📘 Introduction Artificial Intelligence is undergoing a significant shift. For years, generative models have captured headlines — from creating text to generating images. But a new wave is emerging: Agentic AI. So, how does Agentic AI differ from Generative AI? Are they competing paradigms — or complementary forces in the AI ecosystem? In...
📘 Introduction Artificial Intelligence is evolving rapidly. From rule-based systems to generative models, we are now entering a new frontier: Agentic AI. But what exactly is Agentic AI? How does it differ from traditional AI systems, and what opportunities or risks does it bring? In this post, we'll explore...
📘Introduction Large language models (LLMs) have revolutionized artificial intelligence, unlocking new levels of understanding and creativity. But AI’s journey is far from overnight — it’s been shaped by decades of innovation, setbacks, and breakthroughs. In this post, we’ll explore the pivotal moments in AI’s history — from the...
📘Introduction FastAPI is a modern, high-performance web framework for building APIs with Python. In real-world applications, you'll often need to connect to a relational database like PostgreSQL to store and retrieve data. But building that connection securely and cleanly—especially across development, staging, and production environments—requires a...
Introduction In the age of data-driven decision making, having a powerful data architecture is crucial. The Medallion Architecture is a proven data architecture pattern that helps in organizing data across different layers of refinement. When combined with dbt (data build tool), it becomes a powerful and scalable way to manage...
Introduction AI is incredible. It can help you write emails, explain complex ideas, brainstorm, and even code. But sometimes, it gets things completely wrong — and says it like it’s 100% right. This strange behavior is known as an AI hallucination: when an AI gives an answer that sounds correct...
Introduction Retrieval-Augmented Generation (RAG) is an advanced technique in natural language processing that enhances language models by enabling them to retrieve external information in real time. This leads to more accurate and context-aware responses, making RAG ideal for tasks that require up-to-date or domain-specific knowledge, such as customer support, enterprise...
Introduction Keeping the data fresh in your data warehouse is crucial. In dbt (data build tool), source freshness checks help ensure that the data coming from your sources is up-to-date and trustworthy, enabling teams to confidently build reliable models downstream. This is where defining source freshness in the sources.yml...
Introduction Once you've defined sources in dbt, you can reference them using the source() function. This is essential for dbt to identify dependencies between sources and models. In this hands-on tutorial, we’ll show you how to use the source() function with a sample project. 📌 This is a...
