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My first introduction to AI was through prompting, which I imagine is how many people initially experienced it as well. For me, it started with asking questions on ChatGPT and being struck by how contextual and intuitive the responses felt, not just in understanding the question itself, but also the nuances behind what I was actually trying to solve. Soon after, I was generating images in Canva, using Claude to create summaries and interactive product demos, and relying on Mi

Context: Building and Scaling Across Markets Workarena did not start as a fully formed idea. It started from curiosity and proximity to a problem. After working as a founder’s associate in a hiring startup and later as a talent acquisition specialist in an HR development company, I became increasingly interested in solving workforce challenges in Nigeria. With a youth population of over 60 million, I saw a clear opportunity for Nigeria to mirror markets like India in creatin

Lanre Adeoye Image credit: Canva I was in a conversation with friends last week, reflecting on my experience in my post-graduate program. I mentioned something that had been bothering me for a while: I miss the academic rigor of searching through materials to find a specific piece of information for an assignment. That process of scanning articles, skimming papers, and following references forced me to absorb far more than just the answer I was looking for. I often discover

Lanre Adeoye Image credit: Canva As I learn more about AI and its implications, the fundamental question that keeps surfacing for me is this: is generative artificial intelligence, or Gen AI, emerging as a foundational, general-purpose technology in the same way electricity or the internet once did? At first glance, that comparison can feel overstated. AI is not new. It is built on decades of computer science and depends heavily on the internet’s infrastructure. But foundatio