This post delivers a much-needed wake-up call for IT departments dreaming of building their own Retrieval-Augmented Generation (RAG) systems. The comparison to homegrown CRMs or CMSs is spot on—while the idea seems appealing, it’s a classic case of underestimating complexity.

The "It Looks Simple" trap is real. RAG might seem like a neat formula of “Vector DB + LLM,” but as the examples show, it quickly snowballs into a resource-intensive ordeal with unexpected challenges. From dealing with data ingestion quirks and document format headaches to tackling hallucinations and ensuring compliance, each task becomes a rabbit hole of its own.

The biggest takeaway? Just because you can build something doesn’t mean you should. Specialized, off-the-shelf solutions exist for a reason—they save time, money, and sanity while providing scalability and support.

Before diving headfirst into a DIY RAG project, consider this: would your time and talent be better spent focusing on what makes your business unique, rather than reinventing the wheel? It’s a question worth asking before you’re knee-deep in blown budgets and burned-out engineers.