Chapters: 
Get Smart

Public-ready by Friday, July 31, 2026.
SappyFest weekend becomes the “walk away and let it breathe” deadline, not the night-before panic goblin. (Sappyfest)

Phase One goal

By July 31, Get Smart should be presentable as:

A practical method for turning messy content, unclear processes, and half-formed automation ideas into structured, traceable, testable workflows.

Not a recipe app.
Not an AI company.
Not a “consulting fog machine.”

A small, real business offering based on work already done.

Claims you can currently support

These are safe because Get Smart already demonstrates them:

Claim

Current evidence

I can identify a source of truth

Backdrop remains the source of truth

I can move messy content into structured exports

Backdrop CSV export exists

I can normalize content into machine-usable form

recipes_normalized.jsonl exists

I can distinguish trusted/runtime-ready records from review-needed records

runtime catalog + skipped/review flags exist

I can build repeatable update workflows

Camelot → Ansible → SSH → CSV → import → runtime JSON

I can document what needs review instead of pretending certainty

admin/report concept and review-required flags

I can help make demos testable

AACM questioning produced endpoint, input/output, token, mock/demo-mode, expected-output questions

I can define rules before automation

this is already the spine of Get Smart

Do not claim yet:

Avoid for now

Safer wording

“AI governance expert”

“automation and review-readiness support”

“compliance solution”

“compliance-readiness and traceability support”

“enterprise automation platform”

“structured workflow and evidence-first automation support”

“we automate your business”

“we prepare messy systems for safe, testable automation”

The Phase One build

Three outputs by July 31:

  1. Public landing page
    Clear offer, services, good fit/not fit, starter engagement.
  2. Get Smart proof page / case study
    Shows the method using the recipe system: source of truth, export, normalization, runtime catalog, review flags, repeatable refresh.
  3. Public persona profile
    Your “what I do” profile for LinkedIn/site/about page: business analysis, content systems, source-of-truth cleanup, test readiness, automation readiness.

Working backward

June 11–16: Name the method

Deliverable: Get Smart Method v0.1

Core pattern:

Messy reality → source of truth → structure → rules → review flags → trusted output

BA questions:

  • What exists?
  • Where is the source of truth?
  • What can be trusted?
  • What needs review?
  • What output is testable?
  • What should not be automated yet?

Build item:

  • Create one internal page/document called Get Smart Method
  • Add the recipe project as Proof Point 1
  • Add AACM as Proof Point 2, but only as “test readiness / demo readiness analysis,” not implementation

Test:

  • Can a stranger understand what Get Smart does in under 60 seconds?
  • Can every claim point to something real?

June 17–23: Evidence inventory

Deliverable: Claims and Evidence Table

Columns:

Public claim

Evidence

Status

Notes

Source-of-truth cleanup

Backdrop as source of truth

supported

recipes case

Normalized data

JSONL output

supported

recipes case

Review flags

skipped/review-required records

supported

recipes case

Repeatable workflow

Ansible refresh chain

supported

internal proof

Demo readiness

AACM test questions

supported

advisory only

Compliance readiness

traceability pattern

partial

careful wording

Build item:

  • One page or markdown file: claims-evidence.md
  • This becomes your anti-fog-machine device. Gorgeous little truth trap.

Test:

  • Remove any phrase that cannot be tied to evidence.
  • Replace inflated claims with “readiness,” “review,” “structure,” or “support.”

June 24–30: Service packaging

Deliverable: Three service pages or sections

Keep the pillars:

  1. Get Smart Content
    • content audits
    • source-of-truth cleanup
    • taxonomy/field cleanup
    • export/import planning
    • review-required flags
  2. Get Smart Operations
    • business rules
    • workflow mapping
    • acceptance criteria
    • test readiness
    • demo readiness
  3. Get Smart Governance
    • evidence trails
    • review gates
    • traceability
    • risk/gap summaries
    • automation boundaries

Test:

  • Each service must produce a concrete deliverable.
  • No service may promise magic, platform transformation, or “AI pixie dust.”

July 1–7: Landing page v1

Deliverable: Public-facing landing page draft

Suggested structure:

  1. Hero
  2. What I do
  3. The Get Smart pattern
  4. Services
  5. Proof point: recipe/content system
  6. Good fit / not good fit
  7. Starter readiness review
  8. Contact

Test:

  • No jargon without examples.
  • No claim without evidence.
  • No AI-first language.
  • No “consultant nebula” wording.

Here is a tighter version of the public page direction:

Get Smart

Make messy systems usable.

Get Smart helps small teams turn scattered content, unclear processes, and half-formed automation ideas into structured, traceable, testable workflows.

I help you get from:

  • information spread across too many places
  • processes that only work because one person remembers the steps
  • demos that look impressive but are hard to test
  • automation ideas built on unclear inputs
  • content or data that nobody quite trusts

to:

  • clear business rules
  • source-of-truth structure
  • normalized data
  • repeatable workflows
  • testable outputs
  • review-required flags
  • practical documentation
  • safer decisions about what should and should not be automated

Core principle

No action without evidence.
No automation without policy.
No confidence without traceability.

The Get Smart method

Messy reality becomes usable when we can trace it.

Get Smart works through a practical pattern:

messy information
→ source of truth
→ structure
→ rules
→ review flags
→ trusted output

The goal is not to pretend everything is certain.

The goal is to identify what is trusted, what needs review, and what is ready to support a repeatable workflow.

Services

Get Smart Content

For websites, catalogs, knowledge bases, recipes, documents, and operational content that need structure.

Deliverables may include:

  • source-of-truth review
  • content audit
  • field cleanup
  • taxonomy review
  • export/import planning
  • normalized data files
  • review-required flags
  • repeatable update workflow

Get Smart Operations

For teams with a process, product, or demo that needs to become testable.

Deliverables may include:

  • business rules
  • workflow mapping
  • use cases
  • acceptance criteria
  • demo readiness review
  • product validation checklist
  • risk and gap summary

Get Smart Governance

For teams that need evidence, review, and traceability before automation.

Deliverables may include:

  • decision tracking
  • review gates
  • input/output definitions
  • policy boundaries
  • automation-readiness review
  • compliance-readiness notes
  • documentation and handoff materials

Starter engagement

Start with a focused readiness review.

We identify:

  • what exists
  • what is unclear
  • what can be trusted
  • what needs review
  • what can be automated
  • what should not be automated yet
  • the smallest useful next step

The result is a practical plan, not a fog machine.

July 8–14: Proof page / case study

Deliverable: Get Smart Case Study: Recipe Content System

This page proves the method.

Structure:

Section

Content

Problem

recipes/content existed but needed structure

Source of truth

Backdrop

Export

CSV

Normalize

JSONL

Classify

runtime-ready vs review-required

Output

runtime catalog

Governance

repairs happen in Backdrop

Repeatability

Ansible refresh chain

Lesson

this pattern applies beyond recipes

Test:

  • Can the case study show the method without over-explaining the tech?
  • Can a non-technical client understand the business value?
  • Can a technical person see that it is real?

July 15–21: Public persona profile

Deliverable: About / LinkedIn / profile text

This should position you without locking you into one niche.

I help small teams make messy systems usable.

My work sits where content, process, data, and automation meet. I help teams identify sources of truth, define business rules, clean up scattered information, and turn unclear workflows into something structured, testable, and maintainable.

Recent work includes content normalization, Backdrop/Drupal data exports, repeatable update workflows, review-required reporting, automation-readiness planning, and demo-readiness analysis for technical products.

I am especially interested in systems where evidence matters: content catalogs, knowledge bases, operational workflows, AI-adjacent tools, product demos, and compliance-readiness work.

My default rule is simple:

No action without evidence.
No automation without policy.
No confidence without traceability.

Get Smart is the framework I use for this work: messy reality → source of truth → structure → rules → review flags → trusted output.

Test:

  • Does it sound like you?
  • Does it support business development?
  • Does it avoid sounding like a corporate costume?
  • Does it let you talk to content people, operations people, and technical people?

July 22–28: BA test pass

Deliverable: Phase One acceptance checklist

Phase One is done when:

Test

Pass condition

Landing page clarity

A stranger can say what you do

Evidence discipline

Every claim has proof or careful wording

Service clarity

Each service has deliverables

Good fit / not fit

Boundaries are visible

Starter offer

Someone knows how to begin

Proof point

Recipe system shows the method

Public profile

Your profile matches the business

AACM lesson captured

Demo-readiness becomes a service, not a detour

July 29–31: Publishable version

Deliverable: Phase One public release

Minimum public package:

  • landing page
  • about/profile blurb
  • Get Smart method section
  • recipe case study/proof page
  • starter readiness review offer
  • contact path

No need for perfection. Phase One is not the cathedral. It is the first solid bridge plank.

Starter offer

This should be the first thing you can sell.

Get Smart Readiness Review

For small teams with messy content, unclear workflows, or automation ideas that need structure before action.

Output:

  • current-state summary
  • source-of-truth map
  • risks/gaps
  • review-required areas
  • business rules draft
  • test/readiness checklist
  • smallest useful next step

This is concrete, bounded, and billable. It also lets you avoid unpaid rescue work, which belongs in the nearest procedural compost bin.

The real positioning

I would not lead with “consulting.”

I would lead with:

Get Smart makes messy systems usable.

Then explain:

We help teams turn scattered information, unclear processes, and untested automation ideas into structured, traceable workflows.

That gives you room for:

  • recipes
  • sites
  • content cleanup
  • Backdrop/Drupal work
  • business rules
  • demo readiness
  • automation readiness
  • AI-adjacent review
  • compliance-readiness

without pretending they are separate planets.

Phase One motto

Use this internally:

BA. Test. Build. Prove.

Not “brand first.”
Not “tool first.”
Not “AI first.”

Evidence first. Then structure. Then workflow. Then public claim.

That is Get Smart.

 

RULES FROM THE GET GO

voluntary, agentless, evidence-first intake model

No forced agents. No hidden reach. No trust without inspection.

Wanna play on our system? Show me the rubber stamp

Machines can connect voluntarily to a scanning/check-in service. The system evaluates what is visible, declared, or submitted, then produces a result:

  • approved
  • approved with warnings
  • review required
  • rejected / not eligible
  • unknown / insufficient evidence

Rubber stamp only when the evidence supports it.

The principle

No forced agents. No hidden reach. No trust without inspection.

Voluntary machine check-in and readiness assessment. 

The system evaluates what is visible, declared, or submitted, then produces a result:

  • approved
  • approved with warnings
  • review required
  • rejected / not eligible
  • unknown / insufficient evidence

Rubber stamp only when the evidence supports it.

What this means architecturally

The machine does not need a permanent installed agent.

Instead, it connects to a controlled endpoint and provides or exposes enough information for a scan.

Possible evidence sources:

  • machine identity
  • OS/version
  • patch status                                  <---
  • configuration summary                 <---
  • open service inventory                 
  • security baseline answers
  • software/package list
  • certificate status
  • vulnerability scan result                 <---
  • policy attestation                            <<=== Look, I knows
  • last update timestamp
  • human owner/contact                    <--- 
  • business purpose
  • network location or environment

Then Get Smart classifies the machine.

The Get Smart pattern becomes

Machine appears
evidence collected
rules applied
gaps identified
review flags assigned
status issued
trusted output recorded

That is exactly your existing pattern, just applied to infrastructure instead of recipes.

Recipe version:

content → source of truth → normalization → review flags → runtime catalog

Machine version:

machine → evidence source → scan/attestation → review flags → readiness status

Same skeleton. Different hat. Shinier clipboard.

Critical boundary

This should not be framed as hostile scanning.

Not:

“We scan every machine in your corporation.”

Better:

“Systems voluntarily present themselves for readiness assessment. Systems that do not present evidence are not approved.”

That avoids creepy surveillance energy and keeps the governance clean.

Status model

A nice Phase One classification set:

Status

Meaning

approved

Evidence meets current rules

approved_with_warnings

Usable, but has known issues

review_required

Human review needed before trust

insufficient_evidence

Not enough data to approve

rejected

Fails required rule

expired

Stamp is stale and needs reassessment

This is very Get Smart:

Not everything becomes true because a machine said hello.

Policy language

Add this to the Get Smart method:

Agentless readiness principle

Get Smart does not assume every system should require a permanent installed agent.

Where possible, systems should be able to present themselves for review through a controlled check-in or scanning process. The system provides evidence, the rules evaluate that evidence, and the result is classified.

A machine that cannot provide enough evidence does not receive a trust stamp.

The goal is not hidden surveillance or automatic control. The goal is clear readiness status based on visible, traceable evidence.

Business value

This gives you a strong differentiator:

Most security/automation systems say:

Install our thing everywhere.

You are saying:

No. First prove what needs to be known, what can be checked, what needs review, and what should happen when evidence is missing.

That is not anti-automation. It is sane automation.

Phase One addition

Add a fourth proof-pattern to the Get Smart framework:

Get Smart Machine Readiness

For systems that need to be assessed before they are trusted, connected, automated, or included in a workflow.

Deliverables may include:

  • machine intake rules
  • evidence requirements
  • check-in workflow
  • readiness classification
  • review-required flags
  • stamp/approval criteria
  • exception handling
  • expiration/recheck policy

The line I’d keep

They come voluntarily, bring evidence, and get classified. No evidence, no stamp.

That is the whole castle gate. Use it.

 

 

Project Plan