Agentic AI, LLM engineering, and the models behind modern automation — multi-agent systems, LLM evaluation and comparisons, RAG, fine-tuning, AI infrastructure, security, and production AI engineering.
From the blog
A practical comparison of Google Gemini, OpenAI GPT-4, and Anthropic Claude for building AI agents. Covers benchmarks, cost analysis, feature matrices, and use case recommendations.
Build AI agents that generate rich multimodal outputs including images with DALL-E, speech with TTS, PDF documents, and formatted reports. Learn how to orchestrate multiple generation APIs into cohesive, multi-format responses.
Generative AI for video transforms content production with text-to-video synthesis, local inference, and real-time rendering tools studios use in 2026.
Learn how to install the Anthropic Python SDK, configure your API key, make your first Claude API call using the messages endpoint, and parse structured responses for agent development.
Learn how to install the google-generativeai SDK, configure your API key, make your first generate_content call, and parse responses. A complete hands-on beginner tutorial for Google Gemini.
Learn how to install the OpenAI Python SDK, configure your API key, make your first chat completion request, and parse the response object. A complete beginner-friendly walkthrough.
Understand why GPUs dominate AI workloads, how their massively parallel architecture maps to neural network math, and what high-bandwidth memory means for model training and inference.
Design AI agent systems that maintain useful service even when critical components fail. Learn degradation levels, feature flags, reduced-functionality modes, and transparent user communication strategies.
Explore how Graph RAG combines knowledge graphs with vector retrieval to answer multi-hop questions that standard RAG cannot. Covers graph construction, entity linking, and Microsoft GraphRAG.
