end field

Chapter 16: Optimization

Not for greater safety—but for greater cold.

After the “Overload Signal” appeared, the board didn’t call it an incident. Sadly, they didn’t call it a warning anymore. They called it a new indicator in the dashboard—like the others, not requiring immediate action.

The next morning, the internal bulletin began with a small line:

System Indicator: Sustained High Load — 17.8%

No Exceeding the Threshold.

No exceeding the threshold is the new military mantra of the times. It means: everything is fine, but there’s less room for maneuver than before.

No one shouted. People just sighed more and more.

The board met during low load hours—Tuesday, 11:00. The graph on the screen showed: support request frequency increased slightly; synchronization delay deviation was semi-regular; unofficial overtime hours increased slightly.

“The result of prolonged high load,” the chief engineer said. “We need to optimize.”

Not reduce. Not adjust. But optimize—a word used when all standard measures are in place, and only minor improvements remain to gain a few more percent of efficiency.

The security representative began:

“We could re-coordinate shifts using a dynamic model, based on the performance history of each area. Some personnel have very low error rates, so we should increase their shifts accordingly.”

“What will that do to fatigue?” asked the medical staff.

“Reduce errors,” the security representative replied. “But increase working hours.”

“That’s not good,” said the medical staff. “We’ve already seen a slight increase in burnout. Adding hours isn’t truly optimal.”

Logistics presented a simulation:

Reducing average maintenance time by 3% → increasing output by 1.4%

Increasing shifts by 5% → reducing synchronization delay by 2.1%

Optimizing the energy distribution route → reducing downtime by 0.9%

I looked at the numbers. Optimization here was just a painful series of considerations between reducing one thing and increasing another.

“Optimize based on current load,” I said, “but there must be a fatigue constraint — we can’t repeat the exhaustion with fewer signs.”

Linh typed for a few seconds and then said:

“We can set a hard cap for overtime hours — a maximum limit of 4 hours/week — and let the optimization model find a way to reduce delay within that range.”

“That could cause backlog,” Logistics warned. “But if the backlog is < 2% of total tickets, we can accept it.”

The health representative nodded: “Hard cap will help maintain overall health.”

The decision was recorded in the minutes:

Optimization V2.0

↳ Overtime limit: 4 hours/week

↳ Prioritize optimizing energy distribution routes

↳ Reduce maintenance time without impacting users

The Hard Cap column appeared on the dashboard as a small gray bar.

No fuss. No drama.

Just a new colored line in the chart.

That afternoon, I walked past the maintenance area. A worker chuckled when he saw me: “There’s a new overtime limit.”

“Good,” I replied. “What do you think?”

“Probably fine,” he said. “At least not more than 4 hours/week.”

That was a rare compliment for an optimization policy. Meaning: people accepted it. Not jubilant. Not discouraged. Just accepted it.

That evening, when I opened the log, the Point of no return status line was still blank. As if just waiting for a click to turn red. Next to it, the System Load — Sustained High entry had risen to 19.2% in the new cycle.

I thought about the last time we called that number “dangerous.” It was a time when even the concept of danger seemed outdated.

On the screen, the V2.0 curves showed one thing clearly:

slightly reduced latency

exhaustion not exceeding the hard cap

little change in downtime

slow increase in output

No one on the board called it a win. But everyone called it the right direction.

There’s something about the language of the right direction that always sends chills down my spine.

People call it optimal. The system calls it more efficient. I call it another step toward transforming humans into more subtle variables—not green, red, or yellow data, but a rational range of numbers optimized to be noiseless.

I turn off the screen.

Outside, the base continues to run. No noise, no collapse, no obvious anomalies.

Just small metrics, being reshaped to fit more within limits.

And in the language of the system—that is optimization.