“The deadline is six weeks… do it, or don’t bother showing up again.”

The boss spoke words, which continued reverberating in the mind of John even after the meeting was over. He looked at Timothy, who appeared too calm too be in the storm which just has been announced. Six weeks, John said nearly to himself, to construct something which no one had ever attempted to construct... are we magicians or engineers?

Timothy smirked. Occasionally, John, there is not as much difference between magic and engineering as you might think.

AI Creation

This was the problem of a different kind. One of the car rental agencies wanted an algorithm that could compute the rental rates in real time- adjusting prices when there are rush hours, lowering them when nights are dull and promoting their services without damaging profitability. It was a juggle of mathematics, human psychology and technology.

The same evening, John and Timothy started to form their teams. John chose shrewd, fast coders- individuals, who could run at breakthrough speed of intricate issues. Timothy however selected the minds of detail oriented engineers, engineers who are capable of detecting a single error in thousands of lines of code. Thoreau and the Vets could not have appeared to be a pair, yet they made a terrifying duo--speed and precision.

Ai Creation

Ok, so we have to start with demand forecasting, they all sat down in the glass-walled workspace, John began. What causes a surge in rentals--office hours, airports, special events, let find out. Once we break the pattern, we are able to begin predicting demand before it occurs.

One of the engineers on the side of Timothy brought a concern. However, pricing logic are an essential ingredient to demand prediction. Increasing fares excessively will cause people to go to competitors. Less than that and the client loses money.

Timothy nodded. “Exactly. This is why we require a hybrid model- something that researches real- time trends and contrasts them with customer behavior. We’ll call it ‘SmartFlex.’”

The name stuck. Days and nights transformed the workspace into the battlefield of whiteboards, coffee cups and shining screens. The skeleton of the app was developed by the team of John, the code was the predictive algorithm which monitored traffic information, flight time, and even the weather predictions. Timothy and his team narrowed it down, so that the algorithm was not simply responsive, however, it foresaw, always one step ahead.

Yet difficulties could not be avoided. During the week three, their model failed due to the unexpected load of data- bookings during the holiday season. The prices became ridiculous and caused system malfunctions. The whole project was about to fall.

John slammed his fist on the desk. “This is it. Six weeks, and we’re going to fail because of one stupid holiday glitch!”

Timothy stayed composed. “Not fail. Adjust.” He leaned forward, eyes sharp. “What if the algorithm learns from anomalies? Treat holiday data not as errors but as lessons. Like memory.”

The room went silent. Then, slowly, the idea caught fire. They restructured the system into a self-learning algorithm, allowing it to adapt each time it faced unusual demand. It was bold, risky, but brilliant.

By the sixth week, “SmartFlex” was alive. During their final presentation, the boss watched as the app simulated real-world rental scenarios—rush hour peaks, midnight drops, sudden airport demand. Prices adjusted flawlessly, promotions appeared strategically, and revenue remained balanced.

The boss leaned back, impressed. “You’ve not just built a program… you’ve built the future of car rentals.”

John exhaled, relief flooding his face. Timothy only smiled, whispering to him, “See? A little magic, a little engineering.”

The challenge had been met—and conquered.

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I would like to invite my friends @suboohi , @shahid76, and @wuddi to join this challenge.

Regards
artist1111