The meeting ended in less than ten minutes, but the words sat like a stone in John’s stomach: six weeks, real-time demand pricing and an algorithm that could “change the way people moved.”

He glanced at Timothy as they left the room. “Tim, do you realise what this means? We’re not just coding for fun. We’re playing with people’s daily survival here.”

Timothy adjusted his glasses calmly; he was always the cool one. “And maybe, just maybe, we’re about to change it.”

That night, their engineers crowded into the lab, screens glowing, NEPA lights flickering, and suya smoke from a roadside stand sneaking in through the window. Someone pulled up Lagos traffic data, red lines everywhere. If you’ve ever been stuck on Third Mainland Bridge, you’d know that red is not data. It’s suffering. Another engineer pulled Abuja’s records: fares doubling during fuel scarcity, passengers stranded at bus stops because drivers vanished.

Timothy tapped the board. “Our boss wants an algorithm. Fine. But let’s test it with African data. If it can survive Lagos, it can survive anywhere.”

John sighed. “And if it fails?”

Timothy gave a half-smile. “Then at least we aimed high.”

The first week was pure wahala(trouble). Codes crashed, tempers rose. One rainy night, frustrated, John slammed his laptop shut. “This is impossible! The boss wants profit, and we’re here chasing some fantasy about fairness.”

Timothy didn’t even look up. “And you think profit survives when commuters drown daily in unfair fares? If we get this right, we won’t just be writing code. We’ll be rewriting how transport treats people.”

Little by little, something came alive. They built fares that rose gently during peak hours but never spiked to wicked levels. They added a “Community Shield” so that profits made during busy times could subsidise rides when crises hit. And then came the strange part: the app started learning. It noticed how rain in Lagos meant stranded commuters near Balogun Market. It picked up how Christmas travel drained families just trying to reach their villages. The algorithm was more than math; it was almost human.

Two weeks before the deadline, the boss stormed into the lab. His voice was sharp like a whip. “Gentlemen, I asked for an algorithm, not a charity project. What is this nonsense about subsidies and community balance?”

John’s heart dropped, but Timothy stood his ground. “Sir, we can deliver plain numbers. But if we stop there, we’re no better than the companies exploiting people during fuel scarcity. Let us finish, imagine the first rental app in Africa that doesn’t punish the poor. That’s not rebellion, sir. That’s legacy.”

The silence stretched so long that John could hear the hum of the faulty air conditioner. Then the boss exhaled. “Two more weeks. Don’t fail me.”

Launch day was madness. Too many downloads at once, servers crashing, panic everywhere. But when the smoke cleared, something unbelievable happened. In Abuja, fares stayed steady even when queues wrapped around filling stations. In Lagos, mothers could still afford rides in the rain. Drivers who complained at first about “reduced surges” later admitted they were making steady money without chasing passengers away.

The algorithm didn’t just calculate, it balanced and humanised.

That night, Timothy looked at John across the dim office. “We didn’t just meet the boss’s challenge. We met Africa’s.”

John, exhausted but smiling, replied, “Maybe this is what technology was meant for, not just to move cars, but to carry people home.”

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I would like to invite @eliany, @kwinberry @etoro to join the contest. Images created with canva Ai