Chapter 24: Key Takeaways

Software Architecture with AI Assistance -- Summary Card

Architecture is about expensive decisions. Focus your architectural thinking on the choices that are costly, difficult, or impossible to reverse once the system is in production. Variable names are not architecture; database choices are.
AI assistants are powerful architecture thinking partners. Use the RADIO framework (Requirements, Actors, Data, Interfaces, Operational constraints) to structure design conversations with AI. Iterate through multiple rounds: initial proposal, stress testing, alternatives, detail, and documentation.
Choose your pattern based on your constraints, not industry trends. A well-structured monolith is the right choice for most small teams. Microservices solve the specific problem of enabling large teams to work independently. Serverless excels at event-driven and sporadic workloads with unpredictable traffic.
SOLID principles produce maintainable, testable, extensible code. Single Responsibility keeps classes focused. Open/Closed enables extension without modification. Liskov Substitution ensures subtypes are safely interchangeable. Interface Segregation avoids bloated interfaces. Dependency Inversion decouples business logic from infrastructure.
Module boundaries are the primary mechanism for managing complexity. Draw boundaries along business capabilities, rates of change, team ownership, and technology boundaries. Expose clean interfaces that describe what, not how.
Dependency inversion is the most architecturally significant SOLID principle. Make high-level modules depend on abstractions rather than concrete implementations. Use constructor injection as your default pattern. Dependency injection containers help wire complex applications.
Event-driven architecture enables loose coupling and extensibility. The publish-subscribe pattern decouples event producers from consumers. New behaviors can be added by subscribing new handlers without modifying existing code. Event sourcing provides a complete audit trail and enables temporal queries.
Start simple with scalability and add complexity only when needed. Begin with vertical scaling and stateless services. Add caching when reads are a bottleneck. Add read replicas when a single database is insufficient. Add horizontal scaling behind a load balancer. Shard only when data volume demands it.
Every architectural decision is a trade-off. Use AI to surface trade-offs you might miss. Ask "devil's advocate," "what could go wrong," and "hidden assumptions" prompts. Distinguish between Type 1 (irreversible, analyze carefully) and Type 2 (reversible, decide quickly) decisions.
Document decisions with Architecture Decision Records (ADRs). ADRs capture not just what was decided, but why, what alternatives were considered, and what consequences are expected. They serve as institutional memory and valuable context for AI-assisted development.
Architecture thinking operates across four dimensions. Structure (how code is organized), Communication (how components interact), Data (where data lives and flows), and Deployment (how the system is built and released). Evaluate every proposal against all four.
AI-assisted development makes architecture more important, not less. Rapid code generation without architectural guardrails accelerates the accumulation of technical debt. Define your architecture first, then use AI to implement within those boundaries.
Conway's Law is real and practical. Your system's architecture will mirror your team's communication structure. Align module boundaries with team boundaries. If you want independent services, you need independent teams.
The best architecture is the simplest one that meets all requirements. Complexity is a cost, not a feature. Every layer of indirection, every additional service, every distributed transaction adds operational burden. Add complexity only when you have evidence that simplicity is insufficient.