Large Language Models (LLMs) are only as good as the data that shapes them. Whether you’re fine-tuning a model for domain-specific use or building an LLM-powered application from scratch, data readiness is the single biggest factor influencing performance, reliability, and ethical outcomes. As the saying goes, “garbage in, garbage out”  - but with LLMs, the cost of poor data goes beyond technical glitches; it can lead to bias, misinformation, and loss of trust. In this post,

In my previous post,  we looked at the importance of focusing on access control and perimeter security. However, protecting the perimeter...

In my  last post , I looked at some tips on how to write more secure code. However, it’s not just code alone that developers need to...

I’ve already discussed how monitoring applications is vitally important. With companies continuing to operate at a vast global scale and...

Developing and maintaining software applications is only a part of an application’s life cycle. Applications also need to be kept...