Subscribe to Abhishek Parolkar's Writings
<100 subscribers
I recently heard a seasoned programmer complain that AI was turning him into an "AI Agent Manager" rather than code/software craftsman. "I actually enjoy programming!" he said, frustrated that a programmer's new role involves orchestrating AI agents instead of writing code themselves. As a programmer myself who knows both lawyers and poets, I realized they're facing the same dilemma with language in the age of AI.
Most people think lawyers and poets are opposites. Lawyers seem rigid, bound by precedent and procedure. Poets appear free, chasing inspiration wherever it leads. One group wears suits and bills by the hour. The other wears vintage jackets and teaches adjunct classes. Law is about winning arguments. Poetry is about expressing feelings.
Both of these stereotypes are wrong.
Lawyers and poets are much more alike than different. They're both makers, in Paul Graham's sense of the word. Along with programmers, painters, and writers, what lawyers and poets are trying to do is make good things with language. They're not following some predetermined formula, though if they discover new techniques while crafting their work, so much the better.
I discovered this connection when I started paying attention to how both groups actually work. Watch a lawyer drafting a motion, and you'll see something that looks remarkably like poetry. They're searching for the precise word, testing different rhythms, building toward a moment of revelation. The goal isn't just to convey information—it's to create an experience in the reader's mind.
Legal writing, when done well, is full of metaphor. We talk about "intellectual property" as if ideas were real estate. We describe corporations as "persons" and treat contracts as "living documents." These aren't just convenient fictions; they're the same kind of metaphorical thinking that drives poetry. Both lawyers and poets understand that language doesn't just describe reality—it shapes how we see it.
Consider Wallace Stevens, who spent his days as an insurance executive and his mornings composing poetry during his walk to work. To most people, this seemed like a contradiction. How could someone spend their days processing surety claims and their evenings writing lines like "The only emperor is the emperor of ice-cream"?
Stevens himself didn't see the contradiction. "Poetry and surety claims aren't as unlikely a combination as they may seem," he once wrote. "There is nothing perfunctory about them, for each case is different." He understood that both insurance law and poetry required the same fundamental skill: taking the complexity of human experience and finding the precise language to capture it.
I recently heard a seasoned programmer complain that AI was turning him into an "AI Agent Manager" rather than code/software craftsman. "I actually enjoy programming!" he said, frustrated that a programmer's new role involves orchestrating AI agents instead of writing code themselves. As a programmer myself who knows both lawyers and poets, I realized they're facing the same dilemma with language in the age of AI.
Most people think lawyers and poets are opposites. Lawyers seem rigid, bound by precedent and procedure. Poets appear free, chasing inspiration wherever it leads. One group wears suits and bills by the hour. The other wears vintage jackets and teaches adjunct classes. Law is about winning arguments. Poetry is about expressing feelings.
Both of these stereotypes are wrong.
Lawyers and poets are much more alike than different. They're both makers, in Paul Graham's sense of the word. Along with programmers, painters, and writers, what lawyers and poets are trying to do is make good things with language. They're not following some predetermined formula, though if they discover new techniques while crafting their work, so much the better.
I discovered this connection when I started paying attention to how both groups actually work. Watch a lawyer drafting a motion, and you'll see something that looks remarkably like poetry. They're searching for the precise word, testing different rhythms, building toward a moment of revelation. The goal isn't just to convey information—it's to create an experience in the reader's mind.
Legal writing, when done well, is full of metaphor. We talk about "intellectual property" as if ideas were real estate. We describe corporations as "persons" and treat contracts as "living documents." These aren't just convenient fictions; they're the same kind of metaphorical thinking that drives poetry. Both lawyers and poets understand that language doesn't just describe reality—it shapes how we see it.
Consider Wallace Stevens, who spent his days as an insurance executive and his mornings composing poetry during his walk to work. To most people, this seemed like a contradiction. How could someone spend their days processing surety claims and their evenings writing lines like "The only emperor is the emperor of ice-cream"?
Stevens himself didn't see the contradiction. "Poetry and surety claims aren't as unlikely a combination as they may seem," he once wrote. "There is nothing perfunctory about them, for each case is different." He understood that both insurance law and poetry required the same fundamental skill: taking the complexity of human experience and finding the precise language to capture it.
Stevens wasn't unusual. Archibald MacLeish edited the Harvard Law Review before becoming a three-time Pulitzer Prize winner. Edgar Lee Masters was Clarence Darrow's law partner when he wrote Spoon River Anthology. Lawrence Joseph, a contemporary poet, puts it directly: "In the United States the language of law covers every social, economic and political issue... I've used it in my poetry."
What these lawyer-poets understood is what my programmer friend is rediscovering: the deep satisfaction of making something with your hands, whether those hands are holding a pen or typing code. There's a joy in finding exactly the right word, crafting the perfect sentence, building an argument that unfolds with inevitable logic. It's the same pleasure hackers get from elegant code or painters get from capturing light.
But there's a practical reason why so many poets have been lawyers. Law pays well enough to support poetry. Stevens could afford to walk to work composing verses because his insurance job provided financial stability. Poetry rarely pays the bills, but law often pays them quite generously. This isn't compromise—it's strategy. The day job enables the love work.
More importantly, the constraint of legal language can actually enhance poetic creativity. When you spend your days crafting precise, economical prose, you develop an ear for rhythm and an eye for the essential. Legal writing teaches you to cut every unnecessary word, to build arguments that flow inevitably from premise to conclusion. These are exactly the skills poetry demands.
Justice John Paul Stevens (no relation to Wallace) once said, "The study of English literature, especially lyric poetry, is the best preparation for the law." He was right, but the reverse is also true. Law is excellent preparation for poetry. Both require you to understand how language works on multiple levels simultaneously.
Now AI threatens to disrupt this symbiotic relationship. Language models can draft contracts, write briefs, and even compose poems. The same force that's pushing programmers away from hands-on coding is pushing lawyers toward becoming "legal project managers" and poets toward becoming "prompt engineers."
This is what I call the promotion paradox. The better AI gets at the core work, the more we risk being "promoted" away from the thing we actually love doing. Lawyers who entered the profession because they enjoyed crafting arguments find themselves managing AI outputs. Poets who love the feel of words in their mouth find themselves engineering prompts for text generators.
The parallel with programming is exact. My programmer friends didn't become a programmer to manage other programmers or oversee automated systems. Theybecame a programmer because they enjoy the puzzle of turning thoughts into code, the satisfaction of making software that actually works. When AI takes over the coding, they lose the thing they loved about the job.
But here's what I think both lawyers and poets can learn from hackers: the answer isn't to resist the tool, but to understand what the tool can't do.
AI is remarkably good at pattern matching and recombination. It can write a serviceable brief by following templates and precedents. It can generate poems that follow established forms and echo familiar themes. What it can't do—at least not yet—is understand what it means to be human in a specific moment with a particular problem.
When Stevens walked to work composing poetry, he wasn't just arranging words according to patterns he'd absorbed from other poems. He was processing his experience of being a middle-aged insurance executive in Hartford, Connecticut, watching the morning light hit familiar buildings, thinking about mortality and meaning and the strange beauty of ordinary life. The poetry emerged from that specific consciousness encountering that specific moment.
Similarly, when a skilled lawyer crafts an argument, they're not just following procedural templates. They're reading the judge's previous opinions, sensing the emotional undercurrents of the case, understanding how this particular client's story fits into larger questions of justice and human nature. The legal argument emerges from that specific understanding of this specific situation.
AI can simulate both processes, but simulation isn't the same as experience. The question becomes: do we want the simulation, or do we want the real thing?
I think the answer depends on what we're optimizing for. If we just want efficiency—the fastest contract, the most prolific poetry output—then AI is probably the answer. But if we want the satisfaction of craft, the pleasure of making something with our own minds and hands, then we need to be more careful about where we deploy these tools.
This is where the "vintage activity" concept becomes relevant. After recording technology was invented, playing guitar didn't disappear. It became something people did for different reasons—not primarily to distribute music to large audiences, but for the pleasure of making music in the moment. Live performance became more valuable, not less.
I suspect something similar will happen with legal writing and poetry. The routine work—standard contracts, formulaic briefs, greeting card verses—will increasingly be automated. But the craft work, the instances where language needs to capture something uniquely human, will become more valuable, not less.
The lawyer who can sense what's really at stake in a case and translate that into compelling prose won't be replaced by AI. The poet who can find fresh language for universal experiences won't be supplanted by text generators. But both will need to be conscious about which parts of their work they're willing to automate and which parts they insist on doing themselves.
This requires a different kind of choice than previous generations faced. Stevens didn't have to decide whether to let a machine write his insurance reports so he could focus on poetry. Today's lawyer-poets have to actively choose craft over efficiency, presence over productivity.
The programmers who are navigating this transition successfully seem to fall into two camps. Some embrace the role of AI orchestrator, focusing on high-level architecture and letting machines handle the detailed implementation. Others specialize in the kinds of problems that still require deep, hands-on engagement with code.
Lawyers and poets face the same choice. Some will become AI managers, focusing on strategy and oversight while machines handle the routine language work. Others will double down on the irreducibly human aspects of their craft—the moments where language needs to carry not just information but genuine understanding.
Neither choice is wrong, but it's important to be conscious about which one you're making. If you became a lawyer because you love the feel of language taking shape under your hands, don't let efficiency arguments push you into a role you'll hate. If you write poetry because you need to find words for experiences that don't yet have words, don't let productivity tools turn you into a prompt engineer.
The great revelation from Paul Graham's essay is that hackers and painters are both makers—they're trying to create things that work and matter. The same is true of lawyers and poets. They're both trying to make language do something it hasn't done before: capture a specific aspect of human experience with precision and force.
AI can help with this work, but it can't do this work. The difference matters. Understanding the difference—between assistance and replacement, between tool and craftsperson—might be the most important skill for anyone who works with language in the age of AI.
What gives me hope is that the people who are most passionate about their craft seem to intuitively understand this distinction. My programmer friends aren't worried that AI will replace programming. They're worried that AI will replace the kind of programming they love. The solution isn't to reject AI, but to be intentional about how we use it.
Stevens walked to work because he needed the rhythm of his steps on the pavement to match the rhythm of verses forming in his mind. He couldn't have composed those poems sitting at his desk, and he certainly couldn't have composed them by prompting a text generator. The walking was part of the work, not just preparation for the work.
The question for contemporary lawyers and poets is simple: what's your equivalent of Stevens' morning walk? What part of your job/practice is irreducibly human? requiring your specific consciousness engaging with specific problems? That's the part to protect. That's the part that makes you a maker, not just a manager.
The rest can probably be automated. And that might not be a loss—it might be a liberation. If AI can handle the routine contracts and formulaic briefs, maybe lawyers can spend more time on the cases that actually matter. If text generators can produce stock poems and greeting card verses, maybe poets can focus on the lines that actually sing.
The future belongs not to people who can compete with machines at their own game, but to people who understand what games only humans can play. For lawyers and poets, that game is language itself—not just the patterns and structures that AI can learn, but the lived experience that gives those patterns meaning.
In the end, lawyers and poets face the same choice my programmer friends face: efficiency or craft, productivity or presence, optimization or love. The answer isn't obvious, and it isn't the same for everyone. But it's a choice worth making consciously, because the alternative—drifting into roles we never wanted—is a kind of professional sleepwalking.
The lawyers and poets who stay awake, who choose their relationship with AI rather than letting it choose them, will be the ones who keep language alive as a human art. And in a world of increasingly sophisticated machines, that might be the most important work of all.
Stevens wasn't unusual. Archibald MacLeish edited the Harvard Law Review before becoming a three-time Pulitzer Prize winner. Edgar Lee Masters was Clarence Darrow's law partner when he wrote Spoon River Anthology. Lawrence Joseph, a contemporary poet, puts it directly: "In the United States the language of law covers every social, economic and political issue... I've used it in my poetry."
What these lawyer-poets understood is what my programmer friend is rediscovering: the deep satisfaction of making something with your hands, whether those hands are holding a pen or typing code. There's a joy in finding exactly the right word, crafting the perfect sentence, building an argument that unfolds with inevitable logic. It's the same pleasure hackers get from elegant code or painters get from capturing light.
But there's a practical reason why so many poets have been lawyers. Law pays well enough to support poetry. Stevens could afford to walk to work composing verses because his insurance job provided financial stability. Poetry rarely pays the bills, but law often pays them quite generously. This isn't compromise—it's strategy. The day job enables the love work.
More importantly, the constraint of legal language can actually enhance poetic creativity. When you spend your days crafting precise, economical prose, you develop an ear for rhythm and an eye for the essential. Legal writing teaches you to cut every unnecessary word, to build arguments that flow inevitably from premise to conclusion. These are exactly the skills poetry demands.
Justice John Paul Stevens (no relation to Wallace) once said, "The study of English literature, especially lyric poetry, is the best preparation for the law." He was right, but the reverse is also true. Law is excellent preparation for poetry. Both require you to understand how language works on multiple levels simultaneously.
Now AI threatens to disrupt this symbiotic relationship. Language models can draft contracts, write briefs, and even compose poems. The same force that's pushing programmers away from hands-on coding is pushing lawyers toward becoming "legal project managers" and poets toward becoming "prompt engineers."
This is what I call the promotion paradox. The better AI gets at the core work, the more we risk being "promoted" away from the thing we actually love doing. Lawyers who entered the profession because they enjoyed crafting arguments find themselves managing AI outputs. Poets who love the feel of words in their mouth find themselves engineering prompts for text generators.
The parallel with programming is exact. My programmer friends didn't become a programmer to manage other programmers or oversee automated systems. Theybecame a programmer because they enjoy the puzzle of turning thoughts into code, the satisfaction of making software that actually works. When AI takes over the coding, they lose the thing they loved about the job.
But here's what I think both lawyers and poets can learn from hackers: the answer isn't to resist the tool, but to understand what the tool can't do.
AI is remarkably good at pattern matching and recombination. It can write a serviceable brief by following templates and precedents. It can generate poems that follow established forms and echo familiar themes. What it can't do—at least not yet—is understand what it means to be human in a specific moment with a particular problem.
When Stevens walked to work composing poetry, he wasn't just arranging words according to patterns he'd absorbed from other poems. He was processing his experience of being a middle-aged insurance executive in Hartford, Connecticut, watching the morning light hit familiar buildings, thinking about mortality and meaning and the strange beauty of ordinary life. The poetry emerged from that specific consciousness encountering that specific moment.
Similarly, when a skilled lawyer crafts an argument, they're not just following procedural templates. They're reading the judge's previous opinions, sensing the emotional undercurrents of the case, understanding how this particular client's story fits into larger questions of justice and human nature. The legal argument emerges from that specific understanding of this specific situation.
AI can simulate both processes, but simulation isn't the same as experience. The question becomes: do we want the simulation, or do we want the real thing?
I think the answer depends on what we're optimizing for. If we just want efficiency—the fastest contract, the most prolific poetry output—then AI is probably the answer. But if we want the satisfaction of craft, the pleasure of making something with our own minds and hands, then we need to be more careful about where we deploy these tools.
This is where the "vintage activity" concept becomes relevant. After recording technology was invented, playing guitar didn't disappear. It became something people did for different reasons—not primarily to distribute music to large audiences, but for the pleasure of making music in the moment. Live performance became more valuable, not less.
I suspect something similar will happen with legal writing and poetry. The routine work—standard contracts, formulaic briefs, greeting card verses—will increasingly be automated. But the craft work, the instances where language needs to capture something uniquely human, will become more valuable, not less.
The lawyer who can sense what's really at stake in a case and translate that into compelling prose won't be replaced by AI. The poet who can find fresh language for universal experiences won't be supplanted by text generators. But both will need to be conscious about which parts of their work they're willing to automate and which parts they insist on doing themselves.
This requires a different kind of choice than previous generations faced. Stevens didn't have to decide whether to let a machine write his insurance reports so he could focus on poetry. Today's lawyer-poets have to actively choose craft over efficiency, presence over productivity.
The programmers who are navigating this transition successfully seem to fall into two camps. Some embrace the role of AI orchestrator, focusing on high-level architecture and letting machines handle the detailed implementation. Others specialize in the kinds of problems that still require deep, hands-on engagement with code.
Lawyers and poets face the same choice. Some will become AI managers, focusing on strategy and oversight while machines handle the routine language work. Others will double down on the irreducibly human aspects of their craft—the moments where language needs to carry not just information but genuine understanding.
Neither choice is wrong, but it's important to be conscious about which one you're making. If you became a lawyer because you love the feel of language taking shape under your hands, don't let efficiency arguments push you into a role you'll hate. If you write poetry because you need to find words for experiences that don't yet have words, don't let productivity tools turn you into a prompt engineer.
The great revelation from Paul Graham's essay is that hackers and painters are both makers—they're trying to create things that work and matter. The same is true of lawyers and poets. They're both trying to make language do something it hasn't done before: capture a specific aspect of human experience with precision and force.
AI can help with this work, but it can't do this work. The difference matters. Understanding the difference—between assistance and replacement, between tool and craftsperson—might be the most important skill for anyone who works with language in the age of AI.
What gives me hope is that the people who are most passionate about their craft seem to intuitively understand this distinction. My programmer friends aren't worried that AI will replace programming. They're worried that AI will replace the kind of programming they love. The solution isn't to reject AI, but to be intentional about how we use it.
Stevens walked to work because he needed the rhythm of his steps on the pavement to match the rhythm of verses forming in his mind. He couldn't have composed those poems sitting at his desk, and he certainly couldn't have composed them by prompting a text generator. The walking was part of the work, not just preparation for the work.
The question for contemporary lawyers and poets is simple: what's your equivalent of Stevens' morning walk? What part of your job/practice is irreducibly human? requiring your specific consciousness engaging with specific problems? That's the part to protect. That's the part that makes you a maker, not just a manager.
The rest can probably be automated. And that might not be a loss—it might be a liberation. If AI can handle the routine contracts and formulaic briefs, maybe lawyers can spend more time on the cases that actually matter. If text generators can produce stock poems and greeting card verses, maybe poets can focus on the lines that actually sing.
The future belongs not to people who can compete with machines at their own game, but to people who understand what games only humans can play. For lawyers and poets, that game is language itself—not just the patterns and structures that AI can learn, but the lived experience that gives those patterns meaning.
In the end, lawyers and poets face the same choice my programmer friends face: efficiency or craft, productivity or presence, optimization or love. The answer isn't obvious, and it isn't the same for everyone. But it's a choice worth making consciously, because the alternative—drifting into roles we never wanted—is a kind of professional sleepwalking.
The lawyers and poets who stay awake, who choose their relationship with AI rather than letting it choose them, will be the ones who keep language alive as a human art. And in a world of increasingly sophisticated machines, that might be the most important work of all.
Share Dialog
Share Dialog
Abhishek Parolkar
Abhishek Parolkar
No comments yet