In a glittering skyscraper overlooking Silicon Valley, a group of venture capitalists gathered in their minimalist boardroom. They weren’t there to discuss the latest startup or debate the merits of a bold new pitch. No, today was different. Today, they were brainstorming the big idea: the ultimate software creation tool—one that would allow anyone to write working software using nothing but AI prompts.

They called it "DreamCode."

"Imagine this," one of the VCs said, gesturing dramatically. "No engineers, no coders. Just type what you want, and boom! Instant app. The future is democratized creation!" His colleagues nodded with an almost religious fervor.

The prototype had already been built by a team of underpaid engineers who were far too tired to argue. A slick interface allowed users to type in natural language prompts, and an underlying AI would produce code. At first glance, it seemed like magic. "Create a social media platform for pet pictures!" a VC might type, and out came a working prototype… sort of.

The First Crash

The cracks began to show when they presented the prototype to an actual software engineer, a veteran with twenty-five years of experience. His name was John, and he was not impressed.

"Write me a program that tracks expenses and generates a financial report," he typed into the interface.

The AI whirred, blinked, and delivered a block of code. At first, it looked fine. The syntax was correct. There were even comments explaining each function. But when John ran the code, it failed spectacularly. The expense tracking algorithm ignored half the input. The reporting function calculated numbers in a way that would make an accountant cry.

"Okay," one VC said nervously, "but it’s close, right?"

John sighed. "Close enough if you want to spend weeks debugging it. Do you even know how you want the expense report formatted? What kind of data structure should it use? What edge cases need to be handled?"

The room fell silent. It became painfully clear that none of them had thought that far ahead.

The Reality Check

Despite the setbacks, DreamCode launched. The marketing campaign promised the world: "Turn your ideas into reality with a single prompt!" Hundreds of hopefuls signed up, ranging from wannabe entrepreneurs to people who thought coding was something you ordered at Starbucks.

At first, there was excitement. Users would type in vague prompts like "Make me a food delivery app" or "Create an inventory tracker for my store." The AI would spit out code, and they’d marvel at the complexity of what they had "created." But as they dug deeper, problems emerged.

  • A restaurant owner discovered that his "food delivery app" didn’t handle multiple orders properly.
  • A boutique shopkeeper’s inventory tracker was riddled with bugs when dealing with discounts.
  • And one aspiring entrepreneur’s blockchain app turned out to be… not a blockchain app at all.

The forums for DreamCode became a warzone of frustrated users posting error logs and begging for help. "Why doesn’t this work?" was the most common cry.

Enter the Engineers

As the chaos grew, DreamCode's VCs turned back to the very people they had hoped to replace: software engineers. They hired legions of them to patch the AI’s outputs, rewrite broken code, and—most importantly—figure out what the users actually wanted.

"It’s not the AI’s fault," John explained during a heated meeting. "The problem is that people don’t know how to specify what they need. Writing code isn’t just about syntax; it’s about understanding the problem you’re solving. If the user doesn’t know that, the AI can’t either."

"But it’s working, isn’t it?" one of the VCs pressed.

John gave him a long, tired look. "It’s working the way a kindergartener’s drawing of a car is technically a car."

The Pivot

DreamCode eventually rebranded as "DreamAssist" and positioned itself as a tool for software engineers rather than a replacement. The marketing shifted to emphasize that the AI could handle repetitive tasks, generate boilerplate code, and speed up prototyping.

The VCs reluctantly admitted that their dream of replacing engineers with AI was, at least for now, just that—a dream.

Meanwhile, John and his fellow engineers quietly celebrated their vindication. They knew the truth that no AI could replace: the best software isn’t built by magic but by people who truly understand what they want to create—and who know that half the battle is figuring that out in the first place.

As John said to one of his colleagues over a well-earned beer, "It’s not that AI can’t write code. It’s that most people don’t know what code they need."