Scenario branch

Scenario Branch

Presenting one future for a fast-moving, high-agency situation is itself a misrepresentation — it hides that the outcome depends on choices and unknowns that haven't resolved yet. But the usual fix, "optimistic / pessimistic / base case," is barely better: those labels describe your mood, not the mechanics. This skill builds real branches from the variables that actually drive the fork, so each future is a testable if-then, not a vibe.

What separates this from bad scenario work

• Branches come from driver variables, not moods. Identify the 2–4 variables whose values actually determine the outcome (pace of a capability, speed of a policy response, whether a cost curve keeps falling). The branches are combinations of those values — not "good case / bad case."
• Each branch names its trigger. State the observable condition under which this branch is the one you're in. A scenario you can't tell you're entering is useless.
• Plausibility is ordinal, not fake-precise. Rate each branch central / plausible / tail. Do not attach invented probabilities ("23% likely") to things you cannot possibly have measured — false precision manufactures authority you haven't earned.
• Branches propagate. Name which other domains each branch pushes on, through what mechanism, with what lag. A scenario that changes nothing downstream isn't a scenario, it's a footnote.
• Never average the branches. The expected-value mush across incompatible futures is a number no future will resemble. The set of branches is the answer; collapsing it destroys the information.

Driver variables: how to find them

Ask: "what are the few things that, if I knew their values, would tell me which future we're in?" Good drivers are:

• Uncertain (you genuinely don't know the value) — a variable everyone agrees on isn't a driver, it's a constant.
• High-leverage (its value swings the outcome).
• Trackable (you can watch it move — that's what makes triggers work).

Two to four drivers is the sweet spot. One driver gives you a line, not a fork. Five-plus gives you an unreadable combinatorial mess — fold the weak ones into assumptions.

Timescale discipline

The further out, the wider the fork, and the less a "forecast" is even the right object. Scale your register to the horizon:

• 0–1 yr: near-measurement; empirical evidence anchors directly.
• 1–3 yr: branches tighten around known drivers; still forecastable.
• 3–7 yr: scenario-dominant. State the capability/policy assumption each branch rests on, out loud.
• 7–15 yr: conditional statements only ("if driver X holds, then…"), not point forecasts.
• 15+ yr: possibility space, not prediction. Enumerate what could happen; refuse to say what will.

If you're tempted to give a confident single number past ~3 years, that's the signal to branch instead.

Procedure

1. State the question and its horizon.
2. Identify the 2–4 driver variables (uncertain × high-leverage × trackable).
3. Build 3–5 branches from meaningful combinations of driver values. Give each a short evocative name and a one-paragraph internally-consistent story.
4. For each branch: trigger (the observable that says you're in it), plausibility (central/plausible/tail), propagation (which domains it pushes on, mechanism, lag).
5. State what to watch — the leading indicators that will tell you which branch is materializing (hands off to change-my-mind for the update triggers).
6. Give a decision-useful takeaway: what's robust across all branches (do this now), and what to keep optionality on (decide later, when a driver resolves).

Output template

QUESTION: <what> | HORIZON: <window>
DRIVERS: <v1>, <v2>, <v3>  (uncertain, high-leverage, trackable)

BRANCH A — "<name>"  [central | plausible | tail]
  Driver values: <v1=…, v2=…, …>
  Story: <one internally-consistent paragraph>
  Trigger (you're here if): <observable>
  Propagates to: <domain> via <mechanism>, lag <immediate|months|years>

BRANCH B — "…"  [ … ]   … (repeat for 3–5)

WATCH: <leading indicators that discriminate between branches>
ROBUST NOW: <what to do regardless of branch>
OPTIONALITY: <what to keep open until a driver resolves>

Example (compressed)

Question: Will AI broadly raise wages this decade? Horizon: 3–10 yr.

DRIVERS: (1) alignment/oversight matures before capability gaps? (2) does
governance distribute or concentrate the gains? (3) does compute access widen?

BRANCH A — "Electrification redux" [plausible]
  Oversight matures + gains distributed. Lag, then broad wage participation —
  like electricity's delayed but eventually shared payoff.
  Trigger: rising labor share + falling entry-level displacement by ~year 3.
  Propagates to: Education (pipeline stabilizes), Governance (less welfare stress), lag: years.

BRANCH B — "Engels' Pause" [central]
  Capability works, gains captured by capital. Productivity up, median wage flat
  for years — the 1800s pattern, until bargaining power shifts.
  Trigger: productivity-wage divergence persists past year 3; labor share keeps falling.
  Propagates to: Governance (redistribution pressure), Epistemics (AI-blame narratives), lag: immediate → years.

BRANCH C — "Great Divergence hardens" [plausible]
  Compute stays concentrated in a few firms/regions. Rentier structure; gains
  accrue to compute owners; Global South falls further behind.
  Trigger: compute access gap widens; frontier stays in <5 firms.
  Propagates to: Geopolitics (compute as leverage), Demography (migration), lag: years.

WATCH: labor share, entry-level hiring index, compute-access distribution, policy response speed.
ROBUST NOW: invest in retraining infrastructure + measurement — pays off in every branch.
OPTIONALITY: hold big redistribution-policy bets until the labor-share signal resolves (~year 3).

Gotchas

• Branches must be mutually distinguishable by their triggers. If you can't say which one you're in from observables, they're not real branches.
• Don't smuggle your preferred future in as "central." Plausibility ratings are about mechanism and base rates, not what you're rooting for.
• 3–5 branches. Two is a false binary; six is unreadable. Fold weak drivers into stated assumptions.
• Pairs with change-my-mind (the triggers become update conditions) and grade-the-evidence (each driver's current value has an evidence tier).