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GEO

Stage 08 · Improve

Agent-Ready Web: Prepare for Machine-Initiated Journeys

Move beyond being readable in an answer. Design information, interfaces, permissions, and transactions so authorized agents can discover and safely act.

Outcome

Evaluate agent discoverability, machine-readable capabilities, authentication, permissions, state changes, and human oversight.

Prerequisite
Complete or review the previous stage: Operating system
Working effort
60 to 90 min learning + one working session
You leave with
An agent journey map and readiness backlog that separates content discoverability from executable capability.

Learn → Do → Prove

01

Learn the system

Learn the layers between AI-readable content and an agent that can safely complete a task through APIs, feeds, or protocols.

Build the mental model

02

Do the work

Map one customer job from discovery to action, including data contracts, permissions, failure states, and human approval.

Create the working artifact

03

Prove the result

Demonstrate a bounded machine-readable path or prototype and document its security and operational limits.

Check the evidence

Concept boundaries

Machine-readable capability

A clearly described action, input, output, and constraint that software can discover and interpret.

Publishing a description does not make the underlying action safe or executable.

Agentic journey

A task path in which an authorized agent discovers information, makes bounded choices, and may request or perform an action.

Autonomy should not exceed the identity, permission, and approval model.

State-changing action

An operation that creates, updates, purchases, books, sends, deletes, or otherwise changes a system or external commitment.

Machine readability never removes the need for authentication, authorization, validation, idempotency, and recovery.

Core lesson

01

Separate readable information from executable capability

An agent may understand a page yet have no safe path to complete the user's job.

Map the layers: discoverable information, structured facts, capability description, interface contract, authentication, authorization, confirmation, state change, receipt, and recovery. A gap at any layer changes what the journey can responsibly promise.

Static files and metadata can improve discovery. APIs, feeds, tools, or protocols can expose capability. Neither should imply permission to act on behalf of a person without the required controls.

  • Name the exact customer job.
  • Mark where information ends and state change begins.
  • Identify the human confirmation and recovery path.
02

Design the contract around failure

A useful interface declares what happens when data is missing, stale, duplicated, unauthorized, or partially completed.

Define inputs, validation, permissions, side effects, idempotency, rate limits, error states, confirmation language, receipts, and escalation. Treat observability and audit logs as part of the capability, not an afterthought.

Begin with read-only or reversible paths where possible. Expand autonomy only when the evidence shows the team can detect failure, contain impact, and restore a safe state.

  • List failure states before the happy path is approved.
  • Use least privilege for each action.
  • Provide a durable receipt and escalation owner.

Decision framework

Discover → understand → authorize → act → recover

How far can this journey safely progress today?

  1. 01

    Discover

    Can an agent find the correct facts and capability description?

    Fix canonical information and machine-readable discovery first.

  2. 02

    Understand

    Are inputs, outputs, constraints, and freshness explicit?

    Define the contract and validation before execution.

  3. 03

    Authorize

    Can identity, scope, and user intent be verified?

    Keep the path read-only or require human handoff until permissions are sound.

  4. 04

    Act and recover

    Can the system prevent duplicates, record the result, and recover from failure?

    Permit bounded state change only with confirmation, idempotency, audit, and recovery.

Worked non-client example

A service company wants an AI agent to book consultations directly from a public capability page.

  • Service information and availability are readable.
  • The booking endpoint has no idempotency key or scoped authorization.
  • Cancellation and human escalation are not represented.

Expose a read-only availability check and a human-confirmed booking handoff before allowing autonomous booking.

Discovery is ready, but the state-changing contract and recovery path are not.

A prototype can prove the bounded path works under test conditions; it does not establish production security or universal agent compatibility.

Reusable work template

Agent journey and capability contract

Map one customer job from discovery through recovery.

  1. 01

    User job and authority

    State the intended outcome, actor, and who may authorize each step.

  2. 02

    Discoverable facts

    List canonical sources, freshness, and machine-readable representations.

  3. 03

    Capability contract

    Define action, inputs, outputs, constraints, validation, and side effects.

  4. 04

    Permission and confirmation

    Specify identity, scope, least privilege, and human approval points.

  5. 05

    Failure and recovery

    List duplicate, timeout, partial, denied, stale, and cancellation paths.

  6. 06

    Audit and evidence

    Define logs, receipts, monitoring, owner, and production-readiness boundary.

Failure modes and corrections

Metadata equals capability

A file or schema is presented as proof that agents can complete the task.

Description does not provide an authenticated, reliable execution path.

Separate discovery evidence from executable capability evidence.

Happy-path autonomy

The flow handles success but not duplicates, partial completion, denial, or cancellation.

A state-changing failure can create real commitments or data inconsistency.

Design idempotency, receipts, recovery, and human escalation before autonomy.

Permission inherited from access

Because an endpoint is reachable, the agent is assumed to have authority to use it.

Reachability does not establish identity, scope, or user intent.

Require explicit authentication, authorization, and confirmation boundaries.

Practice exercise

Prototype one bounded agent journey

Choose a real customer job and stop the prototype at the last layer the current controls can support.

  1. 01Map discovery, understanding, permission, action, receipt, and recovery.
  2. 02Write the capability contract and failure states.
  3. 03Prototype a read-only, reversible, or human-confirmed path.
  4. 04Test denial, duplicate, stale-data, and handoff scenarios.

Proof artifact

An agent journey map, capability contract, bounded prototype evidence, and readiness backlog.

Completion rubric

  • Information and execution layers are distinct.
  • Authority and human approval are explicit.
  • Failure and recovery paths are testable.
  • The readiness claim stops at what the prototype actually proves.

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Apply the stage with a field tool

AI Agent Strategy

Map one customer job from discovery to action, including data contracts, permissions, failure states, and human approval.

Evidence boundary

Use the output for the decision it describes; do not treat a technical scan, self-assessment, or planning model as proof of live AI citations.

Open field tool

APPLY THE LEARNING

Move from the lesson to an inspectable next decision

Use the linked tool, diagnostic, or service only when its evidence base matches the decision you need to make.

Open the next action