stress-test

name	stress-test
description	Manage — /em -stress-test — Business Assumption Stress Testing
executor	LLM_BEHAVIOR
skill_id	business.c_level_advisor.executive_mentor.stress_test
status	ADOPTED
security	{"level":"standard","pii":false,"approval_required":false}
anchors	["business","testing"]
tier	2
input_schema	[{"name":"code_or_task","type":"string","description":"Code snippet, script, or task description to process","required":true},{"name":"context","type":"string","description":"Additional context or background information","required":false}]
output_schema	[{"name":"result","type":"string","description":"Primary output from stress test"}]

/em:stress-test — Business Assumption Stress Testing

Command: /em:stress-test <assumption>

Take any business assumption and break it before the market does. Revenue projections. Market size. Competitive moat. Hiring velocity. Customer retention.

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Why Most Assumptions Are Wrong

Founders are optimists by nature. That's a feature — you need optimism to start something from nothing. But it becomes a liability when assumptions in business models get inflated by the same optimism that got you started.

The most dangerous assumptions are the ones everyone agrees on.

When the whole team believes the $50M market is real, when every investor call goes well so you assume the round will close, when your model shows $2M ARR by December and nobody questions it — that's when you're most exposed.

Stress testing isn't pessimism. It's calibration.

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The Stress-Test Methodology

Step 1: Isolate the Assumption

State it explicitly. Not "our market is large" but "the total addressable market for B2B spend management software in German SMEs is €2.3B."

The more specific the assumption, the more testable it is. Vague assumptions are unfalsifiable — and therefore useless.

Common assumption types:

• Market size — TAM, SAM, SOM; growth rate; customer segments
• Customer behavior — willingness to pay, churn, expansion, referrals
• Revenue model — conversion rates, deal size, sales cycle, CAC
• Competitive position — moat durability, competitor response speed, switching cost
• Execution — team velocity, hire timeline, product timeline, operational scaling
• Macro — regulatory environment, economic conditions, technology availability

Step 2: Find the Counter-Evidence

For every assumption, actively search for evidence that it's wrong.

Ask:

• Who has tried this and failed?
• What data contradicts this assumption?
• What does the bear case look like?
• If a smart skeptic was looking at this, what would they point to?
• What's the base rate for assumptions like this?

Sources of counter-evidence:

• Comparable companies that failed in adjacent markets
• Customer churn data from similar businesses
• Historical accuracy of similar forecasts
• Industry reports with conflicting data