Start where uncertainty begins

One path from useful knowledge to a working business.

Work through Find → Validate → Build → Sell → Deliver → Operate. If a later step feels stuck, move back to the earliest missing piece of evidence.

Already have an offer or customers?

Do not restart for the sake of completeness. Pick the first sentence you cannot prove: “people want it” (Validate), “the offer works” (Build), “buyers choose it” (Sell), “customers get the result” (Deliver), or “the work repeats safely” (Operate).

Step 01

Find

Who has a painful problem worth solving?

Choose a specific person and a costly, frequent problem before choosing a tool.

Outcome

A narrow customer and problem hypothesis you can explain in one sentence.

Do this next

Write down one group you understand, one recurring frustration, and how they handle it today.

Where AI helps

Organize interview notes, surface patterns, and turn broad ideas into testable problem statements.

Keep human

Choose the people you want to serve and decide whether the problem is meaningful enough to pursue.

Evidence to move on

You can name the customer, the painful moment, the current workaround, and why change matters now.

Step 02

Validate

Will someone act, not just agree?

Test demand with conversations, commitments, and small experiments before building the full offer.

Outcome

Evidence that the problem is urgent enough for a real next step.

Do this next

Ask five relevant people about the last time the problem happened and request one concrete commitment.

Where AI helps

Draft interview guides, summarize objections, compare language, and maintain an evidence ledger.

Keep human

Read hesitation, ask uncomfortable follow-ups, and distinguish polite interest from commitment.

Evidence to move on

At least one qualified person commits time, access, a referral, a pilot, or payment to continue.

Step 03

Build

What is the smallest useful offer?

Turn the validated problem into the simplest deliverable that creates a meaningful result.

Outcome

A clearly scoped offer that can be delivered manually before it is automated.

Do this next

Define the input, output, boundaries, delivery time, and one promise your first version can keep.

Where AI helps

Create drafts, prototypes, checklists, and repeatable production steps from your specification.

Keep human

Set the promise, reject unnecessary features, and decide what quality is good enough to test.

Evidence to move on

A real prospect can understand the offer and receive a useful result from the current version.

Step 04

Sell

Why should this buyer choose this offer now?

Position, price, reach prospects, and ask for the first sale without hiding behind more building.

Outcome

A direct offer, a fair price, and a repeatable way to start qualified sales conversations.

Do this next

Write a plain-language offer and send it personally to three people who match the problem.

Where AI helps

Research public context, draft outreach variants, organize follow-ups, and summarize objections.

Keep human

Choose the price, make the ask, handle trust, and never let AI impersonate a relationship.

Evidence to move on

A qualified buyer pays, signs a pilot, or gives a specific objection you can test next.

Step 05

Deliver

How will the customer get the promised result?

Onboard, serve, support, and improve the outcome before trying to make the work autonomous.

Outcome

A dependable delivery path with clear ownership, checkpoints, and recovery when something fails.

Do this next

Walk one delivery from intake to outcome and mark every handoff, wait, decision, and failure point.

Where AI helps

Prepare materials, track open loops, draft updates, and verify that routine steps actually completed.

Keep human

Own the customer relationship, exceptions, quality bar, and any promise involving trust or risk.

Evidence to move on

The customer receives the promised outcome and you can explain what worked, failed, and changed.

Step 06

Operate

What proven work should become a supervised system?

Make repeatable work easier with AI while keeping permissions, evidence, and stop conditions visible.

Outcome

A documented operation that is cheaper or faster without surrendering judgment.

Do this next

Choose one stable workflow, document the happy path and exceptions, then automate only the reversible steps.

Where AI helps

Run bounded workflows, monitor schedules, maintain state, produce reports, and surface exceptions.

Keep human

Set authority, approve consequential actions, review evidence, and decide when the system must stop.

Evidence to move on

The workflow repeats with visible proof, bounded cost, clear escalation, and a tested recovery path.

Begin with real customer evidence

Start with a conversation, not a stack.

Your first useful action is to talk with a person who knows the problem. AI can prepare the questions and organize the evidence. It cannot decide whose pain deserves your commitment.

Return to Step 1