When to Let AI Write Code and When to Take Control

The Delegation Dilemma

AI coding tools are powerful, but they're not a replacement for developer judgment. The most effective AI-assisted developers know exactly when to lean on AI and when to take the keyboard themselves. This skill is what separates efficient development from frustrating cycles of generate-rewrite-repeat.

Let AI Handle These Tasks

Boilerplate and Scaffolding

Creating new components, setting up project structures, generating CRUD operations. AI excels at repetitive patterns.

Test Generation

Unit tests, integration tests, edge case coverage. Claude can analyze your code and generate comprehensive test suites.

Documentation

JSDoc comments, README files, API documentation. AI reads your code and explains it clearly.

Data Transformations

Converting between formats, mapping data structures, creating type definitions from examples.

Refactoring

Renaming across files, extracting functions, converting promise chains to async/await.

Take Control for These Tasks

Security-Critical Code

Authentication, authorization, encryption, input validation. Always review AI-generated security code carefully.

Complex Business Logic

When the rules are nuanced and context-dependent, you need to guide the implementation step by step.

Performance-Critical Sections

Hot paths, algorithms with specific complexity requirements, memory-sensitive operations.

Novel Architectures

When you're pioneering new patterns or the codebase has unique conventions AI hasn't seen.

The Decision Framework

Ask yourself these questions before delegating to AI:

Is this a well-known pattern? If yes, AI will excel.
Can I verify the result quickly? If not, code it yourself.
What's the blast radius if it's wrong? Higher risk = more oversight.
Would I spend time explaining the context? If extensive, maybe code it yourself.
Is this repetitive? Perfect for AI delegation.

The Hybrid Approach

The best workflow often combines both approaches:

# Step 1: Let AI scaffold

"Create a PaymentService class with methods for processPayment, refund, and validateCard"

# Step 2: Review generated code

# Step 3: Take control for critical logic

*manually write the fraud detection logic*

# Step 4: Let AI complete

"Add error handling and logging to all methods"

Signs You Should Take Over

You've corrected the AI more than twice on the same task
The context explanation is longer than the code would be
You're not sure how to verify the output
The task requires understanding unstated business rules
Performance or security are primary concerns

Signs AI Should Handle It

You know exactly what you want but it's tedious to type
The pattern exists thousands of times in open source
You're creating variations of existing code
The task is well-defined with clear acceptance criteria
You can verify correctness by running tests