From RAG to Agents: The Evolution of AI Applications in 2025 A Comprehensive Analysis of How AI Applications Evolved from Retrieval-Augmented Generation to Autonomous Agent Systems December 2025 | Industry Whitepaper Executive Summary 2025 marked a fundamental shift in how AI applications are built and deployed. What began with Retrieval-Augmented Generation (RAG) as the dominant… Continue reading
Category: Emerging Technologies
Emerging technologies include a variety of technologies such as educational technology, information technology, nanotechnology, biotechnology, cognitive science, psychotechnology, robotics, and artificial intelligence.
Getting Started with Microsoft Foundry Local: Run AI Models On-Device Without the Cloud
Microsoft Foundry Local brings the power of Azure AI Foundry directly to your local device, enabling you to run state-of-the-art AI models without cloud dependencies. Announced at Microsoft Build 2025 and continuously enhanced since, Foundry Local represents a paradigm shift in how developers can build AI-powered applications—with complete data privacy, zero API costs, and offline… Continue reading
Tips and Tricks – Cache LLM Responses for Cost Reduction
Implement semantic caching to avoid redundant LLM calls and reduce API costs.
The Evolution of Anthropic Claude: From 3.5 to 4.5 Opus – A Technical Deep Dive
Having worked with AI models for over two decades, I’ve witnessed countless technological shifts, but few have been as remarkable as Anthropic’s Claude evolution. From the initial Claude 1.0 release in March 2023 to the groundbreaking Claude 4.5 Opus in late 2025, Anthropic has consistently pushed the boundaries of what’s possible with large language models.… Continue reading
Tips and Tricks – Implement Prompt Templates for Consistent LLM Output
Use structured prompt templates to get reliable, formatted responses from LLMs.
Serverless Showdown: Cloud Run vs Cloud Functions vs App Engine – Choosing the Right GCP Compute Platform
I’ve built Serverless Showdown systems for three different companies. Each time, I learned something new. Let me walk you through the complete process, including the mistakes I made so you don’t have to. What We’re Building Today, I’ll show you how to build [specific system] that actually works in production. This isn’t a toy example—it’s… Continue reading
Tips and Tricks – Use Embeddings for Semantic Search
Implement semantic search using text embeddings for more relevant results than keyword matching.
Tips and Tricks – Use dbt for Maintainable Data Transformations
Build modular, tested, documented data transformations with dbt.
Tips and Tricks – Partition Large Tables for Query Performance
Use table partitioning to dramatically speed up queries on large datasets.
Orchestrating Chaos: Why AWS Step Functions Became My Secret Weapon for Building Resilient Distributed Systems
Three years ago, I inherited a distributed system that processed insurance claims across twelve microservices. The orchestration logic lived in a tangled web of message queues, retry handlers, and compensating transactions scattered across multiple codebases. When something failed—and in distributed systems, something always fails—debugging meant correlating logs across a dozen services while the business waited… Continue reading