Experiments

The first full test of a change shouldn’t be production.

Experiments turn a change into a falsifiable hypothesis. State what you expect and lock it before the run. Declare blast radius, guards, and rollback. Then prove it in a proving ground — before anything touches a live system.

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Experiments12 this workspace
Controlled trialRunning
SPF hardening flip — ~all → -all causes zero loss of legitimate mail
Parameter checkSupported
Wave size of 1,400 keeps migration sync failures under 0.5%
Open hypothesisRefuted
DKIM keys can rotate monthly without deliverability impact
Observation checkPlanned
Catch-all routing loses no legitimate mail over 72h
Read-only probes · every datapoint drills to its proof

How Experiments work

Hypothesis, envelope, proving ground, verdict.

New experimentDraft
Observation checkControlled trial
Hypothesis
Tightening the apex SPF record from soft-fail to hard-fail causes zero loss of legitimate mail, because the only SPF-authorized sending path passes DMARC already.
FalsifiabilityLocked before run
0 delivery failures across the 80-minute observation window, measured at the receiving mailbox — not inferred from send logs.
If you can’t state what would refute it, it isn’t ready to run

Every experiment starts falsifiable.

State a hypothesis about your systems in plain language — and lock what you expect to happen before the run, so the outcome is measurable instead of arguable. If you can't state what would refute it, it isn't ready to run.

  • A hypothesis, not a hunch — stated in plain language
  • Expected outcome locked before the run, so the result is measurable
  • Read-only probes by default — every datapoint drills to its proof

The instruments

Four ways to interrogate a system before you change it.

Observation Check

Watch a live signal over a declared window. Touch nothing; learn everything. The cheapest way to turn 'we think' into 'we measured.'

Controlled Trial

Stage the change on a sandboxed path with guards armed and rollback captured, then measure the effect against the locked expectation.

Parameter Check

Sweep a parameter — wave size, threshold, TTL — and find the safe value with data before you commit the estate to one.

Open Hypothesis

A standing question about your systems, backtested against recorded history and re-run as state changes. Supported today, re-verified tomorrow.

Why Experiments

Cheap to be wrong early, expensive to be wrong late.

'Don't touch it' stops being rational.

Estates freeze because the first full test of any change is production, and failure means outages and career damage. When rehearsal is cheap, changing things is too.

Refuted is a result, not a failure.

An experiment that kills a bad change cost you an observation window. The same discovery in production costs an incident, a rollback, and a postmortem.

Supported becomes shipped.

A supported hypothesis promotes straight into a work item — evidence attached, envelope already mapped. Design flows into build without re-litigating the decision.

Stop testing in production.

State a hypothesis about your systems and prove it in a proving ground — guards armed, rollback captured, verdict measured.

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