AI Purple · Module 1 · The Loop in Question

The Pressure on the Loop: Machine-Speed Adversaries, Detection Decay and the Annual Test

The lesson measures the pressure that makes the traditional rhythm inadequate: a shrinking exploitation window, an estate that changes faster than the test, detection decay, the finding half-life, scarce talent and a calendar that rewards a report. Participants calculate a test-to-change ratio, read a decay estimate in three states, and separate what AI makes cheaper, repetition, variation and drafting, from what it does not: novelty, judgement, independence and safety.

Lesson 3 of 29Chapter 370 minutes

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Learning objectives

After the lesson the participant can:

Key concepts

Test-to-change ratio
For a given technique, the number of production changes that touch what the technique depends on, between two passing tests. A ratio of one means every change was followed by a verification; a ratio of twenty means twenty changes accumulated before anyone looked.
Detection decay
The loss of a detection's effect between tests as its dependencies change. It is measured by age since the last passing test, set against the evidence expiry, together with the count of dependency changes since that test.
Current, at-risk, expired
The three states of a decay estimate: current if a test passed within expiry and no dependency changed since; at-risk if within expiry but a dependency changed; expired if the last passing test is older than the expiry.
Finding half-life
The time a finding spends between P3 Observe and P5 Verify, in two parts: the wait for a change at P4 Improve and the wait for the proof of that change.

Interactive exercises

Do them here and get feedback at once. Choose a card and then where it belongs, or drag it.

Interactive exercise 1 · Sort

Current, at-risk or expired

Classify each priority detection at Hansa Mutual, where evidence for a priority technique expires after 90 days, into the three states of the chapter's decay estimate.

Interactive exercise 2 · Scenario

A test-to-change ratio above ten

Apply the chapter's practical guide on the test-to-change ratio to a priority technique at Hansa Mutual.

Teaching plan

15 minThe teacher presents the shrinking window with the chapter's figures (63, 32 and 5 days) and stresses which statements are the sources' and which the book's own conclusion.
10 minWorked example at the board: Nordvik Region's fortnightly releases against an annual test give a ratio of about 26.
25 minExercise: participants estimate the test-to-change ratio and the decay state for three techniques from a supplied or their own change log.
10 minGroups read the usage-mode table and argue why Modes 1 to 3 leave the rhythm as it was while Modes 4 and 5 change it.
10 minPlenary on what AI does not make cheaper, and on the remedies of the two organisations: terms for Nordvik Region, a platform for Hansa Mutual.

Discussion

  1. Age alone misleads in both directions. Which of your detections would look healthy by age and unhealthy by dependency changes, or the reverse?
  2. The chapter says a calendar set by regulation or procurement rewards a report. What would have to change in a contract or a testing programme for it to reward a verified finding instead?
  3. If AI makes variation and repetition cheaper but not novelty, judgement, independence or safety, where does the bottleneck of your own loop move?

Written exercise

Exercise · 25 minutes

Test-to-change ratio and decay estimate

Choose three priority techniques. For each, write down the dependency path: the service or identity it targets, the log source, the detection record and the playbook. From the change log of the last 12 months, count the changes that touched anything on that path, list the dates of passing tests in the same period and divide changes by passing tests. Mark any technique whose ratio exceeds 10 or whose last passing test is older than its evidence expiry, classify its detection as current, at-risk or expired, and choose a remedy per technique: a trigger after a change on the path, a schedule, or an accepted gap recorded as such.

Deliverable: A dated table with one row per technique: changes, passing tests, ratio, last passing test, decay state and the chosen remedy.

Self-test

Choose an answer to see whether it is right, or open the answer below each question.

  1. A priority detection at Hansa Mutual passed its last test 53 days ago, and its log connector was upgraded after that test. Which state does the chapter's decay estimate give it?

    Show the answer

    B. At-risk, because it is within expiry but a dependency has changed.
    A detection is at-risk when its last passing test is within the evidence expiry, 90 days for a priority technique at Hansa Mutual, but a dependency has changed since. Expired applies only when the last passing test is older than the expiry.

  2. What does a test-to-change ratio of twenty mean for a technique?

    Show the answer

    C. Twenty changes accumulated on its dependency path before anyone verified it.
    The ratio counts production changes touching what the technique depends on between two passing tests. At twenty, twenty changes accumulated, and if the twentieth broke something the test cannot say which of them did.

  3. According to the chapter, which of the following does AI not make cheaper in the loop?

    Show the answer

    A. Independence between the side that tests and the side that is tested.
    Repetition is already cheap and variation and drafting are expected to become cheaper. Novelty, judgement, independence and safety stay costly, and a design that assumes otherwise moves the bottleneck without removing it.