I’m Elspeth, a Cloud Engineer and CFG Ambassador. I currently work at BlakYaks, a cloud native consulting, engineering and managed services business in London.

Cloud engineering is often underrepresented in discussions about software engineering and

AI, despite providing the infrastructure that modern software and AI systems rely on. It is a newer area than traditional software engineering. The commercial launch of most prominent cloud services took place over the 2000s and 2010s, with modern cloud disciplines forming in the latter decade.

It is also less well understood outside the tech industry.‘The cloud’ has become a corporate buzzword, thrown into job listings and slide decks with wild abandon. Media reactions to some global cloud infrastructure outages of the last decade, like the Amazon Web Services outage in 2025 and the Microsoft Azure outage in 2023, suggest the area is widely confounding. Yet the outages themselves illustrate how this area of tech underpins global commerce, communication,transportation and finance.

Here I would like to explain what cloud engineering is, some of the key roles of cloud engineers, and how AI can transform cloud engineering. I will also explore how women in cloud roles can benefit from AI.

Where does the fear of AI come from? There are several reasons that may immediately spring to mind: the fear of job loss, concerns about reinforcing bias, and questions around sustainability. Each of these concerns is completely valid, but should we really be afraid?

I think it’s first important to understand the psychology behind the fear. As humans, we instinctively fear the unknown. After all, fear is what has historically kept us alive as a species: the unknown = risk. This applies in the modern era as well.

For example:

• Flying feels scarier than driving
• Sharks feel scarier than cows
• AI feels scarier than Excel

However, cars are statistically more dangerous than flying, and cows are responsible for more deaths worldwide than sharks. Similarly, AI can often complete tasks far more efficiently than traditional software like Excel. So why do the first ones seem scarier? Simply because we understand them less.

No longer do we fear the internet or electricity as we once did. We’ve come to understand them and now use them in our everyday lives without a second thought. Nowadays, many AI systems feel mysterious, which has led to AI feeling dangerous. 

Research has found that a lack of transparency around AI is one of the top reasons people are hesitant to embrace it. And honestly, this fear isn’t irrational. There are multiple concerning ways AI is being misused. For example, misinformation, deepfakes and reinforcing bias (for a deeper look into bias in AI, check out my other blog here!).

Interestingly, women report distrusting AI more than men. A recent US report found that women were less likely to report AI helping their productivity than men, contributing to the AI gender gap. With technology still being a male-dominated industry, it’s important that women are equally equipped with the latest technology to avoid being left behind.

And of course, we can’t forget the environmental cost of AI. The explosive growth of AI infrastructure is currently underway, with water-hungry data centres and increased energy demand raising important questions about sustainability. This is a genuine concern, and one we should continue discussing as AI develops.

So, is all hope lost, and is our fear entirely justified? Definitely not! There are plenty of reasons to be optimistic about AI and its potential to benefit society.

What we can do is use our critical thinking skills, use AI wisely, and take the time to educate ourselves on how it actually works. It’s scientifically proven that fear fades with familiarity, so let’s start by dismantling the black box image of AI.

I’m Miranda, a full stack software engineer and Code First Girls Ambassador. Through my work I’ve spoken to so many women who are curious about tech, but hesitate to take that first step.

One thing I hear again and again is: “I’m just not good at tech.”

What’s striking is that this belief often shows up before someone has even tried coding. It’s not based on experience, it’s based on perception.

This blog explores where that feeling comes from, why it’s so common, and how we can start to reframe tech skills as something that can be learned, rather than something you’re born with, or without.

Hi! I’m Naomi, a former Mental Health Nurse, now a Finance Systems Analyst.

I always knew I wouldn’t stay in healthcare forever and would eventually leave to explore other ventures, I just didn’t know what that would look like at the time.

I started getting curious about the systems I used at work, and who would’ve thought that would spark a whole new career? One minute I was writing care plans, the next I was learning how to code.

My journey from healthcare to tech hasn’t been conventional, but that’s the beauty of staying curious and open to learning. Along the way, I created a framework to guide my decisions: the 4Fs: Funds, Fulfilment, Freedom and Flexibility and honestly, it changed everything.