Introduction You have decided to build an AI application. Now comes a critical question: should you use open source models or proprietary ones? Open source AI—like Llama, Mistral, and Stable Diffusion—offers transparency, customization, and no vendor lock-in. Proprietary AI—like OpenAI’s GPT, Google’s Gemini, and Anthropic’s Claude—offers polished performance, enterprise support, and ease of use. Both…
Introduction Imagine an AI that doesn’t just answer questions but actively works toward goals—researching topics, performing calculations, updating databases, and coordinating with other systems—all with minimal human supervision. This is the promise of autonomous AI agents, and building one is more accessible than you might think. An autonomous AI agent is a system that can make decisions…
1) Opening Scenario: From Idea to Agent Imagine you’re tasked with building an internal AI assistant for a mid-sized enterprise. The requirements are clear but demanding: Traditionally, this would require stitching together multiple services: a vector database for retrieval, an LLM for reasoning, API integrations for tools, and a deployment infrastructure. Months of work, complex…