User Stories - A Legacy Project Artifact?

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The opinions in this article are those of the author and do not necessarily reflect the opinions of their employer.

The primary purpose of user stories and epics is to create a shared understanding of what needs to be built, ensuring alignment between the development team's execution and stakeholders' expectations. They also act as a form of contract or agreement, setting clear boundaries around what is to be delivered to prevent scope creep and manage expectations. This comes at the cost of stakeholders and development teams learning the language of "epics and user stories."

In the rapidly approaching future, where autonomous AI agents will directly converse with stakeholders and transform those discussions into functional deliverables within hours, the traditional framework of epics and user stories needs a reevaluation of its relevance. The agility and immediacy provided by such autonomous AI capabilities challenge the conventional need for structured intermediary artifacts like user stories, which have traditionally served as a safeguard and communication tool between stakeholders and development teams.

When AI Agents can accurately capture stakeholder requirements, interpret the nuances of their needs, and quickly iterate on feedback, IT project delivery will evolve to:

1. Direct Implementation from Conversations: The development process will lean towards direct implementation from stakeholder conversations rather than spending time on the legacy approach of writing epics and user stories.
2. Real-Time Feedback and Iteration: With the capability to prototype or even fully develop features rapidly, the iterative cycle of feedback and adjustments will occur in near-real-time, diminishing the need for epics and user stories as a medium for clarifying and refining requirements.
3. Dynamic Documentation: Instead of epics and user stories, documentation will become a dynamic, AI-generated and maintained record of evolving project requirements and stakeholder intentions, serving more as a historical log than as upfront specifications.
4. Enhanced Communication Channels: The reliance on structured formats for capturing requirements will be replaced by more fluid, natural language processing and understanding, with AI translating stakeholder needs into actionable development tasks without the intermediary step of crafting user stories.

In this context, the relevance of user stories will slowly fade away, especially their role in adding friction and stability to the requirements being addressed. Instead, the emphasis will be on the AI's ability to ensure mutual understanding, accurately translate needs into deliverables, and adapt to changes swiftly. This does not eliminate the need for clear communication, documentation, and agreement on what constitutes success for a project, but it suggests that these elements could be achieved through more direct and efficient means facilitated by AI technology.

While the foundational principles of clear communication and alignment between stakeholders and development teams remain paramount, the mechanisms to achieve these—such as user stories and epics—will evolve significantly in a landscape dominated by advanced, autonomous AI capabilities.