Good AI Task

AI compatibility

Writing a PostgreSQL migration script is squarely in AI's wheelhouse.

Good fit

AI can handle this.

Average across 1 submission.

82
avg / 100

The honest read

This is a well-scoped, technically precise coding task with clear success criteria: the script either compiles, runs correctly, and handles rollback or it doesn't. An AI code agent can produce a solid, production-ready migration script including dry-run logic, CHECK constraints, and indexes — though a human DBA should review the parsing logic for the concatenated column format before running on live data.

Aggregated across 1 submission.

The five dimensions

Repeatability

High

SQL migration scripts follow well-established patterns: ALTER TABLE, UPDATE with string parsing, CREATE INDEX, ADD CONSTRAINT, and transaction blocks. The structure is highly repeatable and AI has seen thousands of examples in training.

Ambiguity Tolerance

Medium

The core requirements are crisp, but the format of the concatenated `customer_info` column is unspecified — the agent must assume a delimiter or pattern, which could be wrong. Success is otherwise verifiable: the script runs, constraints pass, indexes exist, rollback works.

Data & Tool Availability

Medium

The agent doesn't need live database access to write the script, but without seeing actual sample data from `customer_info`, it must guess the parsing logic. If the user provides a sample row or format spec, this becomes high.

Error Cost

High

Running a bad migration on 2 million rows in production can corrupt data or cause downtime. However, the task explicitly includes rollback logic and dry-run mode, which significantly mitigates risk — the real danger is if someone runs the script without reviewing it first.

Human Judgment Required

Low

The technical decisions here — index types, constraint syntax, transaction wrapping, runtime estimation — are well-defined engineering choices with established best practices. A DBA review pass is prudent but the judgment required is minimal.

What an agent would need

  • Sample rows or a format description of the `customer_info` column (e.g., 'John Doe | john@example.com' or CSV-style)
  • PostgreSQL version to ensure compatible syntax for constraints and index options
  • Clarification on whether the migration should run in a single transaction or in batches for large-table safety
  • Definition of acceptable CHECK constraint rules (e.g., email regex pattern, non-null requirements)
  • Confirmation of whether the dry-run mode should use EXPLAIN, row count estimates, or a separate read-only query block

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