Systems Thinking

Scope

Covers

Seeing the “whole system” behind a problem (actors, incentives, feedback loops, culture/rules)
Anticipating second- and third-order effects (including time delays)
Finding leverage points (small changes with outsized impact)
Converting recurring pain into a reusable system (process, automation, or operating mechanism)

When to use

“This is a complex ecosystem; we’re missing the bigger picture.”
“What are the second-order effects if we do X?”
“We keep solving symptoms—what’s the system causing this?”
“Map the players + incentives and how they interact.”
“We need to redesign a process/org without unintended consequences.”

When NOT to use

The problem is simple/linear and mostly execution (use a project plan/timeline).
You need primary user research or data you don’t have (do discovery first).
You need deep quantitative forecasting/simulation (this skill produces a qualitative map + risks, not a full model).
The decision is low-impact and fully reversible (don’t over-invest).

Inputs

Minimum required

The focal decision or problem statement (1–2 sentences)
Desired outcome + time horizon (default: 6–12 months)
Known constraints/guardrails (trust, safety, compliance, budget, headcount)
Known actors/stakeholders (teams, users, partners, regulators, vendors)
What has been tried already (and what happened)

Missing-info strategy

Ask up to 5 questions from references/INTAKE.md.
If answers aren’t available, proceed with clearly labeled assumptions and provide 2–3 alternative system framings/boundaries.

Outputs (deliverables)

Produce a Systems Thinking Pack in Markdown (in-chat; or as files if requested) in this order:

Context + System boundary (goal, scope, non-scope, time horizon)
Actors & incentives map (players, goals, constraints, power, conflicts)
System map (key variables + causal links) + feedback loops (reinforcing/balancing) + time delays
Second-/third-order effects ledger for the top 1–3 decisions
Leverage points + intervention plan (actions, owners, sequencing, guardrails)
System-build opportunities (what to automate/standardize to reduce recurring pain)
Risks / Open questions / Next steps (required)

Templates: references/TEMPLATES.md

Workflow (8 steps)

1) Intake + pick the focal decision/problem

Inputs: User context; use references/INTAKE.md.
Actions: Restate the focal decision/problem, desired outcome, and time horizon; list constraints/guardrails.
Outputs: Draft Context + System boundary.
Checks: The problem is not a solution in disguise; scope and non-scope are explicit.

2) Define the system boundary (what’s “in” vs “out”)

Inputs: Problem statement + constraints.
Actions: Choose a boundary that is useful (not everything). Name the primary outcome metric(s) and a few leading indicators.
Outputs: Boundary statement + success measures.
Checks: Boundary is tight enough to act on, but wide enough to include key externalities.

3) Map actors + incentives (multi-agent reality)

Inputs: Boundary + stakeholder list.
Actions: Enumerate actors/players; capture incentives, constraints, power, and likely behaviors.
Outputs: Actors & incentives map (table).
Checks: Includes at least 1–2 “invisible” actors (e.g., policies, culture norms, platform constraints) if relevant.

4) Build a simple system map (variables + causal links)

Inputs: Actors map + known dynamics.
Actions: List key variables; map causal links (“A increases B”, “C decreases D”); mark time delays.
Outputs: System map (text/table) with 10–20 high-signal links.
Checks: Links are directional and testable; avoids buzzwords (“alignment”, “quality”) without definition.

5) Identify feedback loops + time delays

Inputs: System map.
Actions: Extract reinforcing and balancing loops; note where delays create overshoot/oscillation; flag common traps.
Outputs: Feedback loops section (2–6 loops) + delays list.
Checks: Each loop has a short “so what” describing the pattern it creates.

6) Run second-/third-order effects on 1–3 candidate moves

Inputs: Candidate decisions/actions.
Actions: For each move, enumerate first-, second-, and third-order effects; include who wins/loses and what constraints tighten over time.
Outputs: Second-/third-order effects ledger.
Checks: Includes at least one unintended consequence + one mitigating action per move.

7) Choose leverage points + design interventions (including “build a system”)

Inputs: Loops + effects ledger.
Actions: Identify leverage points (policy, incentives, information flows, tooling, process); propose interventions; include at least one system-build/automation opportunity for recurring pain.
Outputs: Leverage points + intervention plan + System-build opportunities.
Checks: Each intervention has an owner, a measurable leading indicator, and a guardrail.

8) Quality gate + finalize pack

Inputs: All draft sections.
Actions: Run references/CHECKLISTS.md and score with references/RUBRIC.md. Add Risks / Open questions / Next steps.
Outputs: Final Systems Thinking Pack.
Checks: A reader can act without a live meeting; trade-offs and uncertainties are explicit.

Quality gate (required)

Use references/CHECKLISTS.md and references/RUBRIC.md.
Always include: Risks, Open questions, Next steps.

Examples

Example 1 (Org/process): “Our on-call load keeps rising and teams are burned out. Map the system and propose leverage points.”
Expected: an actors/incentives map (teams, incidents, incentives), feedback loops (firefighting loop), effects ledger for candidate changes, and an intervention plan with guardrails.

Example 2 (Product ecosystem): “We’re changing API pricing; what are the second-order effects across partners and customer segments?”
Expected: system boundary + actors map (customers/partners/internal), loops and delays, effects ledger, and a sequencing/mitigation plan.

Boundary example: “Write a status update about this week’s tasks.”
Response: this skill is for complex systems/decisions. Suggest a project update format instead; only use this skill if there’s a systemic pattern to diagnose.