Use streaming wisely. It is great for real-time or chunked data, but avoid long-lived streams unless necessary. Watch for ordering and backpressure issues.
Silent data drift broke our metrics, errors, just lies. We fixed it with schema contracts, validation, lineage, and loud failures. Now, trust is engineered.
Deploying LLMs at the edge is hard due to size and resource limits. This guide explores how progressive model pruning enables scalable hybrid cloud–fog inference.
Listing Top NoSQL databases in use nowadays, with a comprehensive comparison, and also the main proposed uses for each one to help to decide which is the best for you
Explore vibe coding: an AI-driven, natural language approach to rapid software development, enabling fast prototyping, automation, and creative problem-solving.
Using prompt engineering as a tool to reduce hallucinations with LLMs. This is one of the methodologies I used with LLM to output the desired information.
Explore how C# developers can use Docker Model Runner to run AI models locally, reduce setup time, and integrate OpenAI-compatible APIs into their apps.
Reinforcement learning (RL) enables CRM systems to build adaptive marketing strategies that optimize not only immediate response but also long-term customer value (CLV).
Learn to build an MCP server for Keycloak. The article shows how to create a Model Context Protocol (MCP) server for Keycloak using Quarkus and Goose CLI.
In this article, we discuss ethical AI for Product Owners and Product Managers and how to balance AI’s potential with its product discovery and delivery risks.