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Day 3 of 5 · 60% complete
Professional codebases feel different from normal one’s. Professional code is modular. Each file does one thing. Each function does one thing. You can read any function in isolation and understand exactly what it does, what it needs, and what it returns — without reading anything else.
This structure isn’t an aesthetic choice. It’s the property that makes code debuggable, testable, reusable, and maintainable. And it’s the single pattern I’ve found has the highest leverage when prompting Claude Opus 4.8 for application code. Modular prompts — one module, one responsibility, complete specification — produce dramatically better output than monolithic prompts, even for experienced users of the formula.
Today I give you the four module patterns that cover 90% of application development. Validation. Storage. Business logic. UI rendering. Four templates, four prompts, four modules for SecureVault. By the end of today, seven of nine files are complete and the core application logic is working.
🎯 What You’ll Master in Day 3
The four universal module patterns — Validation, Storage, Service, UI
The exact prompt for each pattern — copy-paste, fill in, ship
How to keep modules from knowing too much about each other
The isolation test — how to verify a module works before integration
SecureVault: four core modules built and smoke-tested
⏱ 25 min read · 3 exercises · Claude.ai + code editor needed 📋 Before You Start:
- Completed Day 2 — have your securevault/ folder with contracts.js, utils.js, crypto.js
- Have the SecureVault module map and contracts handy to paste into prompts
Modular Code Patterns — Day 3 of 5
- Single Responsibility — The One Rule That Prevents Everything Else
- Pattern 1: The Validation Module
- Pattern 2: The Storage Module
- Pattern 3: The Service Module (Business Logic)
- Pattern 4: The UI Components Module
- The Isolation Test — Verify Before You Integrate
- Questions and Answers
Day 3 is the most productive day of the course — four modules, four exercises, SecureVault goes from foundation to functionally complete core. The AI Coding Day 3 covers how to read AI-generated code once you have it. Today we focus on how to ask for it in patterns that produce the right code the first time. Our CEH practice exam follows the same pattern philosophy — modular question banks loaded on demand, validation layer separating input from scoring, UI rendering decoupled from answer logic.
Single Responsibility — The One Rule That Prevents Everything Else
Single Responsibility Principle: each module should have one, and only one, reason to change. A validation module changes when validation rules change. A storage module changes when the storage mechanism changes. If a single file would need to change when either validation rules or storage mechanisms change, it’s doing two things — and it will produce bugs when those two concerns pull in different directions.
The prompt-level consequence: when you write a prompt for a module, you should be able to describe its responsibility in one sentence without using “and.” If your description is “this module validates input AND saves to storage,” you’re specifying two modules in one prompt. Split it. The resulting code will be cleaner, easier to test, and more reliable.
I test every module I specify against this rule before writing the prompt. I ask myself: “If the storage backend changed from localStorage to IndexedDB, which modules would need to change?” The answer should be exactly one: the Storage module. If the answer is “the Storage module and also the EntryService module and also the App module,” the storage concerns have leaked across module boundaries and the architecture needs fixing before any code gets written.
I’ve found that beginners struggle most with the service module boundary — it’s tempting to put validation logic inside the service because “it’s all part of creating an entry.” Resist that. The service calls the validator. The service doesn’t contain validation logic. That distinction means you can change your validation rules by editing exactly one file, with zero risk to the service, storage, or UI modules. That kind of surgical changeability is what makes AI-built codebases maintainable long-term, not just functional on day one.
Pattern 1: The Validation Module
The validation module is the gatekeeper. Every piece of data enters the system through validation. Nothing that isn’t validated ever reaches storage or business logic. The validation module’s only job is to accept raw input and return a typed result describing whether the input is valid and if not, exactly why.
Key properties of a good validation module: it has no side effects (it never writes to storage or the DOM), it never throws (it always returns a ValidationResult), it validates one thing per function (not “validate the whole entry” as one function — separate functions for title, content, category), and its error messages are user-facing (not “invalid input” — “Title must be between 1 and 100 characters”).
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