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Master directing AI coding agents to generate robust relational database schemas with explicit constraints, foreign keys, and precision types without hallucinations or data corruption bugs.
Generative AI coding tools operate on probabilistic pattern matching, not database administration. If you provide a casual prompt like 'create an e-commerce database', the AI guesses and makes dangerous architectural assumptions.
Common AI hallucinations include: table IDs without PRIMARY KEY, currency stored as floating-point numbers (FLOAT/REAL) triggering monetary calculation bugs, and omitted FOREIGN KEY relations.
Golden Rule 1: Explicit Identity & Unique Constraints. Always require a PRIMARY KEY on every entity and enforce UNIQUE constraints on credentials like email.
Golden Rule 2: Foreign Keys & Referential Integrity. Always state exact relationships (e.g. orders.user_id references users.id) to prevent orphaned records in production.
Golden Rule 3: Financial Precision & Audit Timestamps. Never store money as floating decimals; use INTEGER in minor currency units (cents or whole currency). Always mandate created_at with CURRENT_TIMESTAMP.
Imagine telling a general contractor: 'Build me a two-story retail shop', without providing architectural blueprints for foundation depth, concrete rebar specs, or load-bearing pillars. The building might look presentable initially, but the moment you load heavy merchandise upstairs, the structure sags and cracks because its foundations were never calculated. Prompting an AI for database schemas is delivering structural engineering blueprints: when you define strict column constraints and relational links, the AI has zero room to hallucinate fragile architecture.