Tools: The Bar has Always Been Moving. Are you?

Today's Wizardry Is Tomorrow's Bare Minimum ## The Ladder We Keep Forgetting We're Climbing ## The Cycle Is Happening Again. Right Now. ## What the Moment Actually Demands ## A Word for African Technologists Specifically ## The Uncomfortable Close And Africa is running out of time to not care. There is a story — the kind that gets passed around in African classrooms — about a colonial-era quack doctor who sold bottled cures to rural crowds. His secret weapon wasn't the concoction. It was the label. Printed paper. English words. A logo, if you could call it that. The author who told this story noted, with quiet humor, that in that era, if you could print your claims, you were generally considered truthful. Literacy was new. The printed word carried the full weight of authority. The bottle didn't need to work. The label just needed to exist. I think about that story every time I watch a new technology go from miracle to minimum. Every generation has its wizardry. Every generation eventually forgets it was ever wizardry at all. In the early 2000s across much of Africa, having an email address made you someone. Not just anyone — someone. A Yahoo address was a kind of credential. It said: I am connected to the world beyond this street. By 2005, having a website meant you were serious. Businesses printed their URLs on flyers like they were printing certificates. By 2010, a Facebook page could legitimize an entire company in the eyes of its customers. By 2015, if your e-commerce store accepted card payments — genuinely processed a Visa transaction — you were operating at a level most of your competitors couldn't touch. Each of these things, in its moment, was the difference between being taken seriously and being invisible. Each of them is now table stakes. This is not a uniquely African story, but it hits differently here — because the gap between when the world adopts something and when we adopt it has historically cost us. Every cycle we miss is compounding interest on a debt we didn't choose but keep paying. Here is what is currently being normalized in the rooms you are not yet in: Teams are training lightweight, fine-tuned models on their own proprietary data — not because they have PhD researchers, but because the tooling now makes it accessible to people who are simply paying attention. Businesses are building internal AI-powered tools that automate entire workflow layers — not SaaS products, not VC-backed startups, just quiet internal infrastructure that makes ten people do the work of fifty. Developers who understand what a dataset is — not theoretically, but practically, in terms of what it enables — are making decisions that others don't even know are available to them. The raw ability to open ChatGPT and ask it a question? That's the Yahoo email address of 2025. Useful, yes. Impressive to exactly no one who matters. Let me be precise, because vagueness is comfortable and comfort is the enemy of timing. The floor right now — the floor — is: 1. Understanding what LLMs can be trained to do, specifically. Not generally. Not "AI can do a lot of things." Specifically: what does it mean to fine-tune a model on a dataset? What changes? What doesn't? You don't need to write the code from scratch. You need to understand the concept well enough to direct someone who can, or to use the tools that now make it possible without a machine learning background. 2. Knowing what a dataset is and how data quality shapes model behavior. Garbage in, garbage out is a cliché because it's accurate. The ability to look at a business problem and ask "what data do we have, and is it enough?" is fast becoming a foundational professional skill — not just for data scientists, but for product managers, founders, consultants, writers building tools. 3. Building something. Anything. A small internal tool. A prompt pipeline with logic. An AI-assisted workflow that saves your team hours a week. The era of watching and waiting to see if AI is real is over. It was over eighteen months ago. The question now is whether you're building or being built around. The geopolitical battle for AI dominance — data centers, foundational models, compute infrastructure — that's being fought between the US and China, with Europe occasionally raising its hand to ask about privacy. That battle is not ours to fight right now. And that's okay. But the application layer? The last mile? The translation of these tools into products and workflows that serve African markets, African languages, African business contexts? Nobody is coming to do that for us. And nobody else should. The window in which we can enter this layer as builders rather than consumers is not permanently open. It is open now. It has been open. It will not always be. The bottled cure in the colonial story worked because people didn't know enough to ask questions. The audit we owe ourselves — as a continent, as a tech community — is whether we're still letting others print the labels on things we should be producing ourselves. The printed label was once enough. Then the social media presence. Then the card payment integration. Now? Now you need to be able to look at a business problem and build an AI-shaped solution for it. Not describe one. Not tweet about one. Build one. Tomorrow, that will be the bare minimum too. The question is never whether the bar will rise. The question is whether you're rising with it — or realizing, five years from now, that you were standing at the bottom, watching, waiting for someone to explain to you that the ladder had already moved. If this made you feel something uncomfortable, that's the right reaction. Sit with it, then do something about it. Templates let you quickly answer FAQs or store snippets for re-use. Are you sure you want to hide this comment? It will become hidden in your post, but will still be visible via the comment's permalink. Hide child comments as well For further actions, you may consider blocking this person and/or reporting abuse