M01-05 · AI-Assisted Software Development

Application Architecture & Programming Patterns

Teaches the architectural concepts and programming patterns that underlie modern web applications. Covers request lifecycle tracing, processing patterns (queues, batch, pub/sub, streaming), concurrency and race condition management, API design patterns (REST, webhooks, pagination, rate limiting, WebSockets), architecture decision-making (monolith vs. microservices, serverless), database modeling, and caching strategies. Students develop the architectural thinking needed to participate in — and eventually lead — system design discussions.

35 Hours

9 Learning objectives

Evaluate Bloom's ceiling (?)

6 Competencies

What You'll Be Able To Do

Learning Objectives

Objectives

Depth

Trace a user action through the complete request lifecycle: browser event, frontend handler, API request, backend processing, database query, and response rendering Analyze
Select appropriate processing patterns for different workloads: synchronous request/response, background jobs (queues), batch processing, scheduled tasks (cron), event-driven (pub/sub), and real-time (WebSockets/streaming) Evaluate
Identify and resolve concurrency issues: race conditions, stale data, idempotency requirements, and optimistic vs. pessimistic locking Analyze
Design RESTful APIs with proper endpoint structure, pagination, rate limiting, error responses, and versioning Create
Implement webhook integrations: sending, receiving, verification, retry logic, and failure handling Apply
Evaluate architecture decisions (monolith vs. microservices, serverless vs. traditional, build vs. buy) using team size, scale, and operational complexity as criteria Evaluate
Design database schemas with appropriate normalization, indexing strategies, and migration paths for evolving requirements Create
Apply caching strategies at appropriate layers (browser, CDN, application, database) with explicit invalidation policies Apply
Read and evaluate AI-generated architecture proposals, identifying over-engineering, missing failure modes, and inappropriate pattern choices for the given scale Evaluate

Levels: Remember · Understand · Apply · Analyze · Evaluate · Create — highest demands most original thinking.

Core Competencies

What You'll Master

Request Lifecycle Understanding

Tracing actions through frontend, API, backend, and database layers; understanding data flow and transformation at each layer.

Processing Patterns

Selecting and implementing appropriate patterns (sync, async, batch, event-driven, streaming) for different workload characteristics.

Concurrency Management

Identifying race conditions, implementing idempotency, choosing appropriate locking strategies.

API Design

RESTful patterns, webhooks, pagination, rate limiting, error handling, versioning, GraphQL awareness.

Architecture Decision-Making

Evaluating architectural tradeoffs for team size, scale, and operational constraints; participating in architecture discussions.

Data Architecture

Schema design, indexing, caching strategies, data modeling for evolving requirements.

Portfolio Artifact

What You'll Build

Architecture Design Portfolio — Student designs the architecture for a realistic application (multi-tenant SaaS with external integrations): system architecture diagram, API design (10+ endpoints with documentation), database schema with migration strategy, processing pattern selections with rationale (which operations are sync vs. queued vs. scheduled), a webhook integration specification, and an architecture decision record (ADR) evaluating 2 significant tradeoffs (e.g., monolith vs. microservices, build vs. buy for auth).

Tools You'll Use

Industry Tools, Not Toy Projects

VS Code / Cursor

Professional code editors for implementing architectural patterns and reviewing AI-generated code.

Claude Code

AI coding assistant for generating architecture proposals, API designs, and schema definitions to evaluate.

PostgreSQL

Relational database for schema design, indexing strategies, and query optimization practice.

Redis

In-memory data store for caching strategies, session management, and queue implementations.

Postman

API development and testing platform for designing, documenting, and testing RESTful endpoints.

Miro / Excalidraw

Diagramming tools for creating system architecture diagrams, data flow visualizations, and design documents.

Next.js / Express

Full-stack frameworks for implementing architectural patterns in real applications.

Prisma

Type-safe ORM for database schema management, migrations, and relationship modeling.