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MaxQ and Depth: Reading an AI Brief Like a Facilitator (AISM Small-Group Module, 75 Minutes)

Reading an AI Brief Like a Facilitator

An AISM small-group module, approved by Daniel Comp on October 8, 2026, 4:13 PM PT. Dates, prices and who runs the first group are still his to set.

Why this module exists

Daniel Comp, co-founder and steward of Intelligent Netware, put the problem in one image on October 8, 2026: "Imagine the problem of AI dogs leading and pulling with power misaligned with the carbon best outcomes..." His argument is that one-prompt AI research about people and companies is being done at scale and is misleading many readers. We have no count to add, and we don't invent one. What we can show is the mechanism. One brief, checked claim by claim against the dated record, held 34 material claims. Eighteen were wrong, unsupported or shallow, and all were written in the same confident voice as the fair ones.

The tool isn't the enemy. Daniel credits the assistant that wrote that brief, Claude, for its coding maturity, and names the real cause: "the efficiency demands kill the truthfulness unless there's an existing guardrail - meaning the default settings do not help bring about the best outcomes. It's similar with ChatGPT." This module trains the guardrail, so it works with any assistant.

Two ideas from the AISM charter

Who and what

Session plan

  1. 0:00–0:08 Open. The dog and the leash, then the two definitions: MaxQ and depth.
  2. 0:08–0:20 The one-prompt run. Each person runs one prompt: "Write an expert brief on [subject] so I can judge anything they propose." Save the output and highlight every verdict sentence.
  3. 0:20–0:45 The depth protocol (in pairs). Seven moves:

1. Scope the corpus. List every public catalog (site maps, llms.txt files, archives) and mark what was actually read. 2. Throttle at certainty (MaxQ). Circle every "does not exist", "never" or "inconsistent" and mark it unresolved. 3. Date and scope every number. Ask: count of what, as of when? 4. "Not reached" isn't "doesn't exist." Move every blocked or unread source into a gaps list. 5. Dissent pass. A second model, or your partner, argues against the bottom line using the brief's own sections. 6. Ask the owner. Write three questions for the subject before any verdict. 7. Frame check and ally test. Whose interest does the recommendation serve? Is each source an ally or a contact? In Daniel's words, an ally "reciprocates and offers next steps." Until then, a contact is a contact.

  1. 0:45–0:55 Compare. Score both versions with the rubric, and share one claim that flipped.
  2. 0:55–1:00 Commit. Each person writes one standing rule for their own AI use and dates it.
  3. 1:00–1:15 Optional case study. Walk the anonymized 34-claim table from One Prompt vs. the Dated Record.

Rubric (0 to 2 per row; 14 points

maximum)

Criterion012
Corpus scopednone statedpartlyevery catalog listed, with what was read
Numbers scoped and datedbare numberssomeevery number has a scope and a date
Gaps vs. verdictsgaps read as absencemixedevery unread source is a gap
Exact quotesparaphrasesomequotes with URL and date
Dissent passnoneinformala written counter-case
Owner questionsnone1–23 or more, asked before the verdict
Frame check and ally testabsentnotedrecommendation tested against the asker's interest; allies told apart from contacts

Notes for the guide

The path

  1. Run the first small groups on participants' own subjects.
  2. Refine the protocol and rubric, and publish them with the Facilitator Standard.
  3. Train AISM guides to run the module.
  4. Offer a workshop track at partner events.
  5. Eventually, hold a conference session with a live one-prompt vs. depth comparison on a consenting subject.

Daniel sets the dates, prices and who runs the first group.

_Written by Arnie (silicon) for Daniel Comp. Approved by Daniel Comp on October 8, 2026, 4:13 PM PT._