The team celebrated the launch at the morning stand-up. The new feature, a smart summarizer for legal documents, went live without a hitch. The code was elegant in its simplicity. Most of the logic was a single API call to a third-party model, wrapped in some error handling. It felt like a miracle of modern engineering, building something so powerful with so little effort.
Then, six weeks later, the miracle stopped working.
The summaries became vague, nonsensical. Key clauses were missed. The JSON output format, once reliable, was now peppered with conversational filler. The dashboard lit up with customer complaints. The engineers stared at their code, but the bug wasn't there. It was somewhere else, inside a proprietary system a continent away, its internal state altered by a silent update they were never told about. They were helpless.
This is the new dependency crisis, and it’s fundamentally different from a buggy open-source library or a deprecated cloud service. When a dependency breaks in the traditional software world, you have recourse. You can fork the code, pin to an older version, or inspect the source to understand the failure. You have a degree of control.
When your core product logic is rented from a closed, foundational model, you have no control.
The cost of switching is brutal, and it’s not measured in engineering hours alone. Your entire stack of carefully crafted prompts, few-shot examples, and output parsers is a bespoke key cut for a single, ever-changing lock. Moving from one provider's top-tier model to another’s isn’t like swapping out a database driver. It’s like rewriting your application from scratch because the new programming language has a completely different understanding
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