investigating software

 In 316 AD Emperor Constantine issued a new coin,  there's nothing too unique about that in itself. But this coin is significant due to its pagan/roman religious symbols. Why is this odd? Constantine had converted himself, and probably with little consultation -  his empire to Christianity, years before. Yet the coin shows the emperor and the (pagan) sun god Sol.  Looks Legit! While this seems out of place, to us (1700 years later), it's not entirely surprising. Constantine and his people had followed different, older gods for centuries. The people would have been raised and taught the old pagan stories, and when presented with a new narrative it's not surprising they borrowed from and felt comfortable with both. I've seen much the same behaviour with Large Language Models (LLMs) like ChatGPT. You can provide them with fresh new data, from your own documents, but what's to stop it from listening to its old training instead?  You could spend a lot of time collating,

I play a card game called cribbage. I often play it with my son . One interesting part of the game is the muggins rule. This means that you can claim points from other players turns, if they miscount the score.  The scoring is slightly nerve racking, with each of us double and triple checking our scores, to avoid falling foul of ‘muggins’, that’s part of the fun.  But my son and I also find ourselves discussing other hands of cards, in a sort of alternate history version of the game. “So if I had a 7 instead of a 2 of hearts, then I’d get a double run and score at least 8 more points”.   “Yes Dad, if you had different cards then you would likely have a different score, but you don’t” he says while rolling his eyes.  This sort of bitter-sweet history rewriting is a convenient tool for us to swallow the awkward truth of the real world. We often create alternate things to object to.  Take Chat GPT 4 and tools like Copilot X. These are powerful tools, capable of doing useful tasks quicker

 I was lucky enough to have started my career in a small company and then in a start-up. Both provided me with an environment perfect for learning. I sat with experts who took time out of their day to help answer my questions. From them, I learned the basics of what I still use today.  I’ve built on those foundations, but things would have been much harder if I didn’t have those foundational moments of my career. I’m not just talking about technical skills, the mentoring on how companies work, consulting and how to be better generally.  But those technical skills were also a big part of it – and a part many people miss out on in their careers. The rise of Large Language Models like ChatGPT4 is rapidly helping to fill that gap – where people don’t have a technical mentor who can explain and help work through those technical problems.  I’m no longer that junior team member – asking the dumb questions (OK, well usually I’m not) but even I find Chat GPT excellent at consolidating a broad s