In the rapidly evolving landscape of Generative AI (GenAI), the importance of version control for prompts cannot be overstated. Initially simple and rigid, prompts have evolved significantly with advancements in AI technology, particularly with the advent of large language models (LLMs) like GPT-3 and GPT-4, which enable more natural and context-aware interactions. Today, prompts are integral to the performance and reliability of AI systems, necessitating meticulous version c

The pervasive notion that sophisticated Artificial Intelligence (AI) systems, particularly predictive models and large language models (LLMs), operate under a regime of continuous, autonomous self-improvement is one of the most persistent and potentially damaging misconceptions in contemporary technology discourse. This belief, often propagated through media narratives and science fiction precedents like Recursive Self-Improvement (RSI), a concept involving a system autonomou

Artificial Intelligence (AI), or more precisely Machine Learning (ML), has become an industry trend in the past 10 years. From a buzzword to a new way of automation and decision-making, ML has become mainstream. I have had conversations with multiple organisations keen to use ML, even without a real-world use case. Graduate schools are offering lightweight courses to the masses, consulting companies are providing services on adopting ML, and technology companies are building