Introduction
Traditional application design, especially in RESTful APIs, has long relied on resource-centric operations. While effective for basic CRUD operations, this model begins to falter when business requirements become context-aware, multi-step, or personalized.
This article introduces a forward-looking concept: Intent-Based Application Design, a method for shifting your architecture to focus on what the user wants to accomplish, rather than just the endpoint being called.
This architectural style is increasingly relevant in the era of AI-driven systems, adaptive interfaces, and natural language inputs. With recent advancements in .NET 8, implementing this concept has become more practical than ever.
What is an "Intent" in Software?
An intent refers to the desired outcome or goal behind a request. It goes beyond simply invoking an endpoint; it encapsulates why the user is making the request in the first place.
In a traditional API call, we expose specific verbs for resources, such as creating an invoice, fetching a customer, or updating an order. However, with intent-based design, we begin to model the reasons behind these actions and create backend flows that interpret and respond accordingly.
This results in software that adapts to the context, aligns more closely with user expectations, and enables future-ready integrations, such as AI-powered interfaces or autonomous systems.
Why Now: The Role of .NET 8
With the release of .NET 8, several features make intent-based architecture more achievable.
- Minimal APIs with endpoint filters enable lightweight routing logic based on context, rather than adhering to strict RESTful patterns.
- Source Generators and Roslyn integration enable dynamic code behavior based on user-defined intent types or inputs.
- Middleware pipelines provide a natural way to intercept and respond to intent flows across multiple stages.
- Command/Query pipelines (e.g., MediatR) model intent handlers in a modular, testable, and extendable fashion.
These features combine to provide developers with tools to design intent-aware systems without compromising the benefits of existing architectural patterns.
Real-World Scenario
Imagine a hospitality system serving personalized experiences. A guest interacting with a restaurant's tablet may want to "find the best dinner option right now."
- A traditional REST system might require five separate calls: guest profile, menu, offers, availability, and pricing.
- In an intent-based system, the front end simply communicates: I want the best dinner option for this guest, at this time, in this location.
The backend interprets this and coordinates necessary services to return a personalized, decision-ready recommendation.
This minimizes front-end logic, improves performance, and keeps business logic centralized and cohesive.
Advantages of Intent-Based Architecture
- Improved User Experience: Clients interact in terms they understand, and the system takes responsibility for interpreting and acting accordingly.
- Future-Ready: AI tools like LLMs integrate seamlessly with intent-based APIs. A natural language request can be transformed into structured backend commands.
- Cleaner Interfaces: Rather than exposing dozens of granular endpoints, you model workflows that express a clear business purpose.
- Adaptable Business Logic: Intent handlers can evolve over time. For example, an intent to "place an urgent order" can later include fraud checks, fast delivery routing, or manager overrides, without needing new endpoints.
- Context Awareness: Each intent can embed context, including user preferences, time of day, device type, or location, allowing for richer and more intelligent behaviors.
Challenges to Consider
- Intent Modeling Complexity: Determining the correct set of intents for a domain requires a deep understanding of the business.
- Debugging and Observability: Tracing intent flows requires more than just logging endpoint names, it also involves tracking the flow of data. Intent identifiers and correlation IDs are essential.
- Standardization: Without care, each team might model intents differently, making reuse and coordination harder.
- Skill Gap: Not all developers are trained in domain-driven design or intent modeling. Team education may be required.
Opportunities with AI
An exciting evolution of this architecture is integrating it with language models. A chatbot or voice interface can interpret a natural input, map it to an intent, and call the backend directly.
For example
"Show me pending invoices from last week."
This could be translated into an internal GetInvoicesIntent with filters applied. The backend remains unchanged, while the interface layer becomes smarter.
Intent-based design provides a bridge between traditional business systems and AI-native experiences.
Final Thoughts
The future of application development is shifting from rigid resource models to flexible, context-aware intent systems. As interfaces evolve beyond screens and buttons into conversations and predictions, the way we architect our backends must also evolve.
.NET 8 provides the tools and performance necessary to implement this shift. By investing in intent modeling today, you not only improve the current user experience but also prepare your application for AI-driven, adaptive interfaces tomorrow.
Further Reading and Next Steps
- Consider identifying common user actions in your domain and drafting an intent model.
- Explore how endpoint filters and minimal APIs can simplify routing based on those intents.
- Think about how your application might one day receive requests from LLMs or voice assistants, and how well it would understand them.
If you’d like to see a follow-up guide on implementing a basic Intent Router in .NET using CQRS, let me know.