Critical Careers - Women Building Careers in Digital Infrastructure - Book - Page 21
Has there been a
moment that made
you feel like you truly
belonged in this
industry?
The moment I felt I really belonged came gradually as I
started watching how the technology was evolving. When
ChatGPT 昀椀rst appeared, it was exciting and full of promise,
but it was also very limited. There were hallucinations, and
even simple bits of code wouldn’t work properly. It was clear
that, at that point, it was mostly just talking back and forth
rather than doing anything meaningful.
What stood out to me was seeing the shift toward agentic
systems. As soon as models started being connected to
real-world data sources, tools, and structured ways of calling
functions, everything changed. Instead of just generating
text, they could interact with applications, pull in live
information, and start operating in a way that felt tangible.
That was the point where it clicked for me.
It began to feel like we were building digital intelligence
that could actually work alongside humans. Seeing that
progression over the past couple of years made me realise
that this is where the industry is heading. The focus now is on
building the infrastructure to support AI workers to take on
more complex tasks and have real-world impact. Watching
that evolution reinforced for me that I’d made the right call,
and that I genuinely belong in this space.
Looking at your growth so far, which skills have
made the biggest difference for you, and why?
The skill that’s made the biggest difference for me is focus. I’ve always had this instinct
to do lots of things at the same time. For a long while I thought of that as being a
strength. But what I’ve learned, especially working on really complex AI problems, is how
important it is to stay with one thing and actually see it through.
Developing the ability to sit with a problem, whether that’s learning something new or
trying to make something work properly, has been a big shift for me. It’s not something I
naturally knew how to do before. There are always distractions, always new ideas, always
something shiny pulling your attention away. Learning to say, “This is what I’m working
on right now,” and committing to it until it reaches a logical end has been huge.
That mindset really matters when you’re building something dif昀椀cult. You don’t have
the luxury of stopping when something is just “good enough.” If it doesn’t work, it
doesn’t work, and you have to keep going until you solve the problem. It’s also a very
competitive space, so whatever you’re working on has to genuinely move the needle for
people. If it’s not good enough, no one will use it, because they’re investing their time
and effort into it too.
What do you wish more senior leaders understood
about what it’s like to be starting out in your career
in today’s work atmosphere?
I wish more senior leaders understood how different it feels to be starting out right now,
particularly with AI reshaping the workplace so quickly. Early on, senior-level conversations
around AI focused on replacement — how much work could be automated and how many
people might no longer be needed. From an early-career perspective, that creates a lot of
uncertainty. What’s been more encouraging to see is a shift towards organisations using AI
to amplify human capability rather than reduce headcount and investing in AI-native talent
who know how to work effectively with these tools.
Giving people real chances to learn, experiment, and build capability with AI makes a
huge difference. If companies helped young people learn how to use AI well, not just
technically but responsibly and creatively, you’d end up with a talent pipeline that’s already
comfortable operating in this new environment. That’s a long-term advantage
for everyone.
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