Stop Trusting the Embedding: How Real RAG Pipelines Actually Work

📰 Medium · Machine Learning

Learn how real RAG pipelines work and why trusting embeddings alone is not enough for accurate question answering

intermediate Published 27 May 2026
Action Steps
  1. Build a basic RAG pipeline using a library like Hugging Face's Transformers
  2. Run experiments to evaluate the performance of your RAG pipeline on your own data
  3. Configure your pipeline to use a combination of embeddings and other features, such as knowledge graph embeddings
  4. Test your pipeline on a variety of question types and datasets to identify areas for improvement
  5. Apply techniques like fine-tuning and data augmentation to improve the accuracy of your RAG pipeline
Who Needs to Know This

Data scientists and machine learning engineers can benefit from understanding the limitations of embeddings and how to build more robust RAG pipelines

Key Insight

💡 Trusting embeddings alone is not enough for accurate question answering, and a more comprehensive approach is needed

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🚨 Don't trust embeddings alone! Learn how to build robust RAG pipelines for accurate question answering 🤖

Key Takeaways

Learn how real RAG pipelines work and why trusting embeddings alone is not enough for accurate question answering

Full Article

A few years ago, getting a model to answer questions about your own data was simple. You wrote the FAQs into the system prompt, you wrote… Continue reading on Medium »
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