map

To map an external feature prototype into an existing product, you analyze candidate modules, routes, workflows, and bounded contexts to identify the best implementation surface. This ensures the new feature aligns with current information architecture without inventing unsupported product details.

Feature mapping is the process of comparing a new feature artifact against existing bounded contexts and surfaces to determine integration fit. It identifies required API changes, storage needs, and permission adjustments for accurate product planning and risk analysis.

You generate an MVP backlog and risk analysis by evaluating the feature artifact against current data and permission requirements. This produces blockers, assumptions, deferred work, and product decisions needed for prioritized backlog planning.

Feature mapping supports data and AI storage requirements analysis for PoCs by identifying required inputs, entities, and lifecycle implications. It maps these data structures against existing storage needs to prevent unlabelled schema proposals during integration.

You can use feature mapping to analyze admin screens and workflow permissions without applying product code changes. It focuses on route, module, and information-architecture analysis to determine permission boundaries and integration fit safely.

A key limitation of feature mapping is that it strictly avoids inventing unsupported routes or unlabelled schema proposals. It only analyzes existing bounded contexts to find the best implementation surface, meaning it cannot design entirely new product architectures from scratch.