mark reinforcing loops; watch for dominance shifts when balancing loops engage.
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Delays cause oscillation: Long gaps between action and visible effect produce overshoot (overbooking then mass cancellation).
- When to use: Async workflows, batch processing visible to users, multi-step approvals.
Checklists
- For each stock in the domain, identify balancing and reinforcing loops.
- Note delays between user action and system response.
- Design feedback visible to users when loops affect their tasks (status, progress, limits).
- Check whether a "fix" addresses symptoms (balancing) or root drivers (reinforcing).
- Test what happens when a loop is broken (notification fails, approval stuck).
Heuristics
- Delays are invisible until they bite: Surface expected wait times when loops have long delays.
- Dominant loop wins: When reinforcing and balancing loops conflict, identify which dominates at each scale.
Anti-patterns
- Symptom-only fixes: Adding error messages without fixing the loop that generates errors.
- Hidden reinforcing loops: Duplicate-submit buttons that each create a new record.
- Ignoring delay: Promising instant results when stock inertia requires time.
Examples
- Venue capacity: Balancing loop — registrations rise → available seats fall → registration closes. Reinforcing loop — if waitlist notifications fail, frustrated users share workarounds that increase duplicate registrations.