Loop engineering is a game-changing approach to working with AI agents. It’s the practice of designing the control loop around an AI agent, effectively streamlining how work is discovered, executed,…
Artificial intelligence is rapidly becoming an active participant in modern software development. AI-powered coding assistants can generate code, explain complex logic, and even review pull requests before another engineer sees…
When developers first build a Retrieval-Augmented Generation (RAG) system, they usually follow what’s now known as “classical RAG“: chunk documents, convert them into dense vector embeddings using an API like…
In the current landscape of AI engineering, multi-agent frameworks like CrewAI and AutoGen are highly celebrated. The promise is tempting: take a complex process like reviewing a pull request, decompose…
In some cases, traditional approaches fall short. Retrieval-Augmented Generation (RAG) has become one of the most effective techniques for improving the accuracy of Large Language Models (LLMs). Instead of relying…
What are the risks of unchecked AI adoption for the software industry? The software industry is on the cusp of a revolution with the rise of artificial intelligence. While AI…
As the world becomes increasingly reliant on artificial intelligence, the way we approach AI engineering is undergoing a significant transformation. Gone are the days when AI was solely focused on…
AI coding assistants have become mainstream, but a growing number of developers are now asking whether local models can replace Claude and GPT for daily development workflows. The answer lies…
There are many misconceptions when it comes to Agentic AI systems. As it is one of the most overused terms in the IT industry. The term “Agentic AI” is often…
