AI-Driven Epic Development: A New Paradigm

TL;DR

Traditional software development struggles to implement epic-level features directly. We propose a new methodology using a multi-agent AI system to manage complexity and accelerate delivery. By decomposing epics into version-controlled design documents, we enable specialized AI agents,Analyst, Designer, and Orchestrator,to execute development from high-level concept to pull request. This approach centers on a living design document that minimizes error drift and ensures continuous alignment, transforming how large-scale features are built. The core of this strategy is AI-Driven Epic Development.

The Challenge with Implementing Epics

In agile development, the hierarchy is clear: Epics break down into User Stories, which then break down into granular Tasks. This decomposition adds clarity and detail, making work manageable for human teams. We don’t build epics in one go; we work on decomposed stories by implementing tasks. This fundamental principle holds true in the age of AI-accelerated development, but the execution model is ripe for transformation.

The challenge has always been maintaining a shared understanding of the epic’s goals across multiple stories and teams. As work progresses, context is often lost, leading to misaligned implementations, duplicated effort, and “error drift”,the gradual deviation from the original technical vision. How can we keep the big picture in focus while executing the small details at machine speed?

A New Framework: AI-Driven Epic Development

We are pioneering a new approach that leverages specialized AI agents to manage the entire development lifecycle, from epic definition to code implementation. This framework for AI-Driven Epic Development is grounded in a centralized, version-controlled design document that serves as the single source of truth.

This living document, stored directly in the repository (e.g., design/JIRA-123-feature-x.md), becomes the anchor for all subsequent work, ensuring every agent and every action remains aligned with the epic’s strategic goals.

The Multi-Agent Workflow

Our methodology employs three distinct AI agents, each with a specialized role:

1. The Analyst Agent: Forging the Master Plan

The process begins with the Analyst Agent. Its primary function is to synthesize high-level requirements into a concrete technical vision.

• Inputs: The Analyst takes the epic-level feature request (e.g., from a Jira ticket) and ingests the existing source code of the repository.
• Process: It analyzes the request in the context of the current codebase to identify dependencies, architectural considerations, and potential challenges.
• Output: The agent produces a comprehensive design document. This isn’t just high-level prose; it may contain pseudo-code, architectural diagrams, API contracts, and data schemas. This document becomes the foundational blueprint for the epic.

By grounding the initial design in the repository’s reality, the Analyst ensures the plan is both ambitious and achievable, this also ensures a human is able to review and approve the technical decomposition of the epic.

2. The Designer Agent: From Epic to Story

Next, the Designer Agent steps in to decompose the master plan into actionable user stories.

• Inputs: The Designer references the epic’s central design document and a specific user story from the backlog.
• Process: It extracts the relevant context from the design document and generates a detailed technical specification tailored to that specific story. This specification is then formatted and published as a GitHub issue, creating a clear, self-contained work package.
• Output: A well-defined GitHub issue containing all the technical details required for implementation, directly linked to the overarching epic design.

The specification is transient, it only lives as long as the PR, so it does not belong in the repo with code. By using GitHub issues, humans are able to step in, review, and adjust the technical specification before we delegate tasks for implementation.

3. The Orchestrator Agent: From Design to Code

With a clear technical spec in hand, the Orchestrator Agent takes over.

• Inputs: The GitHub issue created by the Designer.
• Process: The Orchestrator breaks the specification down into a sequence of coding tasks. It then executes these tasks,writing, modifying, and testing code,until the requirements of the GitHub issue are fully met.
• Output: A pull request ready for review and merging.

The Orchestrator can typically run without human oversight, however we always ensure that the Orchestrator’s final output is reviewed before merging a PR!

Closing the Loop: The Self-Healing Design Document

A plan is only useful if it reflects reality. As code is implemented and merged, the world changes. Our framework accounts for this with a crucial final step: truing up the design.

After a PR is merged, the Analyst Agent is re-engaged. Its new task is to update the central design document to reflect the changes introduced by the implementation. This is achieved with a simple but powerful command that shows what has changed in the codebase since the design was last updated:

git diff $(git log -1 --pretty=format:"%H" -- design/JIRA-123-foo-bar.md) src/

This command provides a precise delta of all code modifications related to the epic, which the Analyst uses to revise the design document. This “self-healing” process ensures the blueprint is always up-to-date, allowing subsequent stories to build upon the latest architectural reality without manual intervention.

When multiple stories are developed in parallel, we simply land all the code first and then run the true-up process once, reconciling all changes in a single, efficient step.

Key Takeaways

Adopting an AI-Driven Epic Development framework offers transformative benefits for engineering teams:

• Reduced Error Drift: A centralized, version-controlled design document acts as a constant anchor, ensuring all development work remains aligned with the epic’s goals.
• Increased Velocity: Specialized agents can operate in parallel, dramatically accelerating the decomposition and implementation of complex features.
• Enhanced Alignment: The living design document eliminates the need for constant meetings and re-alignment sessions. The plan is the code, and the code is the plan.
• Improved Onboarding: New team members (human or AI) can quickly get up to speed by reviewing a single, comprehensive, and up-to-date design document.

This methodology represents a shift from managing tasks to managing systems,a system of intelligent agents, grounded by a clear and evolving architectural vision.

Partner with Tech Celerate to Implement AI-Driven Workflows

At Tech Celerate, we don’t just write about the future of software development,we build it. Our expertise lies in designing and implementing advanced AI-driven frameworks that deliver measurable results. We help organizations move beyond simple code generation to create sophisticated, multi-agent systems that tackle complexity and drive unprecedented velocity.

We offer:

• AI Workflow Assessment: We analyze your current development processes and identify high-impact opportunities for AI integration.
• Custom Agent Development: We build specialized AI agents tailored to your unique workflows, tools, and technical environment.
• Framework Implementation: We guide you through the process of adopting an AI-Driven Epic Development model, from initial setup to full-scale deployment.
• Strategic Consulting: We partner with your leadership to develop a long-term vision for AI in your engineering organization, ensuring you stay ahead of the curve.

Ready to transform your development lifecycle and execute epics with precision and speed? Contact Tech Celerate today and let’s build the future, together.