User Stories | HAP Analysis

The Approach

User Stories emerged from Agile methodologies as a lightweight way to capture software requirements from the end user's perspective. The approach centers on understanding who needs a feature, what they need, and why it matters to them.

This artifact assumes a clear separation between the user (human) and the system (passive tool). The user initiates all actions, and the software responds predictably. There is no consideration for autonomous behavior, learning, or evolving capabilities because traditional software doesn't possess these qualities.

User Stories work exceptionally well for conventional applications: CRUD operations, workflow automation, reporting dashboards, and any system where the human remains the sole decision-maker and the software executes predefined logic.

Artifact Outline

Standard Format

"As a [role], I want [goal/action] so that [benefit/reason]."

Role

The type of user or stakeholder who will use this feature. Defines the perspective and context.

Goal

The specific action or capability the user wants. What they need the system to do.

Reason

The business value or benefit achieved. Why this matters to the user or organization.

Optional Components

Acceptance Criteria: Specific conditions that must be met for the story to be complete
Story Points: Relative effort estimation for sprint planning
Priority: Business importance ranking (MoSCoW, numerical, etc.)

Example

User Story

                                # Story

                                As a customer support manager,

                                I want to view a dashboard of open tickets sorted by age

                                so that I can prioritize which issues need immediate attention.

Acceptance Criteria

GIVEN I am logged in as a support manager
WHEN I navigate to the dashboard page
THEN I see all open tickets sorted by creation date (oldest first)
AND tickets older than 48 hours are highlighted in red
AND I can click any ticket to view its full details

Why This Works for Traditional Systems

This user story works well because the system behavior is entirely predictable and user-initiated. The dashboard displays data, the user reviews it, and the user makes decisions. There's no autonomy, no learning, no evolution. The software is a passive display of information that the human acts upon.

Limitations for AI Systems

User Stories break down when applied to AI-powered systems because they cannot express:

Evolving capabilities: The agent may develop new abilities over time that weren't anticipated
Trust dynamics: The relationship between human and agent changes as confidence builds
Autonomous actions: The agent may act without explicit user initiation
Shared responsibility: Accountability becomes distributed between human and agent

For systems involving AI collaboration, consider Agent Stories or HAP Plans.