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AI Workflow Architect Worksheet

By March 10, 2026No Comments

Use this to design a workflow that actually holds up

Before You Start

This worksheet is for thinking through a workflow, not generating one automatically.

Do not use it to produce a copy-paste output by vibes.
Use it to force clarity before you build.

If you are designing an agent, orchestrator, reusable prompt system, or internal AI workflow, this is meant to help you think through the architecture deliberately.


0. Anchor the Artifact

What final thing should this workflow produce?

  • Real example artifact:

  • If no example exists, describe the target output:

  • Why is this considered good?

  • What must not be lost in reproduction?

  • Deployment mode:

    • one-off

    • repeatable personal workflow

    • reusable operator module

Stop if: the output is still vague.


0.5 Pattern Locks

What makes the example actually work?

Structural locks

What process moves must be preserved?

Surface locks

What quality / tone / rhythm / texture must be preserved?

Anti-patterns

What should future outputs avoid?

Stop if: you still can’t explain why the example works.


1. Use Case Bind

  • Exact use case:

  • Final deliverable:

  • Human role:

  • AI role:

  • Success condition:

  • Unacceptable failure condition:

Stop if: someone else wouldn’t understand the job.


2. Constraints

Hard constraints

Soft preferences

Must-preserve conditions

Forbidden failure modes

Time / effort tolerance

Reversibility requirement

Stop if: you don’t have at least one hard constraint and one unacceptable failure.


3. Runtime Reality

Guaranteed inputs

Optional inputs

Forbidden assumptions

Allowed tools / sources

Volatile inputs

Continuity assumptions

Insufficiency triggers

Stop if: you’re still designing for context the workflow won’t actually have.


4. Failure Profile

Likely shortcut behavior

Hidden-state / fake-success risks

Stage-mixing risks

Evidence / assumption laundering risks

Highest-cost wrong answer

Stop if: you haven’t named how the workflow is most likely to fail.


5. Architecture Shape

Candidate shapes

Why each fits or doesn’t

Selected shape

Reason for selection

Stop if: you chose the shape because it “sounds smart.”


6. Stage Construction

For each stage, define:

Stage name:

Objective:

Allowed evidence:

Prohibited moves:

Required artifact:

Advancement gate:

Collapse condition:

Recovery move:

Repeat for each stage.

Stop if: any stage has no artifact, no gate, or no collapse behavior.


7. Reliability Attack

Try to break the workflow.

  • Could the AI jump to the final answer early?

  • Could a stage be faked?

  • Could evidence boundaries be violated?

  • Could the final output look right without process compliance?

  • Are any transitions narrative rather than conditional?

  • Are any pattern locks merely decorative?

  • Will repeated use cause formulaic output?

Weaknesses found

Fixes needed

Stop if: you haven’t actually tried to break it.


8. Final Package Check

  • Is this workflow heavier than the job requires?

  • Does every stage materially reduce failure risk?

  • Is any stage present only for elegance or ceremony?

  • Is the quality gain worth the overhead?

  • Is it appropriate for the deployment mode?

Final decision

  • finalize

  • simplify

  • roll back and revise


The One Question That Matters

When building the workflow, do not ask:

What are the steps?

Ask:

What artifact must exist before the next move is allowed?


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