Technology & AI risk-off · 0–6 months
A what‑if from the future

What if one model-API outage takes down thousands of AI apps at once?

A single-vendor API outage is a reliability scare, not a demand cut, so the hit is shallow and mean-reverting: NVDA and the semi complex dip on agentic-app concentration fears but the capex thesis is intact. Closer to the CrowdStrike July-2024 global outage — sharp headline, fast recovery once service restored — than to DeepSeek. Forward angle: real repricing is in enterprise multi-cloud redundancy spend, a marginal positive for #2 inference vendors, not a lasting NVDA negative.

30%
our model probability
over 0–6 months
prediction markets — the market's odds
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Anchored to measured history 30% · 90% range 10–51% · 40 dated precedents behind it — a wider range means thinner evidence

Every number ships with its receipt — the odds, the range, the precedents, and a public grade at Reality Check. The statistical machinery that produces it is proprietary.

The butterfly cascade

How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.

Resolution timeline — how this probability is moving

Our model's odds (electric blue) over time vs the market's (Polymarket, amber), from the past toward the 0–6 months horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. Loading the probability audit trail…

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What it would mean

If this plays out, it is a risk-off shock. A shared model-API outage simultaneously downs thousands of agentic apps, exposing single-vendor concentration risk. The trigger decomposes into signed root‑shocks — AI capex ▼ · Risk appetite ▼ — which propagate through our causal graph to the markets below.

Methodology. Probability and impact are anchored to history and scored against what actually happens — wins and losses, in public, at Reality Check. Market odds live from Polymarket & Kalshi. By Vikas Singh, Quantitative Strategist. Updated 2026-08-13.