Data Science
From RAG to Agentic AI: Building Intelligent Enterprise Systems
Three generations of enterprise AI retrieval systems—from hybrid RAG to agentic architectures—and the engineering principles that make them work in production.
Latest Articles
Machine Learning
Is ArrowJS the Right UI Framework for the Agentic Era?
ArrowJS positions itself as the first UI framework built for AI coding agents. Here's what that means for data scientists building AI-powered apps.
AI
Grok Bot Automation: Build Bug and Churn Detection Bots
Grok Bot executes workflows autonomously using skills, routines, and plugins. This tutorial walks through building two practical automation bots step by step.
Tools
Why Multi-Agent Systems Fail Silently in Production
Multi-agent pipelines often fail not with errors, but with valid-looking outputs built on corrupt data. Here's an architecture to catch it.
Data Science
GPT-6 Astra Explained: Features, Benchmarks, and Comparisons
OpenAI's GPT-6 Astra adds computer use, persistent memory, and document generation. Here's what changed, the benchmark numbers, and where caveats apply.
Machine Learning
Switchyard: NVIDIA's Open-Source LLM Routing Library Explained
NVIDIA NeMo Switchyard is an open-source routing layer that directs LLM requests to the right model based on complexity, saving cost and latency.
Tools
Top GitHub Repositories for AI and Agent Tooling: August 2026
August 2026's top GitHub repositories focused on agent harnesses, skills, memory layers, and document tooling — with one repo gaining 190K+ stars in four weeks.
Data Science
A Practical Introduction to Bayesian Neural Networks in Python
Standard neural networks output single predictions with no uncertainty. Bayesian Neural Networks fix this by replacing point weights with probability distributi
Data Science
7 Free AI Automation Courses with Certificates
Seven free courses covering n8n, Make, Zapier, and crewAI to help you build AI-powered workflows and agents, from beginner to advanced.
AI
The Sigmoid Function: From Euler's Number to Neural Networks
Traces the sigmoid function's origins from compound interest and Euler's number to its role as an activation function in neural networks.
Data Science
How a RAG Reranker Really Works: The Honest Explanation
Rerankers aren't smarter than embeddings—they use the same mechanism, just conditioned differently. Here's what that means for your RAG pipeline.