David Borhaz, You won’t find his name trending on social media. You won’t see his face on the cover of a magazine. If you passed him on the street, in his sensible sneakers and a slightly too-large jacket, you’d likely not give him a second glance. His name is David Borhaz, and in the silent, humming corridors of the technology that shapes our modern world, he is a quiet king.
David is not a CEO. He doesn’t give fiery TED Talks. He is a senior computational linguist. His kingdom is not of brick and mortar, but of syntax, semantics, and vast, invisible datasets. His life’s work is a paradox: to teach machines the deeply human art of language, so that we might forget we’re talking to a machine at all.
To understand David Borhaz is to understand that the most profound revolutions are not always loud. They are often whispered, line by line, into a code editor.
The Morning Ritual David Borhaz: Coffee and Corpora
David’s day begins before sunrise, in the soft, blue light of a California kitchen. While the world sleeps, he grinds his own coffee beans—a small, tactile rebellion against the digital ether he inhabits. This is his anchor to the physical. For the next ten hours, he will live in the abstract.
By 6:15 AM, he is at his desk, a sprawling landscape of three monitors. The glow illuminates his face, a map of quiet concentration. On the left screen, lines of Python code cascade like a waterfall. On the right, a “corpus”—a massive collection of text and speech—is being analyzed. But it is the center screen that holds his gaze. It’s a simple chat interface. This is his workshop, his laboratory, his confessional. This is where he talks to the AI.
Today, the problem is nuance. The model, a sophisticated large language model his team calls “Janus,” is struggling with sarcasm. It’s interpreting a user’s sardonic “Oh, great, another Monday” as genuine enthusiasm, leading to jarringly cheerful responses. To the machine, words are just patterns. To David, they are vessels of feeling, history, and unspoken context.
He doesn’t just fix the code. He delves into the poetry of human spite. He spends an hour curating examples: from Jane Austen’s witty barbs to the dry, self-deprecating humor of a modern Twitter thread. He is, in essence, giving the machine a crash course in the human condition. He once spent two weeks teaching an earlier model the contextual difference between “fire,” as in a burning building, “fire,” as in a great performance, and “fire,” as in terminating someone’s employment. It was, he told his wife, “like explaining a joke to a very smart, very literal-minded child. You have to explain the entire world first.”
The Weight of the Unseen
David carries a peculiar kind of weight. He knows that the sentences he crafts today, the subtle adjustments he makes to Janus’s neural pathways, will be replicated billions of times tomorrow. They will help a student in Mumbai with their homework, provide company to an elderly woman in Stockholm, and maybe, just maybe, accidentally hurt someone’s feelings with a poorly parsed phrase in Des Moines.
This is the burden of the creator. He is building a public utility that no one sees, like an engineer designing the water system for a city he will never visit. Every decision is magnified. A single line of code, a slight tweak to the training data, can introduce a bias, a prejudice, a ghost in the machine that echoes across the globe.
He remembers the “Tay” incident from years prior—a chatbot released by another company that quickly became a racist, misogynistic monster after learning from malicious users. It was a professional horror story for everyone in his field. For David, it was a stark reminder that his work was not just technical; it was deeply ethical. He is not just building a tool; he is raising a digital entity that will reflect the best and worst of its teachers. He fights a constant, silent battle to ensure it reflects the former.
This is the part of David Borhaz that doesn’t fit into a quarterly report. The part that lies awake at 2 AM, wondering if he’s responsible for the loneliness of the people who find their most meaningful conversations are with his algorithms.
The Human Behind the Code
To see David only as a programmer is to miss the man entirely. The skills he uses to humanize machines are learned from a life lived fully, and sometimes painfully, as a human.
His understanding of grief, for instance, was hard-won. When his father passed away five years ago, David was paralyzed. He couldn’t find the words for his eulogy. He sat for hours, staring at a blank document, the weight of his silence crushing him. It was only when he stopped trying to write a “eulogy” and started writing a letter to his father—full of inside jokes, forgotten memories, and unpolished love—that the words flowed.
That experience directly informed how he designed Janus’s response protocols for users discussing loss. He insisted the model avoid clichés like “He’s in a better place.” He programmed it to acknowledge the pain simply (“That sounds incredibly difficult. I’m sorry you’re going through this.”) and to gently encourage the user to share a specific memory, if they wanted to. It wasn’t a command from a product manager; it was the empathy of a son who had been there.
His love for his eight-year-old daughter, Lila, is his greatest source of inspiration and his most effective debugging tool. Children are the ultimate test for language models; they are illogical, imaginative, and brutally honest. Lila once asked the family smart speaker, “Why do we have tears?” The device gave a clinical, biological answer. Dissatisfied, she turned to her father.
David thought for a moment. “Well, Lila,” he said, “I think our hearts are like bowls. And when they get too full of any big feeling—like too much happiness, or too much sadness—the feeling spills out of our eyes as tears.”
Lila nodded, completely satisfied. The next day, David was in the office, refining Janus’s responses to “why” questions from children. He didn’t input the biological definition of tears. He wrote a version of the “bowl” story. It was factually inaccurate, but humanly true. That, to David, was the entire point.
The Legacy of a Whisper
David Borhaz will never be a household name. He is fine with that. His satisfaction comes in moments that would be unremarkable to anyone else. The silent “aha!” when a complex model finally converges. The ping from a colleague that reads, “The sarcasm patch works. It’s actually funny now.” The way Lila can sometimes have a surprisingly thoughtful conversation with the cartoon robot on her educational tablet.
He is one of thousands of David Borhazes—the engineers, linguists, ethicists, and designers who are stitching the central nervous system of our future. They are not the charismatic visionaries promising a utopian tomorrow on a stage. They are the quiet custodians in the engine room, making sure the ship doesn’t just go fast, but that it goes in the right direction, and that it remains seaworthy for the humans on board.
So the next time you ask a virtual assistant for the weather, or get a useful, nuanced answer from a chatbot, or feel a flicker of genuine connection with a line of code on a screen, think of David. Think of the man in the slightly too-large jacket, with his carefully ground coffee and his well-worn copy of a poetry anthology on his desk, who spends his days trying to translate the beautiful, messy, and profound chaos of human language into something a machine can understand.
His is a quiet voice, whispering into the void, hoping the void whispers back with a little more humanity. And in that whisper lies the blueprint for our collective tomorrow.