The shift from ETL to ELT to EAI isn’t just a tooling change it’s a strategic reframe of how data teams build for speed, scale, and intelligence in the age of cloud and AI. As organizations modernize, raw data lands first, transformations happen where compute is elastic, and AI begins to orchestrate integration, quality, and … Read more
Meta REFRAG (REpresentation For RAG) isn’t just another RAG tweak it’s a structural rethink that delivers up to 30.85× faster time-to-first-token (TTFT) while extending usable context by 16×, all without sacrificing accuracy, making long-context LLMs practical at scale for the first time. For teams fighting latency, KV cache bloat, or context truncation in production RAG, … Read more
If “AI in the browser” sounded like another round of summarizers and sidebar helpers, Fellou flips that script: it’s an Agentic AI browser that proactively carries out complex tasks opening tabs, logging in, clicking buttons, gathering data, and delivering finished outputs while maintaining user control and traceability. Think research sprints that culminate in crisp briefs, … Read more
For years, the story of artificial intelligence was a tale of titans. We heard about models with hundreds of billions, even trillions, of parameters. The prevailing wisdom was simple: bigger is better. But as we navigate 2025, a quiet but profound revolution has taken hold, and it’s not happening in the sprawling, energy-hungry data centers … Read more
The landscape of AI is constantly evolving, and for developers, staying ahead of the curve isn’t just an advantage it’s a necessity. We’ve all seen the transformative power of Large Language Models (LLMs), but their inherent limitations, like hallucination and reliance on static training data, have been persistent hurdles. Enter Retrieval-Augmented Generation (RAG), a brilliant … Read more
If you’ve ever felt the tug between the speed of SQL and the flexibility of Python, you’re not alone. Imagine a workflow where you push as much heavy lifting as possible into the database (where it’s optimized and scalable), then flip a switch to explore, visualize, and model in Pandas with the light, nimble touch … Read more
Remember the feeling of juggling a dozen browser tabs and terminal windows just to get a single task done? You’d have one for Stack Overflow, another for documentation, a third for your project management tool, and a fourth for your version control system. This fragmentation is the silent productivity killer of modern software development. But … Read more
Imagine having a digital assistant that anticipates your needs, automates tedious tasks, and provides intelligent insights all tailored to your specific requirements. This isn’t some futuristic fantasy; it’s the power of AI agents, and the journey to build your first AI agent is more accessible than you might think. Forget the complex jargon and intimidating … Read more
Imagine building an AI agent that can seamlessly process vast amounts of data, make intelligent decisions in real time, and adapt to changing environments all without the headache of convoluted code. For many Python developers, managing these complex workflows can often feel like navigating a labyrinth. Enter LangGraph for Python Developers, a game-changing solution that … Read more
The Ultimate Breakdown of a Confusing Battle: Generative AI vs Agentic AI vs AI Agents In the wild world of AI buzzwords, three terms keep popping up: Generative AI, Agentic AI and AI Agents. They sound similar, but they describe different capabilities, design goals, and risk profiles. If you’ve ever felt like you’re staring into … Read more