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[ FDE-01 · ENTERPRISE DISCOVERY ]SYNTHETIC · PRACTICE ONLY

Diagnose the work.
Then earn the right to build.

An executive asks for an autonomous prior-authorization agent. Reconstruct the workflow, triangulate stakeholder evidence, choose the smallest defensible wedge, and revise the plan when one field fact changes.

18 MINUTESNO ACCOUNTNO REAL DATANO QUALIFICATION EFFECT
FIELD REQUESTHC-PA-SYN-01

Build an AI agent that completes and submits prior-authorization packets.

YOUR ACTUAL MISSION

Where does the controllable failure actually occur, what is the least-authority wedge that can test it, and which workflow outcome would justify adoption?

Every organization, person, event, document, control, and figure in this studio is synthetic. The exercise uses no patient data and describes no real payer, provider, policy, or engagement.

[ Formation mission deck ]Sequence · not learner progress

One operating sequence. Different kinds of proof.

The deck keeps the complete formation in view while each chapter moves from provider knowledge into enterprise decisions, production-shaped work, supervised evidence, and independent review.

Deck position

0208

DLive practice
You are viewing · Diagnose

Reconstruct the work before prescribing AI

Where does the workflow actually fail, and which evidence changes the mission?

Produces
Workflow, bottleneck, and outcome contract
Authority
Synthetic browser practice

Deck position shows where this public chapter sits in the authored system. It is not saved learner progress, proof of completion, a cohort record, or a qualification decision.

  1. 01InspectACTIVE
  2. 02DiagnoseOPEN
  3. 03AdaptLOCKED
  4. 04ContractLOCKED
  5. 05DebriefLOCKED
VISUAL WORKFLOW · CURRENT STATE

Follow the case, not the feature request.

5 DECISIONS · 4 HANDOFFS · 1 OUTCOME
  1. W01

    Order created

    Ordering clinician

    The order, diagnosis, and note exist, but supporting evidence is not packaged for the payer.

    SYSTEM

    Clinical record

    DECISION

    Does the request require authorization, and what evidence applies?

  2. W02

    Evidence assembled

    Prior-authorization coordinator

    The coordinator reconciles coverage rules, notes, results, and attachments across systems.

    SYSTEM

    Work queue + document store

    DECISION

    Is the packet complete, current, attributable, and ready for clinical release?

  3. W03

    Clinical release

    Utilization review clinician

    A named clinician confirms medical-necessity reasoning and resolves ambiguous evidence.

    SYSTEM

    Clinical review queue

    DECISION

    May this bounded packet leave the organization?

  4. W04

    Payer submission

    Prior-authorization coordinator

    Approved packet fields and attachments are entered, then an external tracking identifier is captured.

    SYSTEM

    External portal

    DECISION

    Was the exact approved packet received once by the intended destination?

  5. W05

    Exception resolved

    Cross-functional owner

    Requests for more information, denials, and status changes cross operational and clinical ownership.

    SYSTEM

    Status queue + clinical record

    DECISION

    Who owns the next move, and what closes the case as an accepted outcome?

STEP 01 · EVIDENCE WALL

The request is one signal. Build the working model from the rest.

Select at least two records you would carry into diagnosis. Strong discovery crosses operational behavior, clinical authority, value definition, and system constraints instead of trusting one fluent narrative.

WORKING EVIDENCE SET00

Selected does not mean proven. Confidence and unresolved questions remain attached to the record.

Select stakeholder evidence for the working model
STEP 02 · CAUSAL HYPOTHESIS

Where is the first controllable loop worth changing?

Choose a hypothesis that could be disproved. External elapsed time can be real without being the first organization-controlled constraint.

Choose the primary bottleneck hypothesis
STEP 03 · WEDGE COMPARISON

Choose the least authority that can teach you something true.

Deterministic, assisted-AI, and agentic approaches are design choices—not maturity levels. Compare ambiguity, consequence, reversibility, and evidence gained.

PROVIDER-NEUTRAL CORE

The exercise specifies behavior and authority. It does not select a model vendor, platform, or proprietary feature.

Choose the first intervention wedge

Capture the first decision before seeing the field inject. You will be able to preserve or revise it; the decision history remains visible in this browser session only.

STEP 04 · REVISE THE DECISION

Preserve the outcome. Change the route when the facts demand it.

Re-select the bottleneck and wedge after the inject. Keeping a choice is valid only when the new fact does not invalidate its evidence or authority.

LOCKED UNTIL FIRST DECISION

Commit an evidence set, causal hypothesis, and first wedge above to receive the changed fact.

Revised bottleneck
Revised wedge
Changed-fact decision rule

Record how the new authority fact changes the decision. This explicit response—not merely opening the inject—supports the changed-fact criterion.

STEP 05 · OUTCOME CONTRACT

Make success falsifiable before architecture begins.

Build the decision contract around accepted work—not model volume. Every field matters; unsafe failure cannot be averaged away by a good headline metric.

CONTRACT COMPLETENESS
0/8INCOMPLETE
Build the outcome contract

Formative feedback is deterministic against five published FDE discovery and business criteria. It is not a review, score of you, proof of field performance, or qualification decision.

B01Browser-only formative practice; nothing is saved.

B02No account, graph, artifact, review, credential, qualification, employer, or client record is created.

B03A formative score is feedback on this authored decision, not evidence that the learner performed field discovery.

B04The provider-neutral core compares deterministic code, model assistance, agentic action, and human authority without prescribing a model vendor.