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AI Onboarding Journey

Surthrive Your AI Adventures

AI will disrupt every workflow — whether you’re building something new or transforming what already exists. The ones who surthrive don’t just automate. They own the setpoint. Five stages. One working system. One irreplaceable moat.

Each stage closes one false belief, collapses one constraint, and produces a deliverable that earns the next move — whether you’re a founder or a re-engineer.

1

Stage 1

The Call

AI is for people further along than us

What’s the one problem that won’t leave you alone — whether you’re building it or living with it?

Most people test AI on the wrong problem — something simple, low-stakes, and already half-solved. The problem that matters is the one you’ve quietly accepted as unavoidable. For a founder it’s the gap between the vision and what you can ship alone. For an existing business it’s the workflow that taxes every week. Name it first. Everything else follows.

Type here — your words will appear in the Executive Brief preview below.

Executive Brief — Preview

Type the workflow above — your Executive Brief preview will appear here with your words in it.

Executive BriefFree. Delivered in Discovery. CEO-facing.

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Stage 2

The Threshold

Our situation is too specific — AI won’t understand our context

Which of your constraints are truly fixed — and which are habits wearing the costume of rules?

Every workflow has inputs, steps, outputs, and judgment calls. The judgment calls stay human. Everything else is pattern. Most teams can’t see the structure in their own operations because they’re inside it. Classification makes it visible.

“Clean data first” is an artifact constraint masquerading as a real one. RPA required it. LLMs don’t. The actual barrier is scattered data: business logic spread across five platforms, senior staff spending 45 minutes assembling context before every call. One onboarding rebuilt from 4.5 hours to 5 minutes — not by cleaning data, but by mapping where it moved.

Classify your workflows: Real, Artifact, or Hybrid?

Artifact constraints are the highest-leverage AI targets — they feel fixed but can move.

Real

Cannot change — law, regulation, physical limit, contracted deadline

Artifact

Feels real but is policy, habit, or belief — chosen once and forgotten

Hybrid

Partly real, partly artifact — the real part stays, the artifact part can move

First Principles PlaybookConstraint MapFree worksheets. Fill before the meeting.

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Stage 3

The Trials

We tried it — results were too generic

What would you tell a new contractor to get good work on day one?

Generic output is a symptom of a generic brief — not a limitation of AI. Brief it the same way you’d brief a new contractor: context, constraints, examples of good output. The comparison tells you everything.

1

What does the week look like right now?

Map it. Where does time go that shouldn't?

2

Follow one piece of work from start to finish — how many platforms does it touch before it's done?

Count the hops. Each hand-off is a flow problem, not a data quality problem.

3

What does your best week look like?

Not the fantasy — the realistic best. What made it work?

4

Which workflow, if it ran automatically, would free the most time or close the most revenue?

Name one.

5

What would have to be true for an AI system to do that job — and what would stop it?

Obstacles first.

Executive Brief — Preview

Type the workflow above — your Executive Brief preview will appear here with your words in it.

ROI & Capital Memo

The Discovery session produces a 1–2 page decision instrument: the selected workflow, time-cost baseline, automation estimate, and break-even timeline. Output: Go / Conditional / No-Go. The condition makes the decision reviewable — not a gut call.

ROI & Capital MemoCo-produced in the Discovery session with your numbers.

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Stage 4

The Abyss

AI adds overhead we don't have time for

Which part of your week repeats with the same inputs every time?

The overhead disappears once the context is built into the system. Second run faster. No new thinking required. That’s the proof — not the feeling.

Systems Blueprint

Automated: Repeating inputs, consistent steps, defined output
Human checkpoint: Quality gate, judgment call, exception handling
Setpoint owner: Who decides what ‘good output’ looks like

Who owns the AI setpoint for each workflow

How quality is measured and by whom

What triggers a human review

What the rollback procedure is

Systems BlueprintChange GuideDelivered in the AI Sprint.

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Stage 5

The Return

AI will displace our people

When the agent runs the workflow — what decisions can only you make?

You came through the trials. Something runs without your constant attention. Now the return: you own the setpoint. AI runs the loop — you own what “done well” means in your domain, your market, your customers. That understanding is irreducible. Whether you built something new or transformed something existing, that judgment is the moat. The Shared Dream begins here.

The Moat Question

Who owns the taste model? When agents handle execution, the irreplaceable asset is knowing what “done well” means in your domain, your market, at your standard. For a founder: the product taste only you can set. For a re-engineer: the operations standard only your team has earned. That judgment — accumulated through real decisions — is the moat.

Review your journey

1Awareness

The task you've quietly accepted as unavoidable is the first candidate

AI is for tech companies, not us

What's the one task across your business that everyone hates and nobody has fixed?

  • The task that matters is the one you've been quietly avoiding — complex, repetitive, high-stakes
  • Surprise is the proof. No surprise means wrong task — pick a harder one
  • Start with the reward: what does a better version of this week look like?

Biases: +

1 / 5

By 2030, the ventures and businesses that surthrive are the ones who own the taste model — not the ones that bought the most software.

The Model

Partnership, Not Pipeline

Give the real thing away. Keep nothing important behind a gate. Let the quality of the work be its own proof.

1

Put the work in the window

Mental models, meeting protocols, diagnostic templates on /docs. If a competitor can copy it, the moat was never the content.

2

Let them try before you ask

A business that has run its own Constraint Map already knows what good looks like. They don't need convincing — they need the rest.

3

Trade reciprocity, not pressure

The model works only when the free asset stands alone as useful even if they never engage further.

Tier 0

Trojan Horse

Open

Pack delivered:

Executive Brief
Book Discovery
Tier 1

AI Discovery

30–60 min

Pack delivered:

First Principles PlaybookConstraint MapROI Memo
Book AI Sprint
Tier 2

AI Sprint

2–4 weeks

Pack delivered:

Systems BlueprintChange Guide
Platform subscription
Tier 3

AI Operations

Ongoing

Pack delivered:

Offer One-PagerFull work-chart
Scale

The Play

Berley, Not Chase

No chase, no pitch

If the ideas are useful, people transform value, the ecosystem grows, goodwill spreads.

Funnel → fishball

A fishball is a self-reinforcing community that circles value back. The five counterparties feed each other.

Meaning over money

When value can be measured and exchanged directly, the real question becomes: what does the business actually want to be doing, and who with?

The movement we need is on your shoulders

Context

Questions

What is the single workflow that, if improved first, creates the most visible difference in the business week — and how do you find it before the client can name it?

  • What distinguishes an artifact constraint from a real one when the team has lived with both for years?
  • How do you write an ROI Memo that gives a CFO a genuine go/no-go — not a sales estimate dressed as analysis?
  • Who owns the taste model inside the business — and is that person building it through real decisions or routine ones?
  • At what point does the partnership shift from delivering automation to developing the business's own capability to direct AI?