The emergency board meeting at DataFlow Inc. was called for midnight. The company's main database had been corrupted, affecting thousands of customers. The CTO, Martin, assembled his best engineers.
"We need to fix this fast," Martin said. "I'll work with our AI tools to generate recovery scripts while you all tackle the infrastructure."
Four hours later, the engineers had stabilized the servers, but Martin was still struggling. His prompts to ChatGPT kept producing generic database recovery advice that didn't fit their specific architecture.
"Why isn't this working?" Martin muttered, typing yet another prompt: "How to recover corrupted PostgreSQL database?"
Emily, a junior developer, peered over his shoulder. "Mind if I try something?"
Martin, exhausted, and desperate, stepped aside.
Emily didn't start with the problem. Instead, she began feeding the AI context—layer by layer, like building a foundation before a house:
"Context: We're a fintech SaaS company running PostgreSQL 14.2 on AWS RDS with multi-AZ deployment. Our database schema has 47 tables with complex foreign key relationships. The corruption occurred during a failed migration at 8:47 PM EST affecting primarily the transactions and user_accounts tables. We have hourly snapshots, but the last clean backup is 6 hours old, meaning we'd lose critical financial data.
Current state: Database is running but queries on affected tables return ERROR: could not read block 8439 in file. We've already tried pg_dump (fails on corrupted blocks) and verified disk space isn't an issue.
Constraints: We cannot lose any transaction data post-backup. Downtime must be under 2 hours. We need to maintain audit trail compliance.
Available resources: 5 engineers, AWS support contract, read replicas are unaffected.
Goal: Recover all data with zero financial transaction loss while maintaining data integrity and audit compliance."
The AI's response was transformative. Instead of generic advice, it provided a detailed recovery plan specific to their architecture, including SQL scripts tailored to their schema, strategies to leverage their read replicas, and a step-by-step process that accounted for their compliance requirements.
They recovered everything. Zero data loss. 87 minutes of downtime.
"How did you know to include all that?" Martin asked Emily afterward.
"AI is like a brilliant consultant," Emily explained, "but one who just arrived from another planet. It has all the knowledge in the universe but no idea about your specific situation. Context isn't optional—it's oxygen."