Proactive Impact Analysis to Fulfill the "AI Dev Team" Promise

[inspiration88]

Problem Statement

Currently, when the AI is given a task, it operates with a limited, short-sighted context. It executes the immediate instruction correctly but often fails to understand the broader implications of that change across the entire codebase.

This leads to unintended side effects, architectural inconsistencies, and subtle bugs. As a result, the developer must act as a "micromanager," manually reviewing every change and anticipating the problems the AI couldn't foresee. This undermines the core promise of an "AI-Powered Dev Team" and disrupts development flow.

Proposed Solution

Implement a Proactive Impact Analysis Engine. Before writing any code, the AI should perform a task-driven analysis to understand the full scope and consequences of a request.

The workflow should be:

1. Task-Driven Analysis: When a task is given (e.g., "Refactor the login form"), the AI identifies the primary code entry points.
2. Dependency Tracing: From those entry points, it traces all relevant connections—component usage, function calls, type dependencies, related tests—to build a "context graph" of the affected area.
3. Impact Analysis & Planning: Using this graph, the AI analyzes the potential ripple effects of the change.
4. Confirmation Before Execution: The AI presents a summary of its findings and a clear execution plan for the user's approval.

Example User Story

User:

Change our primary button style to be blue and more rounded.

Current AI (Implied Behavior):
Might change one CSS class in one file, potentially missing other definitions or breaking visual consistency.

Proposed AI (The New Dialogue):

Analysis Complete: The primary button style is defined in Button.tsx and uses tokens from theme.config.ts. This component is used in 17 places across the app.

Proposed Plan:

1. Update the color token in theme.config.ts.
2. Adjust the border-radius in Button.tsx.

Impact: No breaking changes detected. The Storybook story for this component will be updated.

Proceed? (Y/n)

Benefits

• Fulfills the "AI Dev Team" Promise: Elevates the AI from a simple tool to a trusted partner with agency and foresight.
• Reduces Technical Debt: Prevents architectural drift by catching breaking changes and inconsistencies before they happen.
• Enhances Developer Flow: Allows the developer to remain focused on high-level architecture and intent, not on micromanaging implementation details.

[BradKML]

Seconding this but it needs more analysis on how this can be optimized, and what other "cursor rules" tools are already out there to make assessment easier to do.