At the start, I had to choose one of four options, and I immediately picked the Brahmin from the cou

"To be honest, I'd love to be corrupted like that too. I've been studying graph neural networks for half a month, and I still haven't even grasped the message passing mechanism. He, on the other hand, went from beginner to refactoring in two weeks, and even learned a real-time rendering pipeline along the way—I'd be willing to be kissed by Turing for that kind of efficiency."

As soon as Xiao Zhang said that, the air in the entire office area fell silent for about two seconds. Then, someone couldn't hold back and let out a very low chuckle from a corner. Immediately afterward, as if it were contagious, the shoulders of seven or eight people began to tremble at the same time.

Chen Qiming's hand holding the coffee cup hovered in mid-air. His lips twitched, but he managed to suppress the smile by relying on the facial muscle control he had developed over the years of leading a team.

"Alright, everyone get back to work." Chen Qiming's words brought this brief banter to a close.

But Xiao Zhou was not affected at all.

He had put his headphones back on at some point, and the code window and the rendering preview window of the cartoon girl were laid out side by side on the screen. On the left was a dense array of low-level C++ logic, and on the right was a real-time simulation of the skirt's physics that updated with each save.

His eyes darted rapidly between the two windows, his left hand typing on the keyboard to change the ambient occlusion parameters in the rendering pipeline, while his right hand simultaneously reached out and swiped on the touchpad of another monitor, turning to page four of the MIT paper.

Chen Qiming observed him for a full five minutes and found that he wasn't just pretending—this young man, who had only graduated a year ago, was genuinely handling two completely different and complex systems at the same time.

The training script for the graph neural network was running quietly in the background, while the debugging window of the front-end rendering pipeline was refreshing in real time in the foreground. It was as if Xiao Zhou's brain had established a high-speed channel between these two tasks that was invisible to others, and the cost of switching was almost zero.

Chen Qiming didn't disturb him. He silently walked back to the whiteboard, picked up a marker, and drew a new box next to the densely drawn technical architecture diagram. Inside, he wrote three words: "Xiao Zhou's Team." After writing that, he stepped back and looked at it, then added a line of small text below the box with the marker: "Graph Neural Network + Asynchronous Inference Engine, Person in Charge: Xiao Zhou, Delivery Time: Before the 20th of this month."

A month ago, the entire team would have thought he was joking if this delivery date had been mentioned. But now, every line on the whiteboard is written with a marker, without any trace of correction—meaning that Chen Qiming was 100% certain when he wrote these words down.

The changes didn't just happen to Xiao Zhou alone.

On the evening of the twelfth day, after staring at the screen and debugging for six consecutive hours, Xiao Zhang suddenly stood up from his workstation, the chair wheels scraping the floor with a sharp sound. His sudden movement startled Xiao Li, who was drinking Red Bull next to him, almost causing him to spill the liquid from the can onto the keyboard.

"Found it." Xiao Zhang's voice was hoarse, like sandpaper scraping against a metal surface, but every word carried an uncontrollable tremor. "I've found the culprit that caused the CPU usage to spike to 90% when there were 10,000 concurrent users."

He pointed to three lines of code highlighted in yellow on the screen, his finger almost digging into the monitor. A few people gathered around to look, then exchanged bewildered glances—those three lines of code looked too normal, so normal that they had never questioned them during their previous code reviews. A standard thread pool initialization function, taking the number of CPU cores minus one as the parameter, with no syntax errors and logically completely conforming to conventional practices.

"There's a problem with the thread allocation." Xiao Zhang commented out the code, rewrote a few lines, and spoke rapidly, "We were previously allocating the thread pool based on the number of physical cores minus one. This logic worked fine when running tests on a single machine, but once we moved to a concurrent stress test environment, the virtualization layer would perform additional thread scheduling, causing worker threads in the thread pool and system scheduling threads to compete for time slices. On the surface, the code was running, but in reality, half of the CPU cycles were wasted on thread switching. By changing it to use the number of logical cores, doubling it, and reserving two separate threads for asynchronous coroutines for context switching—just changing these three lines of code, the CPU utilization dropped by half during a 10,000 concurrent stress test."

By the time Xiao Zhang finished speaking, his fingers had already typed out the refactored code.

Packaging, compiling, and starting the load test are all done in one go.

The CPU curve on the monitoring panel smoothly dropped from its previous high level and stabilized at less than half, as quiet as if someone had gently pressed it down with a finger.

Xiao Li stared at the curve for a full fifteen seconds, then lowered his head and carefully wrote something down in his work notebook: "July 6, 2026, Xiao Zhang discovered a thread pool configuration error, and the CPU utilization rate for 10,000 concurrent connections dropped from 90% to 45%." After writing it down, he drew a five-pointed star at the end of this entry—a customary mark within their team indicating that the discovery was important enough to be reported to investors.

But the most important breakthrough came from Dr. He.

At 3 a.m. on the fourteenth day, most of the lights in the entire software park had been turned off, except for the floor where Xinglan Technology was located.

Dr. He sat alone at his workstation, the monitor in front of him displaying a program he had been writing on and off for two weeks.

The idea for this program came to him suddenly one sleepless night—to use a lightweight pre-filtering module to perform a quick semantic dimensionality reduction before the unstructured resume data enters the main matching engine, thus removing obviously irrelevant and redundant information in advance.

The idea is good, but its implementation is fraught with difficulties.

The core issue is that the pre-filtering module itself consumes computational resources. If the filtering algorithm is not efficient enough, adding this module will not only fail to speed things up but will also become a new bottleneck. Dr. He tried seven or eight solutions, from Naive Bayes to lightweight gradient boosting machines, from word frequency inverse document frequency to shallow convolutional networks. Each solution performed well in individual tests, but once embedded into the entire system's call chain, it would encounter a performance bottleneck at some unexpected point.

Suddenly, he stopped working on all his projects.

He sat in his chair, staring at the error logs on the screen, but his mind was on something completely unrelated.