From Prompt Spaghetti to Bounded Contexts: DDD for Agentic Codebases

A JNTX system refers to a coding system that uses agents and prompts to ship new features and functionality. It often faces challenges as it scales, leading to complex integration issues.

The main challenge in scaling JNTX systems is managing complex integration issues, where prompts become too large and difficult to debug, often leading to broken systems and long deployment cycles.

The 'prompt spaghetti' problem occurs when the integration logic in JNTX systems becomes overly complex and unmanageable, resulting in prompts filled with parsing logic and integration instructions instead of being written in structured code.

Domain-driven design principles help by providing a structured approach to handle complexity through bounded contexts, contracts as schemas, anti-corruption layers, and context maps, which makes the system more maintainable as it scales.

A bounded context in domain-driven design refers to a defined boundary within which a specific domain model is applicable, ensuring clear responsibility and separation of concerns.

JNTX systems should avoid using natural language as an API because it leads to unstructured outputs and inconsistencies. Instead, structured schemas should be used as contracts to ensure reliable integration and communication between agents.

The four core patterns are: bounded context, contract as schema, anti-corruption layer, and context map. These patterns help manage complexity and improve maintainability.

Contracts and schemas in JNTX systems define structured expectations for agent outputs, enabling clear communication and integration between different system components.

CI gates automate pre- and post-deployment checks, tests, and validations, ensuring that contracts are adhered to and the system remains stable and consistent.

A context map is important in a JNTX system because it provides an executable configuration that describes and enforces the integration architecture, ensuring clear relationships between different contexts.