RAG vs. Fine-Tuning: The Wrong Question to Ask When Building AI Systems
A platform team is evaluating an LLM-based assistant, still in testing, meant to answer developers' architecture questions using the company's ADRs (Architecture Decision Records) and internal documentation. During an evaluation round, the team itself notices that the assistant recommended a service-to-service authentication pattern the company abandoned last year and, on top of that, suggested…
Two strategies for enhancing AI systems—fine-tuning and RAG—are often pitted against each other, but this framing overlooks a crucial question. The discussion should begin with the failure itself, rather than the technique used to address it. The article argues for this shift in perspective, emphasizing the importance of diagnosing the root cause of the problem before selecting a solution. This approach ensures that the remedy addresses the actual issue, rather than merely treating symptoms.
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