Elian's phone buzzed suddenly in the middle of a calm morning. He glanced at the screen, which said Emil — Incoming Call.
"Elian," Emil said quickly. "Get dressed. NovaTech needs you in the main office right now."
"At this hour?" " Elian looked at the clock. It was barely past eight a.m.
"It is urgent. A top-level meeting. The president wants you to attend in person."
There is no more explanation. Just a click and a dial tone.
Elian did not squander time. He closed his laptop, put on a sharp button-down, and grabbed his luggage. Something was brewing.
The conference room at NovaTech headquarters was buzzing with activity.
Executives from various departments stood on one side of the long, obsidian-glass table. On the opposite end stood President Novarro, flanked by an unusual figure dressed in a stylish gray suit. Behind him was a small retinue carrying branded files with the Aerodyne Dynamics logo.
Emil waved Elian in and patted the seat beside him.
"That's them," he murmured. "The client." Aerodyne is an aerospace startup. Smart money says they just closed a $50 million seed round."
Elian's heart thumped. What would an aerospace company want from NovaTech?
President Novarro stood on the podium and nodded to the man next to him.
"Everyone, this is Mr. Darius Vance, president of Aerodyne Dynamics."
Darius took the floor with cool authority. "We are a freshly created aerospace company that wants to change the way micro-satellite components are made and monitored. We've bought precise printing laboratories and started prototyping gear, but we still lack a next-generation manufacturing intelligence platform."
He paused to study the room.
"We require a system that can manage dynamic scheduling, adaptive error prediction, AI-powered inventory forecasting, and machine telemetry analysis. Something that thinks alongside us, learning as we create. Our team is already pushing the boundaries of innovation. "We want software that matches that energy."
Elian could feel the air shifting. Everyone sat straighter.
Darius continued. "And based on your company's portfolio, services, and technologies, it can offer, we want to build it with NovaTech—if you can deliver. "
Novarro stepped in again. "To prove we're the right partner, we've chosen to do something unusual. We are offering a challenge—an internal competition."
Heads turned.
"In front of us are several of NovaTech's sharpest developers, each with a proven track record of delivery. Today, you'll all receive the same design brief. You have exactly 24 hours to create a simple working prototype of the core system.
Murmurs erupted. A few developers exchanged glances, some excited, some frightened.
"If you succeed, and your prototype impresses Mr. Vance and his board," says Novarro, "you will lead the core development team… as project manager."
Darius jumped up again, "And we'll sweeten the deal by awarding 10% of the project's total contract value upon final delivery. Assuming we proceed.
Ten percent. That was a fortune if the client followed through on their deal. Easily millions.
Emil nudged Elian next to him.
"Are you ready for this?" "He whispered.
Elian was ready to respond when something else occurred.
His screen flashed.
[System Notification].
[Hidden Mission Available]
Mission Title: Prototype Under Pressure.
Objective: Accept the challenge.
Reward: 10+ years of practical experience with artificial intelligence technologies.
This includes:
— Predictive analysis
— Neural network architecture.
— Natural Language Processing
— Real-time ML integration.
— Designing autonomous agents.
Accept the task of integrating the knowledge immediately.
[Accept] [Decline]
Elian's heart pounded.
He looked up and about. The others were talking about the architecture, UI tools, and cloud stacks. Some had already begun sketching diagrams on tablets or checking their laptops.
He looked back down.
10+ years of AI experience. That was not just a theory. That was neuron-level integration. Accelerated learning and knowledge that would take a lifetime to develop.
He tapped [Accept].
The world seems to blur.
A pulse of light flashed over his vision.
It wasn't simply knowledge. It was absorption.
His neural circuits aligned. Concepts were unraveled and reformed. It was as if each tutorial, research article, and hands-on project had been crushed into him in milliseconds. He felt the weight of expertise settle into his mind—how to train a model, discover pattern failures, and fine-tune hyperparameters. Not only how, but why.
He blinked quickly.
Everyone else was still speaking. However, Elian felt like time had slowed.
A faint hum filled his head, bringing new clarity.
Following the meeting, the shortlisted candidates met on the NovaTech innovation floor. Each had access to a secure development environment and sandbox database, as well as the main project brief.
Elian sat at the NovaTech war room station, cracking his knuckles and whispering to himself, "Let's build something they won't forget. "[1]
As the system's AI knowledge reward entered his brain, his mental clarity improved. Frameworks, best practices, and architectural patterns flowed like second nature. Natural Language Processing, ML model pipelines, and data pipeline architecture became as basic to him as breathing.
Architectural Planning
He opened Notion and began diagramming:
Frontend: React + TailwindCSS to improve performance and responsiveness.
Backend: Node.js and Express.js (lightweight and fast for prototyping).
AI Component: Python FastAPI service integrated using REST.
Database: PostgreSQL running in a controlled local Docker container
Authentication: JWT-based login.
Core modules:
Time Tracking
Intelligent Task Suggestion with AI
Real-time Productivity Analysis
Employee Sentiment Detection through Notes
He termed the system "NeuroPulse" - a smart work tracker that detects your productivity and
mood in real time.
He knew the client, a recently created productivity and operations organization in Singapore, need a robust AI-integrated internal system. The organization was rapidly expanding and drowning in unstructured task processes, ineffective time tracking, and a lack of visibility into employee productivity. Their goal was straightforward, but the execution had to be flawless: a smart productivity tracker that used AI to recognize work habits, make intelligent task suggestions, evaluate written logs for sentiment, and generate real-time data. The prototype has to demonstrate practicality, promise, and innovation in 24 hours.
Elian began by mentally drawing out the system architecture and recording it in his notes. The frontend would leverage React for quick UI iteration, together with TailwindCSS to keep the interface clean and modular. The backend would be created using Node.js and Express—fast, familiar, and ideal for creating APIs under pressure. He opted to use FastAPI to launch a separate Python-based microservice for the AI component, allowing for seamless integration with complex NLP models. PostgreSQL would be the primary data store, operating locally with Docker to keep things segregated and controllable.
The system required numerous essential modules, including user identification, time tracking, intelligent task suggestion, productivity analytics, and sentiment analysis of employee notes. He began with user management, creating a lightweight registration and login procedure using token-based authentication. With that done, he moved on to the time tracking method. He designed a dynamic event listener on the frontend to track active tab usage, idle time, and session lengths. This data would be regularly logged and uploaded to the backend, providing the system with detailed insight into each user's daily behaviors.
He then moved on to the key feature, the AI-powered task recommendation engine. Using his newfound mental fluency with transformers and zero-shot learning, he created a simple API for analyzing a user's task history and recommending the most appropriate next step. The model was not overengineered; it employed a lean transformer pipeline that prioritized speed while yet producing intelligent results. Elian designed it to collect user task records, analyze them with a classification model, and provide a ranked suggestion. This would function as a personal productivity assistant for every employee.
[1] This will be like HACKATHON