Generative Ai

The RAG Reality Check: From Vibe-Coding to Production

We’ve all seen the dopamine hit of the "magic" AI demo. In the current landscape, it has never been easier to build a system that feels like the future in thirty minutes. We have officially entered the era of vibe-coding—the practice of using AI-assisted, rapid prototyping to assemble compelling applications that secure client buy-in and validate use cases.This is particularly true for Retrieval-Augmented Generation (RAG) systems. RAG is the essential process of grounding Large Language Models (LLMs) in data they...

MCP and Doc-Monitor Transform External Services Integration

(AI-generated image)In today's interconnected world, integrating with a vast ecosystem of SaaS providers presents a significant challenge. It is not just about understanding and creating OpenAPI REST clients for numerous APIs, but also mapping them to our internal domain model. The real hurdle lies in the continuous maintenance of both the client and the mapping code as these third-party SaaS APIs evolve.Imagine we're building a neobank in the UK. A key feature of our app is providing users with a...

Generative AI and its impact on Software Development

Test Driven Generation — Use AI as a pair for programming.

Written by Amitb and Vighnesh Pathrikar Test Driven Generation Cycle Have you ever found yourself struggling to refactor your code to adhere to SOLID principles or convert user requirements into code? Did TDD or Test-Driven Development feel slow? Have you ever wished for a tool that could make this process easier and more efficient? Well, look no further! With the latest generative AI solution, ChatGPT, you can now easily refactor your code, convert user requirements into code, and even create tests — all...