Your AI Partnership

Most developers use AI in one of three broken ways. If any of these sound like you, don't worry — everyone starts here.

The three models that don't work

The Autocomplete Trap

You write most of the code yourself and let AI finish your sentences. It suggests variable names, completes function bodies, fills in imports. You're getting maybe 20-30% more throughput. Your IDE just got a bit smarter, that's all.

The Stack Overflow Trap

You paste problems into ChatGPT and copy-paste solutions back. Faster than searching, sure, but the answers are generic. They don't know about your database schema, your naming conventions, or the library versions you're actually using. You spend two hours integrating a solution that didn't account for your project's specifics.

The Unguided Generator Trap

You tell AI to build whole features without constraints. It picks its own architecture, invents patterns, and creates code that technically works but doesn't fit anything else in your codebase. Now you've got six different patterns for the same thing. Congratulations — you've automated technical debt.

The model that works

Give AI your decisions. Then get out of its way.

Decision	Who decides	Why
Domain entities and relationships	You	Requires business understanding
API contracts and shapes	You	Defines system boundaries
Database schema	You	Impacts everything downstream
Security model	You	Mistakes leak data
Error handling strategy	You	Affects user experience
Variable naming, imports	AI	Low impact, easily fixed
Test boilerplate	AI	Follows your existing patterns
Documentation wording	AI	Mechanical translation
CRUD operations	AI	Pure pattern repetition

The five-minute investment that saves five hours

Here's what the partnership looks like in practice. You write a Pydantic schema — 5-10 minutes of actual thinking about your domain:

class TaskCreate(BaseModel):
    project_id: UUID
    assignee_id: UUID
    due_date: datetime
    story_points: int = Field(default=3, ge=1, le=21)
    priority: TaskPriority
    description: str = Field(..., min_length=3, max_length=500)

From that single schema, AI generates the service layer (30 seconds), route handlers (30 seconds), database migration (20 seconds), test suite (45 seconds), and TypeScript types (20 seconds). Five minutes of your thinking, five minutes of AI execution, and you've got a complete feature that follows every convention in your project.

The compression timeline

Timeline	Compression	What's happening
Week 1	2x	Learning the partnership model
Month 1	4x	Patterns documented, AI follows them
Month 3	8x	Extensive pattern library built up
Month 6	10x	Every new feature fits established patterns

Four failure modes to watch for

1. Insufficient context — AI generates wrong patterns? Your docs need updating, not your prompts
2. Blind trust — Never merge code you haven't reviewed. AI writes confident nonsense just as fluently as confident correctness
3. Micromanaging — If you're dictating variable names to AI, you're doing it wrong. Focus on what and why
4. No quality gates — Type checking, linting, and tests catch AI mistakes automatically. Without them, mistakes ship to production