── ── Startups
Feedback Loops
A system has a feedback loop when its output circles back as input to the next cycle. Reinforcing loops amplify (compound interest, viral growth, bank runs, death spirals). Balancing loops self-correct (thermostats, price discovery, immune response). The critical complication is delay: when delay is long relative to response time, even well-designed balancing loops produce oscillation and overshoot — and operators…
Run Feedback Loops on a real problem
Bring something you're actually deciding — free, in the browser.
How it works
Run the Feedback-Loop Diagnosis — map structure, find dominant loop, predict behavior, find leverage.
1. Name system + variable of interest. Without a specific variable, analysis becomes vague narrative. 2. List drivers and outputs. What inputs change your variable? What does it change in turn? Stay concrete. 3. Identify loops. Trace chains where a variable feeds back to itself. Most systems have several. 4. Classify each loop (R or B). Count negative signs around the loop — even = reinforcing; odd = balancing. 5. Locate delays. Where does a cause take significant time to produce its effect? Delays are where intuition fails. 6. Identify dominant loop. Growth phase = R dominant; maturity = B catching up; crisis = suppressed R taking over. 7. Map stocks and flows. Stocks = accumulations; flows = rates. A positive flow can still leave a stock dangerously low. 8. Predict behavior pattern. Pure R → exponential growth/collapse. Pure B → equilibrium. R+delay → overshoot/oscillation. R+B competing → S-curve. Mismatch with observed behavior = missed loop. 9. Find leverage (Meadows hierarchy). Parameters → buffers → structures → delays → balancing loops → reinforcing loops → goals → paradigm. Most failed interventions push parameters; move up. 10. Stress-test against system response. Balancing loops fight back; reinforcing loops restore trajectory. Intervention must change structure, not just symptom.
When to use it
- user says "we keep overshooting/undershooting", "the cure is causing the disease", "we're stuck in a loop", "why does this keep happening?", "the system keeps fighting back", "bullwhip effect", "death spiral", "growth flywheel"
- system shows oscillation or sudden collapse
- user is planning an intervention in an org/market/supply chain and wants to predict how it will respond
When not to use it
the decision is a one-shot linear choice with no feedback to future decisions, or an exogenous shock so large it dominates all internal dynamics is the obvious explanation.
Worked example
The AI Capex Boom as a Reinforcing Loop Meeting Its Balancing Limits (2024–2026)
Between 2024 and 2026, the largest US technology companies — Microsoft, Alphabet, Amazon, and Meta, joined by chipmaker Nvidia and a wave of AI-native startups led by OpenAI and Anthropic — poured historic sums into AI data-center capacity. Reported annual capital expenditure at the four "hyperscaler" cloud providers rose from roughly $150 billion in 2023 toward figures widely reported in the several-hundred-billion range for 2025, with further increases guided for 2026. The dominant narrative through most of this period was pure reinforcing-loop optimism: spend more…
Install this skill (free, MIT)
npx skills add deciqAI/knowledge-skillsUseful? Star the repo — stars help other builders find it.
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K = i × c, where i = average invites per existing user, c = conversion rate into new activated users.