YouTube Digest

May 7, 2026

Listen to this issue

English

Based on โ€œWhy We Switched From Claude Code to Codexโ€ from Every Watch the original video

The Agent Evolution: Why Codex is Redefining How We Work

Three months ago, six months ago, if youโ€™d asked the team at Every, an AI-focused media company, about OpenAIโ€™s coding agent, Codex, the answer would have been unequivocal: โ€œIt was trash. I stand by that 100%.โ€ Yet, in a startling pivot that underscores the breakneck pace of AI development, Codex has not only shed its initial reputation but has become the โ€œdaily driverโ€ for many knowledge workers, heralding a new era of human-agent collaboration.

This dramatic shift, discussed by Everyโ€™s CEO Dan and Head of Growth Austin in a recent โ€œCodeex Campโ€ webinar, isnโ€™t just about a better AI model; itโ€™s about a fundamental redefinition of the operating system for how and where work gets done.

From โ€œTrashโ€ to Transformation: Codexโ€™s Rapid Ascent

OpenAIโ€™s initial vision for Codex, particularly around its GPT-5 release, was narrowly focused. It was designed for senior engineers, envisioned as a pair programming tool that would โ€œargue with you, it would make you feel stupid. It was like a little autistic, it didnโ€™t have any emotional intelligence.โ€ The strategy seemed to be: keep โ€œvibe codingโ€ in ChatGPT for general users, while senior engineers used a sandboxed, hobbled Codex for hardcore programming.

However, a competitor, Anthropic, disrupted this theory with their Claude Code model. Anthropic demonstrated the power of a model that was not only usable, fast, and smart but also โ€œemotionally intelligentโ€ โ€“ meaning it could understand context, adapt to user needs, and integrate seamlessly with a computerโ€™s environment. This proved to be a โ€œreally, really great experience for programmers,โ€ allowing them to discard old programming environments and simply โ€œtype commands into your terminal and then it would start working.โ€

Anthropicโ€™s innovation revealed a deeper truth: โ€œIf you have a great general-purpose coding agent on your computer, itโ€™s actually really great for any kind of knowledge work. If it can write software on its own, it can do any kind of knowledge work on its own.โ€ This insight triggered a โ€œhard pivotโ€ from OpenAI. Over the past three months, Codex has transformed from a โ€œsenior engineer only tool that is really for pair programmingโ€ into a versatile, general-purpose agent. Itโ€™s now equipped with the ability to write code, access file systems, utilize a browser, and is wrapped in a desktop application โ€“ an โ€œideal next step for knowledge work.โ€

The New Operating System: Agents as Your Interface

The core message from Every is clear: we are witnessing the emergence of a new operating system, an โ€œagent management interface,โ€ where an AI agent becomes your primary way of interacting with software, the internet, and your daily tasks. This isnโ€™t just about automation; itโ€™s about delegation and strategic partnership.

Austin, Everyโ€™s Head of Growth, experienced his โ€œagent pill momentโ€ earlier with Claude Code, diving deep into its command-line interface (CLI) to automate and enhance his strategic thinking, data analysis, and marketing copy. He found it โ€œthe only way I want to do the kind of knowledge work that requires strategic thinking and data analysis and shipping marketing copy.โ€

Despite his initial allegiance, Danโ€™s persistent nudges to try the new Codex led Austin to a revelation. While he initially found Codex โ€œnothing has ever made me feel more stupid than Codex like two months ago,โ€ the results were undeniable. The true differentiator, however, wasnโ€™t just the modelโ€™s capabilities but the application itself.

The Desktop App Advantage: Why Codex Pulled Ahead (for now)

โ€œTo me thereโ€™s no comparison for how fast and powerful the Codex desktop app is as just like an app compared to the Claude desktop app,โ€ Austin explains. He struggled to get Claudeโ€™s Co-work desktop app to function effectively, feeling โ€œruined by the Codex appโ€ due to its speed, the efficacy of its sub-agents, and its seamless automation suggestions.

Austinโ€™s workflow now begins and ends with Codex. โ€œWhen I sign on during the day, Codex is the first thing I open. It is pulling in whatever I need from Gmail, Slack, Notion, Stripe, all of our data sources. Itโ€™s where I spend like 80% of my time working overwhelmingly because the app itself is just so good. And then the model has now gotten good enough to be the daily driver for me.โ€

This isnโ€™t a trivial preference. Austin describes the โ€œlook of horrorโ€ on his friendsโ€™ faces, mostly Claude Code users, when he tells them heโ€™s fully transitioned to Codex. While Claude Code was โ€œgame changing,โ€ the idea that Codex might be โ€œ30 to 40% betterโ€ felt like a monumental hurdle for some. Yet, Austin insists the benefits are significant, highlighting the appโ€™s superior organization with folders for persistent chats and its ability to effortlessly switch between diverse tasks, from improving a KPI sheet to shipping a PR for a different product.

A Glimpse into the Agent-First Workflow

So, what does this agent-first world look like in practice? Austin provided several concrete examples:

Brainstorming Automations and โ€œDumb Agentsโ€

For new users, Austin recommends starting with a brainstorming automation workflow. He prompts Codex: โ€œGo take a look at the things I use the most, which are Notion, Slack, and Gmail, and think of some automations that would help me with my work.โ€ Codex analyzes his current activities and suggests tailored automations, such as:

  • Follow-up Radar: Triage incoming information from various sources (partnerships, social media).
  • Command Center: Manage complex events with multiple moving parts.
  • Recruiting/Hiring Pipeline: Sync and track candidates through Notion, handling much of the pipeline work.

These automations, Austin notes, โ€œjust work incredibly well,โ€ requiring minimal tweaking. He categorizes these as โ€œdumb agentsโ€ โ€“ those that consistently execute the right thing, like compiling unresponded messages at the end of the day and drafting replies, or even sending a simple Slack reaction.

Strategic Planning with โ€œSmart Agentsโ€

Beyond simple automations, agents can become strategic partners. Austin demonstrated this with a go-to-market plan for a new product. Instead of blocking off an entire day to synthesize information, he leveraged Codex. All the human thinking โ€“ the marketing case, business case, narratives โ€“ had already occurred in internal meetings and Slack conversations. Austin prompted Codex: โ€œCould you just make the plan?โ€

Codex, with access to meeting transcripts, Slack discussions, and Austinโ€™s preferred GTM template, generated an initial draft. After a quick refinement (reminding it to factor in scheduled posts), Codex produced a plan that was โ€œbasically 80 to 90% of the way there.โ€ This wasnโ€™t about the model creating the strategy, but about it assembling and reviewing the strategy from existing human thought.

โ€œBefore this was possible, the only thing I could have done was either block off a whole day to sit and do this or get done with my work for the day at like 6 or 7 and then stay up all night writing this,โ€ Austin reflects. This capability is a โ€œgame changer,โ€ especially for busy professionals who need to produce comprehensive documents in the โ€œcracks of their day.โ€

Managing Email and Sub-Agents

When asked about managing client emails and ensuring important leads arenโ€™t missed, Austin described a layered approach. He often uses Kora, an AI email assistant, but can direct it via Codexโ€™s CLI/API connector. His strategy involves:

  1. Agent Interview: Instead of dictating rules, he has the agent โ€œinterviewโ€ him to understand what constitutes a priority, what should be archived, or what requires a personalized response.
  2. Brain Dump: Using a speech-to-text app like Monologue, he articulates the problem (โ€œMy emailโ€™s a mess. Letโ€™s figure out how to triage it.โ€).
  3. Sub-Agents for Search: He prompts Codex to โ€œspawn sub-agents to do a search across different workflowsโ€ to analyze all his emails.
  4. Plan Review: Codex returns with a plan, which Austin reviews for any potential misinterpretations (e.g., archiving a money-making lead).
  5. Audit Reminders: He uses a task tracker (Todoist, connected to Codex) to set reminders to audit the new automationโ€™s performance after a few days, prompting the model to report what it has been archiving.

This highlights the flexibility and power of an agent that can orchestrate other tools and agents based on a deep understanding of user preferences and data.

Trust, Accountability, and the Rise of โ€œAgent Documentsโ€

A critical aspect of this agent-first world is the relationship between human and AI-generated content. Austin has a clear โ€œreview stepโ€: โ€œEverything I work primarily in Codex. I do all the drafting and setup in Codex and then itโ€™s helpful for my brain to have the final review step actually live in the external app.โ€ This means drafting Slack messages in Codex, but reviewing and sending them from Slack; creating email drafts in Codex, but finalizing them in Gmail. This external check โ€œfreshens up my brainโ€ and ensures human oversight before engaging with other people.

Dan champions the concept of โ€œagent documents,โ€ advocating for the normalization of AI-written content, especially using formats like Everyโ€™s โ€œProof docsโ€ (agent-friendly markdown files). He even suggests, โ€œI would actually prefer to read your agentโ€™s writing than your writing in a lot of cases because I know that itโ€™s just easier for you to get all that that thinking together in a format I can read if you have your agent write it.โ€

The underlying principle is accountability. If an AI generates a document, the human user is expected to โ€œstand behind all of it.โ€ Austin builds rules into his project files, such as โ€œdonโ€™t add anything that I havenโ€™t like said in another context,โ€ to ensure the AIโ€™s suggestions remain distinct from the final, human-approved output. This fosters a partnership where the AI handles the synthesis and formatting, but the human remains the ultimate strategic and factual authority.

The Great Agent Race: Whatโ€™s Next for Knowledge Work

This transformation isnโ€™t confined to OpenAI. Itโ€™s a โ€œhorse raceโ€ among major AI model companies, each developing their own agent management desktop apps:

  • OpenAI: With Codex
  • Anthropic: With Claude Code and Co-work
  • XAI: Having recently acquired Cursor
  • Google: Expected to follow suit, despite their current โ€œAnti-gravityโ€ not being widely adopted for this purpose.

This competition benefits users, making it โ€œfairly easy to switch betweenโ€ these tools. Users can even prompt Codex to โ€œgo grab all my Claude stuff,โ€ demonstrating a growing interoperability.

The future of work, as envisioned by Every, is one where the agent is your primary interface to software and the internet, enabling unprecedented delegation and creative partnership. This frees knowledge workers from the โ€œdumb stuffโ€ โ€“ the time-consuming tasks of formatting, compiling, and synthesizing information that has already been thought through. Instead, humans can focus on the deeper thinking, strategy, and creative problem-solving, with agents acting as powerful extensions of their will.

The days of manually clicking through dashboards and onboarding experiences may be numbered. In an agent-first world, AI can gather context, configure tools, and initiate workflows simply by being told what you want to achieve. This is not just a technological upgrade; itโ€™s a profound shift in how we conceive of and execute our daily work, promising a more powerful, efficient, and even โ€œfunโ€ way to navigate the complexities of knowledge work. The agent evolution is here, and itโ€™s rapidly reshaping our digital landscape.


Based on โ€œWas Adam Smith Really a Right-Winger? (Update) | Freakonomics Radioโ€ from Freakonomics Radio Network Watch the original video

Adam Smith: The Philosopher Caught in a Tug-of-War Over His Legacy

Adam Smith, the Scottish moral philosopher whose 1776 magnum opus, The Wealth of Nations, cemented his status as the first modern economist, remains a figure of intense debate and selective interpretation more than two centuries after his death. Far from a dusty historical artifact, Smithโ€™s ideas are perpetually resurrected and reframed, particularly in the ongoing ideological battles between proponents of free markets and those advocating for greater government intervention. Was Smith truly the patron saint of unbridled capitalism, or has his profound and nuanced philosophy been hijacked for modern political agendas?

The question of Smithโ€™s true leanings has sparked a โ€œraging debate in Smith scholarship,โ€ dividing experts into โ€œleft Smithiansโ€ and โ€œright Smithians.โ€ Yet, as Steven Dubner of Freakonomics Radio observes, โ€œwhether you are a left Smithian, a right Smithian, or even if youโ€™ve never heard of him, itโ€™s fair to say that we are all Smithians today.โ€ His influence is inescapable, but his meaning is anything but settled.

The Moral Compass: Beyond Self-Interest

Before The Wealth of Nations became his most famous work, Smith published The Theory of Moral Sentiments in 1759. At just 36, Smith, then a moral philosophy professor at the University of Glasgow, earned widespread praise for his writingโ€™s beauty and, more importantly, its profound humanity. Smith argued that wealth was not a prerequisite for moral virtue, nor was poverty a barrier to it.

As political scientist and Smith scholar Glory Liu highlights, Smith was deeply concerned with human sympathy and the potential for moral corruption. A striking passage from The Theory of Moral Sentiments underscores this: โ€œThis disposition to admire and almost to worship the rich and the powerful, and to despise, or at least to neglect persons of poor and mean condition, though necessary both to establish and to maintain the distinction of ranks and the order of society, is at the same time the great and most universal cause of the corruption of our moral sentiments.โ€ This early work reveals a Smith acutely aware of the social and moral complexities inherent in human ambition and societal structure.

After its success, Smith embarked on a European tour as a tutor, observing firsthand the burgeoning global trade and the onset of the Industrial Revolution. He noted governmentsโ€™ pervasive protectionist instincts, which he viewed as detrimental, advocating instead for greater openness to free trade. These observations would deeply inform his subsequent work.

The Birth of The Wealth of Nations: A Polemic for Its Time

Seventeen years after his first book, The Wealth of Nations was published in 1776, a year etched in history for other reasons โ€“ the death of Smithโ€™s close friend David Hume and, crucially, Britainโ€™s loss of its American colonies. Aean Butler, director of the free-market Adam Smith Institute in London, describes it as a โ€œpolemic against economic centralism and restrictions on trade.โ€

Smithโ€™s primary audience was the politicians of his day, whom he saw as misguided in their mercantilist fixation on accumulating gold and silver and resisting foreign goods. He believed wealth stemmed from production, not mere accumulation. Importantly, Smith was a staunch supporter of the American colonists, criticizing the British Empireโ€™s exploitative control over their trade. He famously derided the British Empireโ€™s colonial project as โ€œnot a gold mine but the project of a gold mine. A project which has cost which continues to cost and which if pursued in the same way as it has been hitherto is likely to cost immense expense without being likely to bring any profit.โ€

In the nascent United States, Smithโ€™s work was quickly recognized as a vital โ€œtechnical resource,โ€ a โ€œblueprintโ€ for national wealth. Figures like James Madison, Alexander Hamilton, and Thomas Jefferson devoured his analysis of commerce, agriculture, manufacturing, and trade. Hamilton even โ€œcribbed bits of Adam Smithโ€ for his reports on national banks. Smithโ€™s ideas became woven into the very fabric of the American experiment, though, as Glory Liu notes, he hadnโ€™t yet acquired the โ€œhaloโ€ of intellectual infallibility.

A Shifting Reputation: From Progressive Champion to Free-Market Messiah

Throughout the 19th and early 20th centuries, Smithโ€™s influence persisted, but his interpretation remained fluid. Both sides of the vigorous American debates on trade policy and tariffs cited Smith. Surprisingly, as the organized labor movement gained traction, progressive economists like Richard T. Ely argued that Smith would have unequivocally sided with unions. This progressive reading of Smith, however, stands in stark contrast to his modern reputation, which leans decidedly conservative or libertarian.

The pivotal shift in Smithโ€™s public image, according to Glory Liu, largely originated from the University of Chicagoโ€™s economics department in the mid-20th century. Early Chicago figures like Jacob Viner and Frank Knight initially taught Smith as an early theorist of price, using his work to lend scientific credibility to economics. But it was a later generationโ€”Friedrich Hayek, George Stigler, and Milton Friedmanโ€”who fundamentally reshaped Smithโ€™s legacy.

Liu argues that this new cohort โ€œsmoothed over or altogether obscured the complexities, tensions and other problematic aspects characteristic of earlier readings of Smith.โ€ They reinterpreted Smithian concepts like individualism, self-interest, and the โ€œinvisible handโ€ to justify a market-oriented society on social scientific grounds. Self-interest, which Smith had viewed as one human motivation among many (and one with potentially dangerous โ€œextreme versionsโ€), was elevated by Stigler to have โ€œthe most explanatory power.โ€ Stigler, who famously wore a t-shirt proclaiming โ€œAdam Smithโ€™s best friendโ€ (an endearing anecdote about his interaction with his familyโ€™s children), found in Smith the โ€œperfect mascotโ€ for his own free-market convictions.

Milton Friedman, a โ€œrhetorical genius,โ€ further popularized this interpretation. Through his public television show Free to Choose, Friedman presented the โ€œinvisible handโ€ as synonymous with the price mechanism โ€“ a magical phenomenon that efficiently coordinated the activities of millions without centralized planning. For Friedman, the market became a โ€œmoral thing in and of itself,โ€ its objective, scientific appearance implicitly prioritizing efficiency over other values like equity or democracy.

This Chicago School interpretation had a profound consequence: it โ€œreframed the problems of modern American capitalism and modern society as problems that stemmed from government rather than the market itself.โ€ Glory Liu points to the opioid epidemic as a contemporary example of market failure, where โ€œmarket incentives to push a drug onto the marketโ€ led to catastrophic human welfare costs, despite any purported โ€œefficiency in terms of allocation.โ€

The Invisible Hand: A Metaphor Misunderstood?

One of the most enduring and frequently misused phrases attributed to Smith is the โ€œinvisible hand.โ€ Dennis Rasmusen, a political scientist at Syracuse University, laments that the Chicago School โ€œpicked out the phrase the invisible hand, which he uses just two or three times in his writings and made that the central feature of who Smith was. To me, thatโ€™s unfortunate.โ€

Indeed, the phrase appears only once in The Wealth of Nations, in a passage discussing how a businessman, by preferring domestic over foreign industry for his own security and gain, is โ€œled by an invisible hand to promote an end which was no part of his intention.โ€ Craig Smith, another scholar from the University of Glasgow, clarifies that for Smith, it was merely a โ€œmetaphor for an unintended consequences explanation,โ€ not necessarily implying positive outcomes. Today, however, the โ€œinvisible handโ€ is commonly invoked to suggest that economic markets will operate perfectly well if left entirely unregulated, a notion far removed from Smithโ€™s original intent.

Dennis Rasmusen argues that this selective reading ignores Smithโ€™s keen awareness of โ€œthe real potential drawbacks and dangers of commercial society.โ€ Smith recognized โ€œthe ways that commerce can produce great inequalities, the ways that wealthy merchants and manufacturers collude against the public interest, and above all, the way that the desire for wealth often leads people to submit to endless toil and anxiety in the pursuit of just frivolous material goods that will produce only fleeting satisfaction.โ€ While Smith ultimately defended commercial society, he did so not as an apologist for its perfection, but as a pragmatic choice, believing its faults were less numerous and severe than those of other societal forms.

Adam Smith and the Thatcher Revolution

The conservative, free-market interpretation of Adam Smith found its most zealous champion in British Prime Minister Margaret Thatcher. Aean Butler and his Adam Smith Institute (ASI), founded in London in 1977, were perfectly positioned to capitalize on her ascent. Inspired by American free-market thinkers like Friedman and Hayek, Butler and his colleagues, disillusioned with Britainโ€™s plummeting economy, returned from the US with a mission to import free-market ideas.

When Thatcher was elected in 1979, the ASI found an โ€œopen goal.โ€ Thatcher, the โ€œdaughter of a shopkeeper,โ€ was an ideological leader determined to run the economy prudently and challenge the prevailing centrist consensus. She famously declared, โ€œThere is no such thing as public money. There is only taxpayers money.โ€

The ASI became a key intellectual engine for Thatcherโ€™s reforms. They famously published a 12-foot-long single-page book listing 3,68 quangos (quasi-autonomous non-governmental organizations), leading to a civil service purge. They advocated for contracting out local government services and, most significantly, provided the intellectual framework for the massive privatization program that saw state-owned industries like telephones, gas, water, electricity, steel, and railways transferred to the private sector. Butler defends these privatizations as a โ€œgreat exercise in promoting a capital-owning democracy,โ€ citing the sale of council houses to tenants at a discount and the increased competition in previously nationalized industries.

However, not all of Thatcherโ€™s vision was realized. The National Health Service (NHS), a beloved institution in the UK, remains public. Butler, while acknowledging its popular support, describes it as a โ€œtop-down Stalinist style organizationโ€ and โ€œgrotesquely inefficient,โ€ advocating for its privatization. His advice to any current Prime Minister, like Rishi Sunak, would be to drastically reform government systems, cut the โ€œbloated civil service,โ€ simplify the โ€œmost complicated tax system in the world,โ€ and reform planning laws to reduce bureaucratic hurdles.

The Adam Smith Problem: Two Books, One Philosopher?

The enduring debate over Smithโ€™s legacy often boils down to what 19th-century German scholars termed โ€œdas Adam Smith Problemโ€โ€”the perceived inconsistency between the compassionate humanist of The Theory of Moral Sentiments and the architect of capitalism in The Wealth of Nations.

Mariana Mazzucato, an economist at University College London, represents a โ€œleft Smithianโ€ perspective, arguing that Smithโ€™s concept of a โ€œfree marketโ€ didnโ€™t mean โ€œfree from the state,โ€ but โ€œfree from rent, free from extraction of value from the system.โ€ She contends Smith would be appalled by modern โ€œexcess profitsโ€ in energy and mining, or the use of trillions for share buybacks, viewing them as โ€œmodern-day feudal kind of value extraction.โ€

Crucially, Smith himself, in Book Five of The Wealth of Nations, explicitly supported government provision of services like education, infrastructure, and law and order. He argued that โ€œfor a very small expense, the public can facilitate, can encourage, and can even impose upon almost the whole body of the people the necessity of acquiring those most essential parts of education.โ€ Aean Butler, however, dismisses this section as โ€œa little bit rushed,โ€ suggesting Smith was under pressure to finish the book and that these arguments werenโ€™t the โ€œmain thrustโ€ of his work. This selective reading, while perhaps pragmatic for a free-market advocate, highlights the challenge of interpreting a voluminous and complex text.

Glory Liu, however, rejects โ€œdas Adam Smith Problemโ€ as a โ€œpseudo problem.โ€ She argues that the perceived inconsistency stems from a desire for philosophical consistency, particularly among German scholars, rather than an accurate reflection of Smithโ€™s holistic thought. For Liu, Smithโ€™s works are not contradictory but complementary, offering a comprehensive view of human morality and societal organization that encompasses both individual action and the necessary role of institutions.

An Enduring Legacy of Contradiction and Complexity

Adam Smithโ€™s legacy is a testament to the power of ideas and the malleability of interpretation. From a moral philosopher concerned with human sympathy to the alleged architect of unbridled capitalism, his reputation has been a battleground for competing economic and political philosophies. He was neither a simple right-winger nor a clear-cut progressive, but a thinker whose observations on human nature and economic systems were rich with nuance and complexity.

The ongoing โ€œtug-of-warโ€ over Adam Smith reminds us that historical figures are not static icons but dynamic sources of inspiration and contention. His works, though often more cited than read, continue to shape our understanding of markets, government, and the very nature of wealth, proving that the search for the โ€œreal Adam Smithโ€ is far from over.


Based on โ€œQuests, token leaderboards, and a skills marketplace: the elite AI adoption playbook | John Kimโ€ from How I AI Watch the original video

The Elite Playbook: How One Company is Forging an โ€œAI Firstโ€ Culture with Quests, Leaderboards, and a Skills Marketplace

In the rapidly evolving landscape of artificial intelligence, many companies grapple with the challenge of widespread AI adoption. Itโ€™s often reduced to a directive of โ€œdo more with less,โ€ leaving employees feeling pressured rather than empowered. However, John Kim, founder and CEO of Sunbird, offers a refreshing and profoundly effective alternative: a gamified, empowering, and deeply integrated approach that transforms AI adoption from a corporate mandate into a vibrant, creative, and measurable movement.

Sunbirdโ€™s strategy isnโ€™t just about using AI as a tool; itโ€™s about making AI an integral part of the workforce, unleashing creativity, and fostering a culture where every employee can become an AI builder. This isnโ€™t merely a program; itโ€™s a product, meticulously designed to inspire, enable, and measure an โ€œAI Firstโ€ transformation.

Beyond Efficiency: Unleashing Creativity with AI

The conventional wisdom around AI often centers on efficiencyโ€”automating tasks, reducing costs, and accelerating processes. While these are certainly benefits, Sunbirdโ€™s approach highlights a more profound outcome: the liberation of human creativity and the ability to pursue โ€œbigger ambitions and honestly, more fun things.โ€

A prime example of this philosophy in action is their โ€œBig S Energyโ€ swag store. This entire e-commerce site, offering timely and culturally relevant merchandise, was conceived and built by Sunbirdโ€™s marketing team without any engineering support. Imagine a marketing department with a brilliant, quirky ideaโ€”like a t-shirt proclaiming โ€œMy ass is bigger than your SaaSโ€โ€”that can bring it to life, integrate payment systems, and launch it to the market in a matter of days. This rapid deployment of creative ideas, once bottlenecked by engineering roadmaps and prioritization cycles, is now a reality. The store even features a secret Konami code Easter egg, a playful nod to gamers that unlocks details for their upcoming โ€œDelight Sparkโ€ conference, further demonstrating the fun and ambition that AI empowers.

As the interviewer, Clarvo, aptly notes, this shifts the focus from โ€œcan we prioritize it?โ€ to โ€œlet marketers cook.โ€ When the cost of building something fun and delightful becomes cheap, companies can afford to be more playful, leading to more engaging customer experiences and higher team engagement.

The โ€œAI Firstโ€ Mandate: Integrating AI into the Workforce

Sunbirdโ€™s overarching ambition is to become an โ€œAI Firstโ€ company. This means going beyond simple tool adoption to truly embedding AI into the fabric of their operations and empowering every individual. To facilitate this company-wide transformation, they developed an internal platform called the Automator Platform.

This platform is more than just a repository of tools; itโ€™s a dynamic ecosystem designed to connect AI needs with AI builders within the company. It serves as the central hub for their unique approach to AI adoption, enabling anyone to initiate a โ€œquestโ€ and contribute to the companyโ€™s AI evolution.

Gamifying Innovation: Quests, Rewards, and a Thriving Skills Marketplace

At the heart of Sunbirdโ€™s AI adoption strategy is a brilliantly gamified system that encourages participation, learning, and collaboration.

The Quest System

The Automator Platform allows any employee to โ€œraise their hand and create what we call the quest.โ€ A quest represents an AI automation or tool needed within the company. For instance, a finance department might initiate a quest to automate accounts receivable and payable workflows.

What makes this system revolutionary is its marketplace-like nature:

  • AI Needs Meet AI Builders: Employees with specific needs can post quests, and others with AI building skills (or the desire to learn) can โ€œpop in and say, โ€˜Oh, I think I know how to do that.โ€™โ€
  • Bypassing Bureaucracy: Quests operate outside the traditional, often cumbersome, software development lifecycle and sprint prioritization. This allows for rapid ideation and deployment of solutions that might otherwise be deemed too small or niche for the main product roadmap.
  • AI-Assisted Development: In a groundbreaking move, AI agents can now read quest specifications, create Product Requirement Documents (PRDs), and even start coding. This significantly accelerates development and serves as a powerful learning tool for human builders.
  • Immediate Value & Dopamine Hits: The direct connection between a quest giver (user) and a quest builder means immediate feedback and visible impact, providing an โ€œinstantaneous dopamine hitโ€ upon delivery.

Each quest is transparently displayed, showing its potential risk, estimated weeks saved, and the benefiting team, creating a clear picture of its value.

Earning XP and Recognition

To further incentivize participation, the quest system incorporates gamified rewards:

  • Experience Points (XP): Completing quests earns builders experience points.
  • Tangible Rewards: Accumulated XP can be exchanged for gift cards, a private tea with an executive, or the opportunity to present their built solution to the entire company.
  • Spotlight on Innovation: Weekly stand-ups feature different teamsโ€”often non-engineering teamsโ€”showcasing their AI creations, fostering a culture of peer learning and recognition.

The Company-Wide Skills Marketplace

Recognizing that many teams might be building similar functionalities in silos, Sunbird established a company-wide skills marketplace. Here, employees can create and download โ€œpluginsโ€ or individual โ€œskillsโ€โ€”collections of AI capabilities. For example, a sales team can access a โ€œMEDIC framework advisorโ€ skill, learning about the sales methodology and plugging it directly into their workflows.

This marketplace promotes co-evolution, prevents redundant work, and serves as a central repository for encoding institutional knowledge and best practices into reusable AI components. It organically trains employees on the concept of โ€œskillsโ€ as they see them in action and shared across the organization.

Building the Foundation: Secure Infrastructure and a Dedicated AI Team

Empowering every employee to build with AI requires a robust and secure underlying infrastructure. Sunbird has meticulously crafted this foundation, ensuring that creativity doesnโ€™t come at the expense of compliance or security.

Templated โ€œHappy Pathsโ€ to Production

One of the most practical and impactful elements of their strategy is the creation of โ€œapp templates.โ€ These templates provide pre-configured, fully compliant, and secure environments with all necessary authentication and infrastructure already set up.

  • Simplified Development: Marketers or customer success managers no longer need to worry about the complexities of GitHub setup, security protocols, or database integration. They simply โ€œextract the template and just build it on top of it.โ€
  • Accelerated Velocity: This โ€œhappy pathโ€ approach significantly reduces friction, allowing non-technical users to bring their ideas to production rapidly and securely.
  • โ€œRight-Sizedโ€ Security: By providing pre-vetted stacks, Sunbird ensures that internal tools are built with appropriate security from the outset, preventing the proliferation of insecure, shadow IT projects.

The AI Engineer for Internal Operations Team

To maintain and evolve this critical infrastructure, Sunbird established a dedicated team: the AI Engineer for Internal Operations. This mouthful of a title signifies a crucial role: accelerating the companyโ€™s AI transformation.

  • Cross-Functional Mandate: Reporting directly to the CEO and Chief of Staff, this team has the authority and support to work across all functions, partnering closely with CTO, engineering, and infosec teams.
  • Unblocking Challenges: They meet weekly to address compliance issues, logging best practices, and vetting software, ensuring a smooth path for AI builders.
  • Organic Origins: This team didnโ€™t emerge from a top-down directive; it grew out of the success of early, non-engineering employees who built personal tools and demonstrated the immense potential, prompting leadership to invest in dedicated infrastructure.

Measuring Mastery: The AI Token Leaderboard

A cornerstone of Sunbirdโ€™s AI strategy is its transparent and gamified measurement of AI usage through a token consumption leaderboard. While acknowledging the historical pitfalls of measuring developer productivity by lines of code, John Kim emphasizes that their goal is not performance review, but rather understanding learning curves and fostering engagement.

The Dashboard and Metrics

The dashboard provides a real-time view of AI usage:

  • Company-Level Usage: Tracking overall token consumption, revealing trends (e.g., Cloud Code vs. Codecs preference for different tasks).
  • โ€œSmoothing the Curveโ€: A unique metric that tracks the consistency of token consumption. A smooth curve indicates that AI partners are working around the clock, even when human employees are on vacation, highlighting AIโ€™s autonomous potential.
  • Individual and Team-Level Usage: Managers can see their team membersโ€™ usage, enabling tailored enablement strategies.

The Five Tiers of AI Mastery

To gamify and guide the learning journey, Sunbird categorizes employees into five tiers based on their daily token consumption:

  1. Beginner
  2. Intermediate
  3. Expert
  4. Architect
  5. Catalyst
  6. AI God (spending over 100 million tokens a day)

Managers use this framework to understand where their team members stand and provide appropriate support, ensuring that beginners receive the right tools to quickly advance. John Kim himself, a self-proclaimed โ€œCatalyst,โ€ averages 30-50 million tokens a day, demonstrating that even leaders are active participants in this ecosystem.

This transparent measurement system sends a clear signal: AI proficiency is an expectation, not just an option. Itโ€™s about setting clear visions for what โ€œAI nativeโ€ looks like at individual, organizational, and functional levels.

Real-World Impact: From Swag Stores to Social Campaigns

The impact of Sunbirdโ€™s AI-first approach is evident in concrete, high-value projects:

  • The Marketing SAS Portal: Beyond the swag store, the marketing team has built an entire suite of AI-powered tools for their operations. This โ€œmarketing SASโ€ includes interview planners, marketing calendars, account-based marketing tools, competitor reviews, and real-time metrics, all built, managed, and used daily by the marketing team without external engineering support.
  • The โ€œBuzzboardโ€ Campaign: A recent example is a tool called โ€œBuzzboard,โ€ which allows the marketing team to create campaigns, track social shares, and identify top internal engagers. It enables them to manage real-time campaigns, such as a San Francisco billboard promotion, where they can select AI-generated billboard designs, choose pre-configured copy, and post directly to LinkedIn, all within their self-built tool.

These examples underscore a critical shift: companies are no longer just seeking external SaaS solutions. Instead, they are asking, โ€œCan we build it internally?โ€ This leads to highly customized โ€œmicro software solutionsโ€ that perfectly align with a companyโ€™s unique culture and workflow, rather than simply functionally replicating an external vendor. This era marks the โ€œrevenge of the internal tools team,โ€ transforming a previously overlooked function into a vibrant, green-field opportunity for innovation and impact.

AI for Personal Growth: The Gardener and Learning Centers

Beyond corporate applications, John Kim also demonstrates the profound personal utility of AI.

  • The โ€œGardenerโ€ Project: An open-source project John built for himself, โ€œThe Gardenerโ€ acts as an AI assistant for personal knowledge bases (like Obsidian notes). It daily combs through notes, enriches content, researches unregistered names, fixes errors, and creates beautiful headings and cross-links, effectively โ€œtendingโ€ to oneโ€™s digital garden of knowledge.
  • Personal AI Learning Centers: John showcases AI-generated learning centers on topics like neuroscience, quantum mechanics, and fusion. By providing a prompt to an AI model, he can generate a beautifully structured, interconnected knowledge base tailored to his learning style. This โ€œbest teacher with the most in-depth knowledge and an endless willingness to go do researchโ€ is right at his fingertips, allowing for deeply engaging and customized learning experiences that grow with oneโ€™s understanding. This concept holds immense potential for education, offering personalized learning environments for complex subjects, even for children.

The Leadership Playbook: Cultivating an AI-First Culture

For executives looking to replicate Sunbirdโ€™s success, John Kim offers a clear playbook:

Find and Empower the Curious

โ€œThere are always people in your organization who are already curious, who already have agency. Find them. Make them the champions. Give them the spotlight. Let them share their fun things.โ€ By building energy around these early adopters and providing them with confidence, organizations can create a viral effect for AI adoption.

Lead by Example

Leadership buy-in is paramount. At Sunbird, the top token consumers include the CTO, co-founder, and chief architect. This signals to the entire team that AI is not just a passing trend but a critical, integrated part of their work, inspiring others to follow suit.

Embrace โ€œFail Forwardโ€

โ€œThis is a beautiful time to fail forward and still get up and run faster than the others.โ€ Encouraging experimentation and accepting that not every attempt will be perfect fosters a culture of innovation where learning from mistakes is celebrated.

Redefining Hiring

Sunbird has actively re-evaluated job descriptions for AI-relevant roles, lowering the bar for traditional tenure or experience. Instead, they optimize for three key attributes: high curiosity, high agency, and high energy. These are the individuals who will naturally โ€œfigure things out and learn on their own,โ€ leveraging the accessible and affordable power of AI.

The journey to becoming an โ€œAI Firstโ€ company is not without its humorous moments. John Kim, a former professional gamer, admits to feeling more addicted to AI coding than games, experiencing the same builder energy he had as a teenager. His prompting strategy for AI reflects this unique perspective: โ€œI want to like start building a nice relationship with them and so that when the Skynet takes over, Iโ€™m like, โ€˜Well, John was pretty nice to us, you know, like weโ€™ll let him live a few years longer.โ€™โ€

Sunbirdโ€™s approach provides a compelling blueprint for any organization seeking to harness the full potential of AI. By empowering employees, gamifying adoption, building robust infrastructure, and leading by example, they are not just adopting AI; they are cultivating a thriving culture of innovation, creativity, and continuous learning, setting a new standard for the โ€œelite AI adoption playbook.โ€


Based on โ€œPresident Trumpโ€™s Sudden U-Turn, and a $1 Billion Ballroom Proposalโ€ from New York Times Podcasts Watch the original video

The Shifting Sands of Power: Trumpโ€™s U-Turn, AIโ€™s Impact, and a Billion-Dollar Ballroom

The past week unfurled a series of unexpected pivots and profound shifts, demonstrating the volatile nature of global politics, the relentless march of technology, and the enduring human spirit in the face of change. From a sudden reversal in Middle East policy to the unsettling economic implications of artificial intelligence, and even the fading flames of a geological wonder, the headlines painted a picture of a world in flux, grappling with both immediate crises and the dawning of new eras.

Geopolitical Whiplash: Trumpโ€™s Iran U-Turn

The week began with a clear, assertive stance from the Trump administration regarding the conflict with Iran. Secretary of State Marco Rubio confidently declared that the โ€œEpic Furyโ€ operation was over, and the United States was now embarking on โ€œProject Freedom.โ€ This new mission, as Rubio explained, involved escorting ships through the strategic Strait of Hormuz, a waterway whose closure had been inflicting significant economic havoc worldwide. Defense Secretary Pete Hgsth echoed this sentiment, hailing the effort as โ€œa direct gift from the United States to the world,โ€ and proudly announcing the establishment of โ€œa powerful red, white, and blue dome over the strait.โ€ The message was unequivocal: America was asserting its presence, protecting global commerce, and bringing stability to a volatile region.

Yet, just one day into Project Freedom, and after only a handful of ships had successfully navigated the strait, President Trump executed a dramatic U-turn. In a social media post, he announced that Project Freedom was being put on hold, citing โ€œgreat progress toward a long-term peace deal with Iran.โ€ He further stated that the pause was requested by Pakistan, which had been mediating the peace talks, along with other unnamed countries.

The abrupt reversal left many observers perplexed. At present, both Iran and the U.S. continue to claim control of the strait, and maritime traffic remains at a standstill. Analysts suggest that the Iranian government believes it holds the upper hand, confident in its ability to withstand economic pressureโ€”a strategy it has employed successfully in the pastโ€”for longer than the Trump administration can tolerate the rising global energy prices. This diplomatic whiplash underscores the unpredictable nature of international relations and the personal influence of the presidency in shaping foreign policy.

Domestic Political Maneuvers and a Controversial Proposal

Closer to home, the political landscape also saw its share of strategic plays and power dynamics. Vice President JD Vance embarked on a critical tour, attempting to rally support for Republican candidates ahead of the midterms. In Iowa, a state vital for the GOP, Vance faced a challenging audience of farmers struggling with high fertilizer prices and the lingering effects of Trumpโ€™s tariff policies. While acknowledging their plight, Vance downplayed the broader geopolitical context, remarking, โ€œAs the president of the United States has said, we got a little a little blip in the Middle East. We got to take care of some business on the foreign policy side.โ€ His stops in Iowa and Oklahoma are seen as a blueprint for his efforts to boost GOP candidates nationwide, who are contending with the headwinds of high gas prices and the unpopular war in Iran.

Meanwhile, in Indiana, President Trump demonstrated the enduring strength of his influence within the Republican party. He delivered on a promise of โ€œpaybackโ€ against several state senators who had defied his push to redraw election maps the previous year. The primary elections served as a litmus test for the presidentโ€™s sway over Republican voters, and the results were decisive: at least five of the seven senators who had opposed him lost their seats to Trump-backed challengers. This outcome solidified Trumpโ€™s position as a kingmaker within the GOP, capable of punishing dissent and rewarding loyalty.

Perhaps the most surprising domestic development, however, came from Washington, where Senate Republicans quietly inserted a staggering $1 billion for a โ€œballroom projectโ€ into a funding bill slated for a quick passage through Congress. The measure, which doesnโ€™t explicitly mention a ballroom, instead allocates funds for โ€œEast Wing security enhancements.โ€ While President Trump had previously stated that renovations for the proposed ballroom would be privately funded, some congressional Republicans began pushing for federal funding after a recent incident at the White House correspondentsโ€™ dinner. The $1 billion provision is strategically tucked into an immigration enforcement funding bill, a move designed to bypass any potential Democratic filibuster and ensure its swift approval. The controversial allocation raises questions about fiscal priorities and the use of federal funds for projects that were initially promised to be privately financed.

The AI Revolution and an Unprepared Safety Net

Beyond the political arena, a more profound, long-term shift is underway, driven by the rapid advancements in artificial intelligence. This past week saw yet another major tech company, Coinbase, announce widespread layoffs, explicitly stating that it was โ€œoptimizing for AI.โ€ The cryptocurrency exchange is cutting 14% of its workforceโ€”approximately 700 employeesโ€”with its CEO explaining that the changes will lead to โ€œsmaller teams with humans managing the work of AI agents.โ€ This follows similar significant job cuts or buyouts at industry giants like Microsoft and Meta, both of which have also attributed their workforce reductions, in part, to AI and the necessity of embracing this new technology.

The implications extend beyond job losses to a reduction in new job openings, prompting serious concerns among economists and labor market experts. Ben Castleman, the Timesโ€™ chief economics correspondent, highlights a critical consensus: โ€œour safety net is not ready for an age of AI-driven job disruption.โ€ He points to two major shortcomings in the existing system.

Firstly, the unemployment insurance system, designed as the primary line of defense for those who lose their jobs, may fail to cover a substantial portion of workers most vulnerable to AI disruption. Castleman specifically notes that new graduates, a group economists believe could be hardest hit, often do not qualify for unemployment benefits due to lack of prior work history.

Secondly, the โ€œlast line of defenseโ€ against severe hardshipโ€”programs like food stamps and Medicaidโ€”have been restructured to primarily cover individuals who are working. This means that if someone loses their job due to AI or any other reason, they also lose access to these crucial safety net components. While economists remain divided on whether AI will lead to mass unemployment, they largely agree that disruptions are inevitable and people will lose their jobs. The consensus is clear: โ€œthis is the time to start aligning our safety net with that coming wave of disruption. And so far, that really has not happened.โ€ The urgent call is for proactive policy changes to prepare society for the economic shifts that AI is already beginning to unleash.

The Price of Passion: World Cupโ€™s Dynamic Dilemma

In the realm of global sports, the upcoming World Cup, set to kick off in the U.S., Mexico, and Canada, is introducing a significant and controversial change: dynamic pricing for tickets. For the first time ever, FIFA is adjusting ticket prices based on the popularity of teams, leading to a stark impact on passionate fans, particularly those in countries where soccer is a national obsession.

The Times checked in with fans in Argentina, where the national teamโ€™s victory in the last World Cup has sent ticket prices for this yearโ€™s games soaring. Many Argentinian fans, accustomed to attending previous tournaments, expressed shock and frustration. One fan, who had attended World Cups in Russia and Qatar, recalled paying less than a hundred dollars for tickets in the past. Now, they are looking at prices exceeding the average monthly salary in Argentina, with one individual needing to spend $3,000 for just three tickets.

The exorbitant costs are forcing many to reconsider their dreams of attending. Some are simply giving up, while others are going to extreme lengths, racking up debt and maxing out credit cards. FIFA has consistently defended its dynamic pricing strategy, arguing that the income is essential to fund soccer development worldwide. However, for many Argentinian fans, it feels like a โ€œcash grab.โ€ As one fan, likely unable to attend this year, poignantly put it, โ€œIt makes you angry that they take something that should be for everyone and turn it into something that is just for the few.โ€ The World Cup, once a global celebration accessible to many, now risks becoming an exclusive event for the privileged.

The Gates to Hell: A Fiery Enigma Fading

Finally, an update on one of the worldโ€™s most baffling and captivating tourist attractions: the Gates to Hell in Turkmenistan. Officially known as the Darvaza crater, local lore suggests its fiery existence began over 60 years ago when Soviet geologists, drilling for oil, accidentally hit a gas deposit. The ground collapsed, forming a massive pit, and to mitigate the toxic fumes, scientists decided to light the gas on fire, expecting it to burn out in a few weeks. It has been burning ever since, captivating researchers and adventurous tourists alike.

Recent data from a company monitoring natural gas flares, however, indicates that the eternal flames might not be so eternal after all. Infrared imaging reveals that the intensity of heat from the pit has decreased by 75% over the last few years. The exact reasons for this decline remain unclear, as do the long-term implications. The flames currently burn off methane leaking from the pit, preventing this potent greenhouse gas from entering the atmosphere. If the fire diminishes further or extinguishes, it could lead to increased methane emissions, posing a new environmental challenge.

For those inspired to witness this fiery spectacle before it potentially fades, thereโ€™s still hope. A tour guide recently assured the Times that on a trip, it was still โ€œhot enough that his group roasted marshmallows over it.โ€ The Gates to Hell, a testament to human error and geological forces, continues its slow, uncertain transformation, reminding us that even the most enduring wonders are subject to change.

From the shifting sands of geopolitical power and domestic politics to the profound societal impacts of technological advancement and the evolving face of global events, the past week has underscored a world in constant motion. Each story, in its own way, reflects the intricate dance between human agency and broader forces, shaping our present and hinting at the many transformations yet to come.


ํ•œ๊ตญ์–ด

โ€œWhy We Switched From Claude Code to Codexโ€ โ€” Every ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

ํด๋กœ๋“œ ์ฝ”๋“œ์—์„œ ์ฝ”๋ฑ์Šค๋กœ: ์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜ ์ž‘์—… ํ๋ฆ„์˜ ํ˜์‹ ๊ณผ Every์˜ ์ „ํ™˜ ์‚ฌ๋ก€

์ตœ๊ทผ ์ธ๊ณต์ง€๋Šฅ(AI) ๊ธฐ์ˆ ์€ ๊ฐœ๋ฐœ ํ™˜๊ฒฝ์„ ๋„˜์–ด ์ง€์‹ ๋…ธ๋™ ์ „๋ฐ˜์— ๊ฑธ์ณ ํ˜๋ช…์ ์ธ ๋ณ€ํ™”๋ฅผ ๊ฐ€์ ธ์˜ค๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ ์—์ด์ „ํŠธ(Agent) ๊ธฐ๋ฐ˜์˜ ์ž‘์—… ํ๋ฆ„์€ ์šฐ๋ฆฌ๊ฐ€ ์ผํ•˜๋Š” ๋ฐฉ์‹์˜ ์ƒˆ๋กœ์šด ์šด์˜ ์ฒด์ œ๋กœ ๋ถ€์ƒํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ณ€ํ™”์˜ ์„ ๋‘์— ์„  ๋ฏธ๋””์–ด ๊ธฐ์—… Every๋Š” ์ตœ๊ทผ ํด๋กœ๋“œ ์ฝ”๋“œ(Claude Code)์—์„œ ์ฝ”๋ฑ์Šค(Codex)๋กœ์˜ ๋Œ€๋Œ€์ ์ธ ์ „ํ™˜์„ ๋ฐœํ‘œํ•˜๋ฉฐ, ๊ทธ ๋ฐฐ๊ฒฝ๊ณผ ์‹ค์ œ ํ™œ์šฉ ์‚ฌ๋ก€๋ฅผ ๊ณต์œ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋ฒˆ ๊ธ€์—์„œ๋Š” Every์˜ ๋ฆฌ๋”์‹ญ ํŒ€์ด ํด๋กœ๋“œ ์ฝ”๋“œ์—์„œ ์ฝ”๋ฑ์Šค๋กœ ์ „ํ™˜ํ•˜๊ฒŒ ๋œ ๊ฒฐ์ •์ ์ธ ์ด์œ ์™€, ์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜์˜ ์ƒˆ๋กœ์šด ์—…๋ฌด ํ™˜๊ฒฝ์ด ์–ด๋–ป๊ฒŒ ์ƒ์‚ฐ์„ฑ๊ณผ ์ฐฝ์˜์„ฑ์„ ๊ทน๋Œ€ํ™”ํ•˜๋Š”์ง€ ์‹ฌ์ธต์ ์œผ๋กœ ๋‹ค๋ฃน๋‹ˆ๋‹ค.

์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜ ์ž‘์—…์˜ ๋ถ€์ƒ: ์ฝ”๋ฑ์Šค์˜ ๊ทน์ ์ธ ๋ณ€ํ™”

3~6๊ฐœ์›” ์ „๋งŒ ํ•ด๋„ ์ฝ”๋ฑ์Šค(Codex)๋Š” โ€œ์“ธ๋ชจ์—†๋Š”(trash)โ€ ๋„๊ตฌ๋กœ ํ‰๊ฐ€๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. OpenAI์—์„œ ๊ฐœ๋ฐœํ•œ ์ดˆ๊ธฐ ์ฝ”๋ฑ์Šค๋Š” ์ฃผ๋กœ ์ˆ™๋ จ๋œ ์—”์ง€๋‹ˆ์–ด๋“ค์˜ ํŽ˜์–ด ํ”„๋กœ๊ทธ๋ž˜๋ฐ(Pair Programming)์„ ์œ„ํ•ด ์„ค๊ณ„๋˜์—ˆ์œผ๋‚˜, ์‚ฌ์šฉ์ž์™€ ๋…ผ์Ÿํ•˜๊ณ  ๊ฐ์„ฑ ์ง€๋Šฅ์ด ๋ถ€์กฑํ•˜์—ฌ ์‚ฌ์šฉ์ž๋“ค์„ ์ขŒ์ ˆ์‹œํ‚ค๋Š” ๊ฒฝํ–ฅ์ด ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค.

์ดˆ๊ธฐ์˜ ์ฝ”๋ฑ์Šค: โ€œ์“ธ๋ชจ์—†๋˜โ€ ๊ฐœ๋ฐœ์ž ๋„๊ตฌ

Every์˜ CEO๋Š” ์ดˆ๊ธฐ์˜ ์ฝ”๋ฑ์Šค์— ๋Œ€ํ•ด โ€œ100% ์“ธ๋ชจ์—†์—ˆ๋‹คโ€๊ณ  ๋‹จ์–ธํ–ˆ์Šต๋‹ˆ๋‹ค. ๋‹น์‹œ OpenAI๋Š” GPT-5 ์ถœ์‹œ์™€ ํ•จ๊ป˜ โ€˜์ž์œ ๋กœ์šด ์ฝ”๋”ฉ(Vibe Coding)โ€˜์€ ์ฑ—GPT(ChatGPT)์—์„œ, ์ „๋ฌธ์ ์ธ ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์ž‘์—…์€ ์ฝ”๋ฑ์Šค์—์„œ ์ด๋ฃจ์–ด์งˆ ๊ฒƒ์ด๋ผ๋Š” ์ „๋žต์„ ๊ฐ€์ง€๊ณ  ์žˆ์—ˆ๋˜ ๊ฒƒ์œผ๋กœ ๋ณด์ž…๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ฝ”๋ฑ์Šค ๋ชจ๋ธ์€ ์•ˆ์ „์„ ์œ„ํ•ด ์ƒŒ๋“œ๋ฐ•์Šค(Sandbox) ํ™˜๊ฒฝ์— ๊ฐ‡ํ˜€ ๊ธฐ๋Šฅ์ด ์ œํ•œ์ ์ด์—ˆ๊ณ , ์‚ฌ์šฉ์ž์™€์˜ ์ƒํ˜ธ์ž‘์šฉ์—์„œ ๊ฐ์„ฑ ์ง€๋Šฅ์ด ๊ฒฐ์—ฌ๋˜์–ด ๋งˆ์น˜ โ€œ์•ฝ๊ฐ„ ์žํ์ ์ธโ€ ๋А๋‚Œ์„ ์ฃผ์—ˆ๋‹ค๊ณ  ํšŒ๊ณ ํ•ฉ๋‹ˆ๋‹ค.

์•คํŠธ๋กœํ”ฝ์˜ ์„ ์ : ํด๋กœ๋“œ ์ฝ”๋“œ์˜ ์ง€์‹ ์ž‘์—… ํ™•์žฅ

๊ทธ๋Ÿฌ๋‚˜ ๊ฒฝ์Ÿ์‚ฌ์ธ ์•คํŠธ๋กœํ”ฝ(Anthropic)์€ ๋‹ค๋ฅธ ๋ฐฉํ–ฅ์œผ๋กœ ์ ‘๊ทผํ–ˆ์Šต๋‹ˆ๋‹ค. ์•คํŠธ๋กœํ”ฝ์€ ์‚ฌ์šฉํ•˜๊ธฐ ์‰ฝ๊ณ  ๋น ๋ฅด๋ฉฐ ์Šค๋งˆํŠธํ•˜๋ฉด์„œ๋„ โ€˜๊ฐ์„ฑ ์ง€๋Šฅโ€™์„ ๊ฐ–์ถ˜ ๋ชจ๋ธ์„ ์ปดํ“จํ„ฐ์—์„œ ์ง์ ‘ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜๋Š” ๊ฒƒ์ด ํ”„๋กœ๊ทธ๋ž˜๋จธ๋“ค์—๊ฒŒ ์—„์ฒญ๋‚œ ๊ฒฝํ—˜์„ ์ œ๊ณตํ•œ๋‹ค๋Š” ๊ฒƒ์„ ๊นจ๋‹ฌ์•˜์Šต๋‹ˆ๋‹ค. ํด๋กœ๋“œ ์ฝ”๋“œ(Claude Code)๋Š” ๋‹จ์ˆœํžˆ ์ฝ”๋“œ๋ฅผ ์ž‘์„ฑํ•˜๋Š” ๊ฒƒ์„ ๋„˜์–ด, ์ปดํ“จํ„ฐ์— ์ ‘๊ทผํ•˜์—ฌ ํŒŒ์ผ์„ ๊ด€๋ฆฌํ•˜๊ณ  ์›น ๋ธŒ๋ผ์šฐ์ง•์„ ์ˆ˜ํ–‰ํ•˜๋Š” ๋“ฑ โ€˜๋ชจ๋“  ์ข…๋ฅ˜์˜ ์ง€์‹ ์ž‘์—…โ€™์„ ์Šค์Šค๋กœ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ์Œ์„ ์ž…์ฆํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ํด๋กœ๋“œ ์ฝ”๋“œ์˜ ์„ฑ๊ณต์€ ํ”„๋กœ๊ทธ๋ž˜๋จธ๋“ค์ด ์ž์‹ ์˜ ์ž‘์—…์„ ์œ„์ž„ํ•˜๋Š” ๋ฐฉ์‹๋ฟ๋งŒ ์•„๋‹ˆ๋ผ, ๋ชจ๋“  ์ง€์‹ ๋…ธ๋™์ž๊ฐ€ ์ž์‹ ์˜ ์—…๋ฌด๋ฅผ ์—์ด์ „ํŠธ์—๊ฒŒ ์œ„์ž„ํ•˜๋Š” ์ƒˆ๋กœ์šด ์‹œ๋Œ€๋ฅผ ์—ด์—ˆ์Šต๋‹ˆ๋‹ค.

OpenAI์˜ ์ „๋žต์  ์ „ํ™˜: ์ฝ”๋ฑ์Šค์˜ ์žฌํƒ„์ƒ

์•คํŠธ๋กœํ”ฝ์˜ ํด๋กœ๋“œ ์ฝ”๋“œ๊ฐ€ ์‹œ์žฅ์—์„œ ํฐ ๋ฐ˜ํ–ฅ์„ ์ผ์œผํ‚ค์ž, OpenAI๋Š” ์ง€๋‚œ 3๊ฐœ์›”๊ฐ„ ์ฝ”๋ฑ์Šค์— ๋Œ€ํ•œ โ€˜ํ•˜๋“œ ํ”ผ๋ฒ—(Hard Pivot)โ€˜์„ ๋‹จํ–‰ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ณผ๊ฑฐ ์ˆ™๋ จ๋œ ์—”์ง€๋‹ˆ์–ด๋งŒ์„ ์œ„ํ•œ ํŽ˜์–ด ํ”„๋กœ๊ทธ๋ž˜๋ฐ ๋„๊ตฌ์˜€๋˜ ์ฝ”๋ฑ์Šค๋Š” ์ด์ œ Every์˜ CEO์—๊ฒŒ โ€œ๋งค์ผ ์‚ฌ์šฉํ•˜๋Š”(daily driver)โ€ ๋„๊ตฌ๊ฐ€ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ฝ”๋ฑ์Šค๋ฅผ ์‹ฌ์ธต์ ์ธ ์—”์ง€๋‹ˆ์–ด๋ง ์ž‘์—…๋ถ€ํ„ฐ ๊ธ€์“ฐ๊ธฐ, ์ธ์žฌ ์ฑ„์šฉ(recruiting)์— ์ด๋ฅด๊ธฐ๊นŒ์ง€ ๋ชจ๋“  ๋ถ„์•ผ์— ํ™œ์šฉํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

OpenAI๋Š” ์ฝ”๋ฑ์Šค๋ฅผ ์ผ๋ฐ˜ ๋ชฉ์ ์˜ ์—์ด์ „ํŠธ(General Purpose Agent)๋กœ ๋ฐœ์ „์‹œ์ผœ, ์ฝ”๋“œ ์ž‘์„ฑ ๋Šฅ๋ ฅ, ํŒŒ์ผ ์‹œ์Šคํ…œ ์ ‘๊ทผ ๋Šฅ๋ ฅ, ๋ธŒ๋ผ์šฐ์ € ๊ธฐ๋Šฅ ๋“ฑ์„ ๋ฐ์Šคํฌํ†ฑ ์•ฑ์— ํ†ตํ•ฉํ•จ์œผ๋กœ์จ ์ง€์‹ ์ž‘์—…์˜ ์ด์ƒ์ ์ธ ๋‹ค์Œ ๋‹จ๊ณ„(ideal next step)๋ฅผ ์ œ์‹œํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  Every๋Š” ํ˜„์žฌ๊นŒ์ง€ ์ฝ”๋ฑ์Šค๊ฐ€ ๊ทธ ์ตœ๊ณ ์˜ ๊ตฌํ˜„์ฒด๋ผ๊ณ  ํ‰๊ฐ€ํ•ฉ๋‹ˆ๋‹ค.

์ƒˆ๋กœ์šด ์šด์˜ ์ฒด์ œ: ์—์ด์ „ํŠธ ๊ด€๋ฆฌ ์ธํ„ฐํŽ˜์ด์Šค์˜ ์‹œ๋Œ€

์ด์ œ ์—…๋ฌด๋ฅผ ์ˆ˜ํ–‰ํ•˜๋Š” ๋ฐฉ์‹๊ณผ ์žฅ์†Œ์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ์šด์˜ ์ฒด์ œ(Operating System)๊ฐ€ ๋“ฑ์žฅํ–ˆ์Šต๋‹ˆ๋‹ค. ๋ฐ”๋กœ โ€˜์—์ด์ „ํŠธ ๊ด€๋ฆฌ ์ธํ„ฐํŽ˜์ด์Šค(Agent Management Interface)โ€˜์ž…๋‹ˆ๋‹ค. ์ด๋Š” ํด๋กœ๋“œ ์ฝ”๋“œ๋‚˜ ์ฝ”๋ฑ์Šค ๊ฐ™์€ ๋ฐ์Šคํฌํ†ฑ ์•ฑ์„ ํ†ตํ•ด ์—์ด์ „ํŠธ๋ฅผ ๊ด€๋ฆฌํ•˜๋Š” ๋ฐฉ์‹์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

๋ฐ์Šคํฌํ†ฑ ์•ฑ ์ „์Ÿ: ๋ชจ๋ธ ๊ธฐ์—…๋“ค์˜ ๊ฒฝ์Ÿ

ํ˜„์žฌ AI ๋ชจ๋ธ ๊ธฐ์—…๋“ค์€ ์—์ด์ „ํŠธ ๊ด€๋ฆฌ๋ฅผ ์œ„ํ•œ ๋ฐ์Šคํฌํ†ฑ ์•ฑ ์‹œ์žฅ์—์„œ ์น˜์—ดํ•œ ๊ฒฝ์Ÿ์„ ๋ฒŒ์ด๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ฐ ๋ชจ๋ธ ํšŒ์‚ฌ๋Š” ํ”„๋กœ๊ทธ๋ž˜๋ฐ ์—์ด์ „ํŠธ๋ฅผ ํ•ต์‹ฌ์œผ๋กœ ํ•˜๋Š” ์ง€์‹ ์ž‘์—…์šฉ ์—์ด์ „ํŠธ ๊ด€๋ฆฌ ํ‘œ๋ฉด(surface)์„ ์ œ๊ณตํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

  • ์•คํŠธ๋กœํ”ฝ(Anthropic): ํด๋กœ๋“œ ์ฝ”๋“œ(Claude Code)์™€ ํด๋กœ๋“œ ์ฝ”์›Œํฌ(Claude Co-work)
  • OpenAI: ์ฝ”๋ฑ์Šค(Codex)
  • XAI: ์ตœ๊ทผ ์ปค์„œ(Cursor)๋ฅผ ์ธ์ˆ˜
  • ๊ตฌ๊ธ€(Google): ์•ˆํ‹ฐ๊ทธ๋ผ๋น„ํ‹ฐ(Anti-gravity)๋ฅผ ๋ณด์œ ํ•˜๊ณ  ์žˆ์œผ๋‚˜ ์•„์ง ๋„๋ฆฌ ์‚ฌ์šฉ๋˜์ง€๋Š” ์•Š์Œ

Every๋Š” ์ด๋Ÿฌํ•œ ๊ฒฝ์Ÿ์ด ์‚ฌ์šฉ์ž์—๊ฒŒ ํฐ ์ด์ ์„ ์ œ๊ณตํ•œ๋‹ค๊ณ  ๋ด…๋‹ˆ๋‹ค. ํ˜„์žฌ๋Š” ๊ฐ ์•ฑ ๊ฐ„์˜ ์ „ํ™˜์ด ๋น„๊ต์  ์‰ฌ์›Œ, ์‚ฌ์šฉ์ž๋“ค์ด ์—ฌ๋Ÿฌ ๋„๊ตฌ๋ฅผ ์˜ค๊ฐ€๋ฉฐ ์—์ด์ „ํŠธ ์šฐ์„ (Agent-First) ์„ธ์ƒ์˜ ๊ฒฝํ—˜์„ ์ฒด๊ฐํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์ฝ”๋ฑ์Šค์—๊ฒŒ ํด๋กœ๋“œ ๊ด€๋ จ ์ž‘์—…์„ ๊ฐ€์ ธ์˜ค๋„๋ก ์š”์ฒญํ•˜๋ฉด ์ด๋ฅผ ์ˆ˜ํ–‰ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

์—์ด์ „ํŠธ ์šฐ์„ (Agent-First) ์„ธ์ƒ์˜ ์ด์ 

์—์ด์ „ํŠธ๊ฐ€ ์†Œํ”„ํŠธ์›จ์–ด์™€ ์ธํ„ฐ๋„ท์— ์ ‘๊ทผํ•˜๊ณ  ์‚ฌ์šฉํ•˜๋Š” ์ฃผ๋œ ๋ฐฉ์‹์ด ๋˜๋ฉด, ์ด์ „์—๋Š” ๋ถˆ๊ฐ€๋Šฅํ–ˆ๋˜ ํฅ๋ฏธ๋กœ์šด ๊ฐ€๋Šฅ์„ฑ๋“ค์ด ์—ด๋ฆฝ๋‹ˆ๋‹ค. ์—์ด์ „ํŠธ์—๊ฒŒ ๋‹ค๋ฅธ ์†Œํ”„ํŠธ์›จ์–ด์™€ ๋Œ€ํ™”ํ•˜๊ณ  ์ •๋ณด๋ฅผ ๊ฐ€์ ธ์˜ค๋„๋ก ์ง€์‹œํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์šฐ๋ฆฌ๊ฐ€ ๋งค์ผ ์‚ฌ์šฉํ•˜๋Š” ์ˆ˜๋งŽ์€ ์†Œํ”„ํŠธ์›จ์–ด์™€ ์—…๋ฌด์˜ ์ธํ„ฐํŽ˜์ด์Šค๊ฐ€ ์—์ด์ „ํŠธ๊ฐ€ ๋˜๋Š” ์„ธ์ƒ์„ ์˜๋ฏธํ•˜๋ฉฐ, Every๋Š” ์ด๋ฅผ โ€œ์ •๋ง ์žฌ๋ฏธ์žˆ๊ณ  ๋ฉ‹์ง„โ€ ๊ฒฝํ—˜์œผ๋กœ ๋ฌ˜์‚ฌํ•ฉ๋‹ˆ๋‹ค.

Every์˜ ์„ฑ์žฅ ์ฑ…์ž„์ž ์˜ค์Šคํ‹ด์˜ ๊ฒฝํ—˜: ์ฝ”๋ฑ์Šค ์ „ํ™˜์˜ ๊ฒฐ์ •์  ๊ณ„๊ธฐ

Every์˜ ์„ฑ์žฅ ์ฑ…์ž„์ž ์˜ค์Šคํ‹ด(Austin)์€ ์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜ ์ž‘์—… ํ๋ฆ„์˜ ์—ด๋ ฌํ•œ ์ง€์ง€์ž์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” โ€˜์—์ด์ „ํŠธ ๊ฐ์„ฑ(Agent Pill Moment)โ€˜์„ ๊ฒฝํ—˜ํ•˜๋ฉฐ ํด๋กœ๋“œ ์ฝ”๋“œ์—์„œ ์ฝ”๋ฑ์Šค๋กœ ์™„์ „ํžˆ ์ „ํ™˜ํ•˜๊ฒŒ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

โ€˜์—์ด์ „ํŠธ ๊ฐ์„ฑโ€™์˜ ์ˆœ๊ฐ„: ํด๋กœ๋“œ ์ฝ”๋“œ์˜ ๊ฐ•๋ ฅํ•จ

์˜ค์Šคํ‹ด์˜ โ€˜์—์ด์ „ํŠธ ๊ฐ์„ฑโ€™์€ 3~4๊ฐœ์›” ์ „ ํด๋กœ๋“œ ์ฝ”๋“œ์˜ CLI(Command Line Interface) ๋ฒ„์ „์„ ๊นŠ์ด ํŒŒ๊ณ ๋“ค๋ฉด์„œ ์ฐพ์•„์™”์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ํด๋กœ๋“œ ์ฝ”๋“œ๋ฅผ ์—…๋ฌด์™€ ๊ฐœ์ธ ์ƒํ™œ์— ์‚ฌ์šฉํ•˜๋Š” ๋ชจ๋“  ๋„๊ตฌ์— ์—ฐ๊ฒฐํ–ˆ๊ณ , ์ด๋ฅผ ํ†ตํ•ด ์ž๋™ํ™”ํ•  ์ˆ˜ ์žˆ๋Š” ์ž‘์—…์˜ ์–‘๊ณผ ํด๋กœ๋“œ๊ฐ€ โ€˜์‚ฌ๊ณ  ํŒŒํŠธ๋„ˆ(Thought Partner)โ€˜๋กœ์„œ ์ž์‹ ์˜ ์ž‘์—…์„ ๊ฐœ์„ ํ•˜๋Š” ๋ฐฉ์‹์— ๊นŠ์€ ์ธ์ƒ์„ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” โ€œ์ „๋žต์  ์‚ฌ๊ณ , ๋ฐ์ดํ„ฐ ๋ถ„์„, ๋งˆ์ผ€ํŒ… ๋ฌธ๊ตฌ ์ž‘์„ฑ ๋“ฑ ์—ฌ๋Ÿฌ ์•ฑ๊ณผ ๋„๊ตฌ์— ๋ถ„์‚ฐ๋˜์–ด ์žˆ๋˜ ์ง€์‹ ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•˜๋Š” ์œ ์ผํ•œ ๋ฐฉ๋ฒ•โ€์ด๋ผ๊ณ  ๋А๊ผˆ์Šต๋‹ˆ๋‹ค.

์ฝ”๋ฑ์Šค ๋ฐ์Šคํฌํ†ฑ ์•ฑ์˜ ์••๋„์ ์ธ ์šฐ์œ„

Every์˜ CEO๋Š” ์˜ค์Šคํ‹ด์—๊ฒŒ ์ฝ”๋ฑ์Šค๋ฅผ ์‚ฌ์šฉํ•ด๋ณด๋ผ๊ณ  ์ง€์†์ ์œผ๋กœ ๊ถŒ์œ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ฒ˜์Œ์—๋Š” ์ฝ”๋ฑ์Šค๊ฐ€ ์ž์‹ ์„ โ€œ์–ด๋ฆฌ์„๊ฒŒ ๋งŒ๋“ค์—ˆ๋‹คโ€๊ณ  ๋А๋‚„ ์ •๋„๋กœ ์–ด๋ ค์› ์ง€๋งŒ, ์•ฑ ๊ตฌ์ถ• ๋Šฅ๋ ฅ์€ ๋›ฐ์–ด๋‚˜๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‹ค ํ•œ ๋‹ฌ ์ „ ์ƒˆ๋กœ์šด GPT ๋ชจ๋ธ(GPT 5.5)์„ ์‚ฌ์šฉํ•˜๊ฒŒ ๋˜๋ฉด์„œ ์ƒํ™ฉ์ด ๊ธ‰๋ณ€ํ–ˆ์Šต๋‹ˆ๋‹ค.

์˜ค์Šคํ‹ด์€ ์ตœ์‹  GPT ๋ชจ๋ธ์ด ํด๋กœ๋“œ ์˜คํ‘ธ์Šค(Opus) ๋ชจ๋ธ๊ณผ ์ง€์‹ ์ž‘์—… ๋Šฅ๋ ฅ์—์„œ ์ตœ์†Œํ•œ ๋™๋“ฑํ•œ ์ˆ˜์ค€์— ๋„๋‹ฌํ–ˆ๋‹ค๊ณ  ํ‰๊ฐ€ํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ์—๊ฒŒ ์ง„์ •ํ•œ ์ฐจ๋ณ„์ ์€ ๋ฐ”๋กœ ์ฝ”๋ฑ์Šค ๋ฐ์Šคํฌํ†ฑ ์•ฑ์˜ ์••๋„์ ์ธ ์†๋„์™€ ์„ฑ๋Šฅ์ด์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ํด๋กœ๋“œ ๋ฐ์Šคํฌํ†ฑ ์•ฑ(์ฝ”์›Œํฌ)๊ณผ ๋น„๊ตํ•  ๋•Œ ์ฝ”๋ฑ์Šค ์•ฑ์ด ํ›จ์”ฌ ๋น ๋ฅด๊ณ  ๊ฐ•๋ ฅํ•˜๋ฉฐ, ์„œ๋ธŒ ์—์ด์ „ํŠธ(Sub-agents) ๊ธฐ๋Šฅ๊ณผ ์ž๋™ํ™” ์ œ์•ˆ ๋ฐ ์‹คํ–‰ ๋Šฅ๋ ฅ์ด ํƒ์›”ํ•˜๋‹ค๊ณ  ๊ฐ•์กฐํ–ˆ์Šต๋‹ˆ๋‹ค.

โ€œ์ €์—๊ฒŒ๋Š” ์ฝ”๋ฑ์Šค ๋ฐ์Šคํฌํ†ฑ ์•ฑ์˜ ์†๋„์™€ ๊ฐ•๋ ฅํ•จ์— ๋น„ํ•  ๋ฐ”๊ฐ€ ์—†์Šต๋‹ˆ๋‹ค. ํด๋กœ๋“œ ๋ฐ์Šคํฌํ†ฑ ์•ฑ๊ณผ ๋น„๊ตํ•  ์ˆ˜ ์—†์–ด์š”. ์ฝ”์›Œํฌ๊ฐ€ ์ œ๋Œ€๋กœ ์ž‘๋™ํ•˜๋Š” ๊ฒƒ์„ ๋ณธ ์ ์ด ์—†๋Š”๋ฐ, ์•„๋งˆ ์ฝ”๋ฑ์Šค ์•ฑ์— ๋„ˆ๋ฌด ์ต์ˆ™ํ•ด์ ธ ๋ฒ„๋ ธ๊ธฐ ๋•Œ๋ฌธ์ผ ๊ฒ๋‹ˆ๋‹ค. ๋„ˆ๋ฌด ๋น ๋ฅด๊ณ , ์„œ๋ธŒ ์—์ด์ „ํŠธ๋„ ๋„ˆ๋ฌด ํ›Œ๋ฅญํ•˜๊ณ , ์ž๋™ํ™”๋ฅผ ์ œ์•ˆํ•˜๊ณ  ์‹คํ–‰ํ•˜๋Š” ๋ฐฉ์‹์ด ์ •๋ง ๋Œ€๋‹จํ•ด์„œ, ์ด๊ฑธ ์‚ฌ์šฉํ•˜์ง€ ์•Š๋Š” ๊ฑด ์ƒ์ƒํ•  ์ˆ˜ ์—†์–ด์š”.โ€

์ผ์ƒ ์—…๋ฌด์˜ ์ค‘์‹ฌ: ์ฝ”๋ฑ์Šค์™€์˜ 80% ์‹œ๊ฐ„

์ด์ œ ์˜ค์Šคํ‹ด์—๊ฒŒ ์ฝ”๋ฑ์Šค๋Š” ํ•˜๋ฃจ๋ฅผ ์‹œ์ž‘ํ•  ๋•Œ ๊ฐ€์žฅ ๋จผ์ € ์—ฌ๋Š” ์•ฑ์ด ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์ฝ”๋ฑ์Šค๋Š” Gmail, Slack, Notion, Stripe ๋“ฑ ๋ชจ๋“  ๋ฐ์ดํ„ฐ ์†Œ์Šค์—์„œ ํ•„์š”ํ•œ ์ •๋ณด๋ฅผ ๊ฐ€์ ธ์˜ต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์—…๋ฌด ์‹œ๊ฐ„์˜ ์•ฝ 80%๋ฅผ ์ฝ”๋ฑ์Šค ์•ฑ์—์„œ ๋ณด๋‚ธ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์บ ํ”„(์ด๋ฒคํŠธ)๋ฅผ ์œ„ํ•œ ์‹คํ–‰ ๊ณ„ํš(Run of Show)์„ ๋งŒ๋“ค ๋•Œ, ์ฝ”๋ฑ์Šค์—๊ฒŒ ๋ฉ”์‹œ์ง€๋ฅผ ๋ณด๋‚ด๋ฉด ๊ณผ๊ฑฐ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด ๋‚ด์šฉ์„ ํŒŒ์•…ํ•˜๊ณ  Notion์— ๊ณ„ํš์„ ํ‘ธ์‹œํ•œ ํ›„ Slack์œผ๋กœ ๊ณต์œ ํ•˜๋Š” ์ผ๋ จ์˜ ๊ณผ์ •์„ ์™„๋ฒฝํ•˜๊ฒŒ ์ˆ˜ํ–‰ํ•ฉ๋‹ˆ๋‹ค.

์ฝ”๋ฑ์Šค ํ™œ์šฉ์˜ ์‹ค์ œ ์‚ฌ๋ก€: ์ƒ์‚ฐ์„ฑ์„ ๊ทน๋Œ€ํ™”ํ•˜๋Š” ๋ฐฉ๋ฒ•

์˜ค์Šคํ‹ด์€ ์ฝ”๋ฑ์Šค๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ฐœ์ธํ™”๋œ ์ž๋™ํ™”๋ฅผ ๊ตฌ์ถ•ํ•˜๊ณ  ๋ณต์žกํ•œ ์—…๋ฌด๋ฅผ ํšจ์œจ์ ์œผ๋กœ ์ฒ˜๋ฆฌํ•˜๋Š” ๋‹ค์–‘ํ•œ ๋ฐฉ๋ฒ•์„ ์‹œ์—ฐํ–ˆ์Šต๋‹ˆ๋‹ค.

๋งž์ถคํ˜• ์ž๋™ํ™” ๊ตฌ์ถ•: โ€œEvery Growth OSโ€ ํด๋”

์˜ค์Šคํ‹ด์€ ์ฝ”๋ฑ์Šค ์•ฑ ๋‚ด์— โ€˜Every Growth OSโ€™๋ผ๋Š” ํด๋”๋ฅผ ๋งŒ๋“ค์–ด ์‚ฌ์šฉํ•ฉ๋‹ˆ๋‹ค. ์ด ํด๋”์—๋Š” Every ๋น„์ฆˆ๋‹ˆ์Šค์— ๋Œ€ํ•œ ์„ค๋ช…, ๋ชฉํ‘œ, ํ˜‘์—… ๋ฐฉ์‹ ๋“ฑ์„ ๋‹ด์€ ํ”„๋กœ์ ํŠธ ์ง€์นจ ํŒŒ์ผ๊ณผ ํ•จ๊ป˜, ํšŒ์‚ฌ์˜ ๋น„๋ฐ€ ํ‚ค์™€ ๊ฐ™์€ ๋ฏผ๊ฐํ•œ ์ •๋ณด๋“ค์ด ์•ˆ์ „ํ•˜๊ฒŒ ์—ฐ๊ฒฐ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ๋˜ํ•œ, ํšŒ์‚ฌ์˜ โ€˜์ปดํŒŒ์šด๋“œ ์—”์ง€๋‹ˆ์–ด๋ง(Compound Engineering)โ€™ ํ”Œ๋Ÿฌ๊ทธ์ธ์—์„œ ํŒŒ์ƒ๋œ ๋งž์ถคํ˜• ๋ฆฌ๋ทฐ์–ด ์—์ด์ „ํŠธ(Reviewer Agents)๋“ค์ด ํฌํ•จ๋˜์–ด ์žˆ์–ด, ์ „๋žต์  ๋ชฉํ‘œ ์ •๋ ฌ ๋ฐ ๋ฐ์ดํ„ฐ ์ •ํ™•์„ฑ ๋“ฑ ํŠน์ • ๊ธฐ์ค€์— ๋งž์ถฐ ๊ณ„ํš์„ ๊ฒ€ํ† ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

์˜ค์Šคํ‹ด์˜ ์ถ”์ฒœ ์ž๋™ํ™” ํ”„๋กฌํ”„ํŠธ

์ƒˆ๋กœ์šด ๋ชจ๋ธ์ด๋‚˜ ์•ฑ์„ ์‹œ์ž‘ํ•  ๋•Œ, ์˜ค์Šคํ‹ด์€ ์—์ด์ „ํŠธ์—๊ฒŒ ์Šค์Šค๋กœ ์‚ฌ์šฉ ๋ฐฉ๋ฒ•์„ ์ œ์•ˆํ•˜๋„๋ก ์š”์ฒญํ•˜๋Š” ๊ฒƒ์„ ์„ ํ˜ธํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๊ฐ€ ์ถ”์ฒœํ•˜๋Š” ํ”„๋กฌํ”„ํŠธ๋Š” ๋‹ค์Œ๊ณผ ๊ฐ™์Šต๋‹ˆ๋‹ค.

โ€œ์ œ๊ฐ€ ๊ฐ€์žฅ ๋งŽ์ด ์‚ฌ์šฉํ•˜๋Š” Notion, Slack, Gmail์„ ์‚ดํŽด๋ณด์‹œ๊ณ , ์ œ ์—…๋ฌด์— ๋„์›€์ด ๋  ๋งŒํ•œ ์ž๋™ํ™” ๋ช‡ ๊ฐ€์ง€๋ฅผ ์ œ์•ˆํ•ด ์ฃผ์„ธ์š”.โ€

์ฝ”๋ฑ์Šค๋Š” ํ˜„์žฌ ํšŒ์‚ฌ์˜ ์ƒํ™ฉ์„ ๋ถ„์„ํ•˜์—ฌ โ€˜ํ›„์† ์กฐ์น˜ ๋ ˆ์ด๋”(Follow-up Radar)โ€˜(๋‹ค์–‘ํ•œ ์†Œ์Šค์—์„œ ๋“ค์–ด์˜ค๋Š” ์ •๋ณด๋ฅผ ๋ถ„๋ฅ˜), โ€˜๋ช…๋ น ์„ผ์„œ(Command Sensor)โ€˜(์ด๋ฒคํŠธ ๊ด€๋ฆฌ), โ€˜์ฑ„์šฉ ๋ฐ ๊ณ ์šฉ ํŒŒ์ดํ”„๋ผ์ธ(Recruiting and Hiring Pipeline)โ€˜(Notion ๊ธฐ๋ฐ˜)๊ณผ ๊ฐ™์€ ์œ ์šฉํ•œ ์ž๋™ํ™” ์•„์ด๋””์–ด๋ฅผ ์ œ์•ˆํ–ˆ์Šต๋‹ˆ๋‹ค.

์ž๋™ํ™”์˜ ํ’ˆ์งˆ๊ณผ ์‹ค์ œ ์ ์šฉ

์ฝ”๋ฑ์Šค๊ฐ€ ์ œ์•ˆํ•œ ์ž๋™ํ™”๋“ค์€ ๋†€๋ผ์šธ ์ •๋„๋กœ ์ž˜ ์ž‘๋™ํ•˜๋ฉฐ, ๊ฑฐ์˜ ์ˆ˜์ • ์—†์ด ๋ฐ”๋กœ ์‚ฌ์šฉํ•  ์ˆ˜ ์žˆ์—ˆ์Šต๋‹ˆ๋‹ค. ์˜ค์Šคํ‹ด์€ ์—์ด์ „ํŠธ๊ฐ€ ์ƒ์„ฑํ•˜๋Š” ์ž๋™ํ™”๋ฅผ โ€˜์–ด๋ฆฌ์„์€ ์—์ด์ „ํŠธ(Dumb Agent)โ€˜์™€ โ€˜๋˜‘๋˜‘ํ•œ ์—์ด์ „ํŠธ(Smart Agent)โ€˜๋กœ ๋ถ„๋ฅ˜ํ•ฉ๋‹ˆ๋‹ค.

  • ์–ด๋ฆฌ์„์€ ์—์ด์ „ํŠธ: ๋งค๋ฒˆ ์˜ฌ๋ฐ”๋ฅธ ์ผ์„ ํ•˜๋Š” ๋‹จ์ˆœํ•œ ์ž๋™ํ™”. ์˜ˆ๋ฅผ ๋“ค์–ด, ๋งค์ผ ์—…๋ฌด ์ข…๋ฃŒ ์‹œ์ ์— ๋ฏธ์‘๋‹ต ๋ฉ”์‹œ์ง€๋ฅผ ์ทจํ•ฉํ•˜๊ณ  ๋‹ต์žฅ ์ดˆ์•ˆ์„ ์ž‘์„ฑํ•˜์—ฌ Slack ์ด๋ชจํ‹ฐ์ฝ˜ ๋ฐ˜์‘๋งŒ์œผ๋กœ ๋ณด๋‚ผ ์ˆ˜ ์žˆ๋„๋ก ํ•ฉ๋‹ˆ๋‹ค.
  • ๋˜‘๋˜‘ํ•œ ์—์ด์ „ํŠธ: ์‚ฌ์šฉ์ž์™€ ์ƒํ˜ธ์ž‘์šฉํ•˜๋ฉฐ ์ฐฝ์˜์ ์ด๊ณ  ์ „๋žต์ ์ธ ํŒŒํŠธ๋„ˆ ์—ญํ• ์„ ํ•˜๋Š” ์—์ด์ „ํŠธ.

์ฝ”๋ฑ์Šค๋Š” ์ด ๋‘ ๊ฐ€์ง€ ์œ ํ˜•์˜ ์—์ด์ „ํŠธ๋ฅผ ๋ชจ๋‘ ๊ตฌ์ถ•ํ•˜๋Š” ๋ฐ ๋Šฅ์ˆ™ํ•ฉ๋‹ˆ๋‹ค.

์ธ๊ฐ„์˜ ์ตœ์ข… ๊ฒ€ํ† : ์—์ด์ „ํŠธ ์ž‘์—…์˜ ์‹ ๋ขฐ์„ฑ ํ™•๋ณด

์˜ค์Šคํ‹ด์€ ์—์ด์ „ํŠธ๊ฐ€ ๋งŒ๋“  ์ž‘์—…๋ฌผ์˜ ์ตœ์ข… ๊ฒ€ํ†  ๋‹จ๊ณ„๋ฅผ ์™ธ๋ถ€ ์•ฑ์—์„œ ์ˆ˜ํ–‰ํ•˜๋Š” ๊ฒƒ์„ ์„ ํ˜ธํ•ฉ๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, Slack ๋ฉ”์‹œ์ง€ ์ดˆ์•ˆ์€ Slack ์•ฑ์—์„œ, ์ด๋ฉ”์ผ ์ดˆ์•ˆ์€ Gmail ์•ฑ์—์„œ ์ง์ ‘ ํ™•์ธํ•˜๊ณ  ๋ณด๋ƒ…๋‹ˆ๋‹ค. ์ด๋Š” ๊ทธ์˜ ๋‘๋‡Œ๋ฅผ โ€˜์ƒˆ๋กญ๊ฒŒโ€™ ํ•˜์—ฌ ์‚ฌ๋žŒ์ด ์ตœ์ข…์ ์œผ๋กœ ๋ณด๋‚ผ ๋‚ด์šฉ์ด ๋ฌด์—‡์ธ์ง€ ๋‹ค์‹œ ํ•œ๋ฒˆ ํ™•์ธํ•˜๋Š” ๋ฐ ๋„์›€์„ ์ค๋‹ˆ๋‹ค. ์ „๋žต ๊ณ„ํš ๋ฌธ์„œ์˜ ๊ฒฝ์šฐ์—๋„, Notion์ด๋‚˜ โ€˜ํ”„๋ฃจํ”„(Proof)โ€™ ๋ฌธ์„œ(Every์—์„œ ์‚ฌ์šฉํ•˜๋Š” ์—์ด์ „ํŠธ ์นœํ™”์ ์ธ ๋งˆํฌ๋‹ค์šด ํŒŒ์ผ)๋กœ ํ‘ธ์‹œ๋œ ๋‚ด์šฉ์„ ์ธ๊ฐ„์ด ์ตœ์ข…์ ์œผ๋กœ ๊ฒ€ํ† ํ•ฉ๋‹ˆ๋‹ค.

๋ณต์žกํ•œ ์ด๋ฉ”์ผ ๊ด€๋ฆฌ: ์—์ด์ „ํŠธ์™€ ํ•จ๊ป˜ํ•˜๋Š” ๋ฆฌ๋“œ ๋ถ„๋ฅ˜

๊ณ ๊ฐ์œผ๋กœ๋ถ€ํ„ฐ ์˜ค๋Š” ์ค‘์š”ํ•œ ์ด๋ฉ”์ผ(๋ฆฌ๋“œ)๊ณผ ๋‰ด์Šค๋ ˆํ„ฐ ๊ฐ™์€ ์ •๋ณด์„ฑ ์ด๋ฉ”์ผ์„ ๋ถ„๋ฅ˜ํ•˜๋Š” ๋ฌธ์ œ์— ๋Œ€ํ•ด, ์˜ค์Šคํ‹ด์€ ์—์ด์ „ํŠธ์—๊ฒŒ ์ž์‹ ์„ ์ธํ„ฐ๋ทฐํ•˜๊ฒŒ ํ•˜์—ฌ ๊ทœ์น™์„ ์„ค์ •ํ•˜๋Š” ๋ฐฉ๋ฒ•์„ ์ถ”์ฒœํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์Œ์„ฑ-ํ…์ŠคํŠธ ๋ณ€ํ™˜ ์•ฑ์ธ ๋ชจ๋†€๋กœ๊ทธ(Monologue)๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ์ž์‹ ์˜ ์ด๋ฉ”์ผ ๋ฌธ์ œ๋ฅผ ์„ค๋ช…ํ•˜๊ณ , ์—์ด์ „ํŠธ์—๊ฒŒ ์ด๋ฉ”์ผ์„ ๊ฒ€์ƒ‰ํ•˜๊ณ  ์„œ๋ธŒ ์—์ด์ „ํŠธ๋ฅผ ์ƒ์„ฑํ•˜์—ฌ ๋ถ„๋ฅ˜ ๊ณ„ํš์„ ์„ธ์šฐ๋„๋ก ์ง€์‹œํ•ฉ๋‹ˆ๋‹ค. ์—์ด์ „ํŠธ๊ฐ€ ์ œ์•ˆํ•œ ๊ณ„ํš์„ ๊ฒ€ํ† ํ•˜๊ณ  ํ•„์š”ํ•œ ๊ฒฝ์šฐ ์ˆ˜์ •ํ•˜๋ฉฐ, ์ƒˆ๋กœ์šด ์ž๋™ํ™”๊ฐ€ ์ž˜ ์ž‘๋™ํ•˜๋Š”์ง€ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•ด ์ฃผ๊ธฐ์ ์ธ ๊ฐ์‚ฌ(Audit) ์•Œ๋ฆผ์„ ์„ค์ •ํ•ฉ๋‹ˆ๋‹ค.

์ „๋ฌธํ™”๋œ ์—์ด์ „ํŠธ ์Šค์œ„ํŠธ ๊ตฌ์ถ•

์˜ค์Šคํ‹ด์€ ํด๋ ˆ์–ด๋ณด(Clairebo)์˜ ์ธํ„ฐ๋ทฐ์—์„œ ์˜๊ฐ์„ ๋ฐ›์•„, ๋งˆ์Šคํ„ฐ ์—์ด์ „ํŠธ ๋Œ€์‹  6๊ฐœ์˜ โ€˜์ „๋ฌธํ™”๋œ ์—์ด์ „ํŠธ ์Šค์œ„ํŠธโ€™๋ฅผ ๊ตฌ์ถ•ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ํด๋ ˆ์–ด๋ณด์˜ ์ธํ„ฐ๋ทฐ ์Šคํฌ๋ฆฝํŠธ๋ฅผ ์ฝ”๋ฑ์Šค์—๊ฒŒ ์ œ๊ณตํ•˜๋ฉฐ, ์ž์‹ ์˜ ์—…๋ฌด์™€ Slack ํ™˜๊ฒฝ์— ๋งž์ถฐ 6๊ฐœ์˜ ์—์ด์ „ํŠธ๋ฅผ ์ œ์•ˆํ•˜๋„๋ก ์š”์ฒญํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ์—์ด์ „ํŠธ๋“ค์€ Slack์ด๋‚˜ Notion์—์„œ ํŠน์ • ์ž‘์—…์„ ์ˆ˜ํ–‰ํ•˜๋„๋ก ํ”„๋กœ๋น„์ €๋‹(provisioning)๋˜์—ˆ์œผ๋ฉฐ, ์—์ด์ „ํŠธ๊ฐ€ ์˜ค์ž‘๋™ํ•  ๊ฒฝ์šฐ ์ฝ”๋ฑ์Šค์—๊ฒŒ ๋ฌธ์ œ ์ƒํ™ฉ์„ ์„ค๋ช…ํ•˜๊ณ  ์ˆ˜์ •ํ•˜๋„๋ก ์ง€์‹œํ•˜์—ฌ ํšจ์œจ์ ์œผ๋กœ ๊ด€๋ฆฌํ•ฉ๋‹ˆ๋‹ค.

GTM(Go-to-Market) ๊ณ„ํš ์ˆ˜๋ฆฝ: ์ƒ๊ฐ์˜ ์ง‘๋Œ€์„ฑ

์˜ค์Šคํ‹ด์€ ์ฝ”๋ฑ์Šค๋ฅผ ํ™œ์šฉํ•˜์—ฌ GTM(Go-to-Market) ๊ณ„ํš์„ ์ˆ˜๋ฆฝํ•˜๋Š” ๊ณผ์ •์„ ์‹œ์—ฐํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ด๋ฏธ ๋‚ด๋ถ€ ํšŒ์˜๋ก, Slack ๋Œ€ํ™”, ๊ฐœ์ธ์ ์œผ๋กœ ์„ ํ˜ธํ•˜๋Š” GTM ํ…œํ”Œ๋ฆฟ ๋“ฑ ๋ชจ๋“  ํ•„์š”ํ•œ ์ •๋ณด๊ฐ€ Notion์— ๊ธฐ๋ก๋˜์–ด ์žˆ๋‹ค๋Š” ์ ์„ ํ™œ์šฉํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ฝ”๋ฑ์Šค์—๊ฒŒ โ€œ๊ณ„ํš์„ ๋งŒ๋“ค์–ด๋‹ฌ๋ผโ€๊ณ  ์š”์ฒญํ–ˆ๊ณ , ์ฝ”๋ฑ์Šค๋Š” ๊ธฐ์กด์˜ ๋ชจ๋“  ์ •๋ณด๋ฅผ ์ทจํ•ฉํ•˜์—ฌ 80~90% ์™„์„ฑ๋œ ๊ณ„ํš ์ดˆ์•ˆ์„ ์ƒ์„ฑํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด๋Š” ๋ชจ๋ธ์ด ์ƒˆ๋กœ์šด ์ „๋žต์„ ์ฐฝ์กฐํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ์ธ๊ฐ„์ด ์ด๋ฏธ ๋…ผ์˜ํ•˜๊ณ  ์ƒ๊ฐํ–ˆ๋˜ ๋ชจ๋“  ์ •๋ณด๋ฅผ ์กฐํ•ฉํ•˜๊ณ  ๊ฒ€ํ† ํ•˜์—ฌ ๋ฌธ์„œํ™”ํ•˜๋Š” ๋ฐ ํ™œ์šฉ๋  ์ˆ˜ ์žˆ์Œ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ฐฉ์‹์€ ์˜ค์Šคํ‹ด์ด ํ•˜๋ฃจ ์ข…์ผ ๊ณ„ํš ์ˆ˜๋ฆฝ์— ๋งค๋‹ฌ๋ฆฌ๊ฑฐ๋‚˜ ์•ผ๊ทผํ•  ํ•„์š” ์—†์ด, ํšŒ์˜ ์ค‘๊ฐ„์˜ ์งง์€ ์‹œ๊ฐ„์—๋„ ์ค‘์š”ํ•œ ์ „๋žต ๋ฌธ์„œ๋ฅผ ์™„์„ฑํ•  ์ˆ˜ ์žˆ๋„๋ก ํ–ˆ์Šต๋‹ˆ๋‹ค.

์—์ด์ „ํŠธ ๋ฌธ์„œ์˜ ์‹œ๋Œ€: ์ƒˆ๋กœ์šด ์†Œํ†ต ๋ฐฉ์‹

Every๋Š” ์—์ด์ „ํŠธ๊ฐ€ ์ž‘์„ฑํ•œ ๋ฌธ์„œ๋ฅผ ์„œ๋กœ ๊ณต์œ ํ•˜๊ณ  ๊ฒ€ํ† ํ•˜๋Š” ๊ฒƒ์„ โ€˜์ •์ƒํ™”(normalize)โ€˜ํ•˜๋Š” ๊ฒƒ์„ ์ค‘์š”ํ•˜๊ฒŒ ์ƒ๊ฐํ•ฉ๋‹ˆ๋‹ค.

โ€˜ํ”„๋ฃจํ”„(Proof)โ€™ ๋ฌธ์„œ์˜ ํ™œ์šฉ๊ณผ AI ์ž‘์„ฑ์˜ ํ‘œ์ค€ํ™”

Every๋Š” โ€˜ํ”„๋ฃจํ”„(Proof)โ€˜๋ผ๋Š” ๋งˆํฌ๋‹ค์šด(Markdown) ๊ธฐ๋ฐ˜ ๋ฌธ์„œ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์—์ด์ „ํŠธ๊ฐ€ ์ƒ์„ฑํ•œ ๊ฒฐ๊ณผ๋ฌผ์„ ์‰ฝ๊ฒŒ ๊ณต์œ ํ•˜๊ณ  ๊ฒ€ํ† ํ•ฉ๋‹ˆ๋‹ค. Every์˜ CEO๋Š” ์–ด๋–ค ๊ฒฝ์šฐ์—๋Š” ์ธ๊ฐ„์ด ์ง์ ‘ ์ž‘์„ฑํ•œ ๊ธ€๋ณด๋‹ค ์—์ด์ „ํŠธ๊ฐ€ ์ž‘์„ฑํ•œ ๊ธ€์„ ์„ ํ˜ธํ•œ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์ค‘์š”ํ•œ ๊ฒƒ์€ ์ž‘์„ฑ์ž๊ฐ€ ๊ทธ ๋‚ด์šฉ์— ๋Œ€ํ•ด ์ถฉ๋ถ„ํžˆ ์ƒ๊ฐํ•˜๊ณ  ์ฑ…์ž„์งˆ ์ˆ˜ ์žˆ๋Š”์ง€ ์—ฌ๋ถ€์ž…๋‹ˆ๋‹ค.

AI ์ž‘์„ฑ ๋ฌธ์„œ์— ๋Œ€ํ•œ ์ฑ…์ž„๊ฐ

Every์˜ ๋ฌธํ™”๋Š” AI๊ฐ€ ์ž‘์„ฑํ•œ ๋ฌธ์„œ๋ผ ํ• ์ง€๋ผ๋„, ํŒ€์›๋“ค์ด ๊ทธ ๋‚ด์šฉ์— ๋Œ€ํ•ด ์ „์ ์œผ๋กœ ์ฑ…์ž„์ ธ์•ผ ํ•œ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ํšŒ์˜์—์„œ ๋ฌธ์„œ ๋‚ด์šฉ์— ๋Œ€ํ•ด ์งˆ๋ฌธ์„ ๋ฐ›์•˜์„ ๋•Œ โ€œAI๊ฐ€ ์“ด ๊ฒƒ์ด๋ผ ๋ชจ๋ฅธ๋‹คโ€๊ณ  ๋‹ตํ•˜๋ฉด ์•ˆ ๋ฉ๋‹ˆ๋‹ค. ์ด๋ฅผ ์œ„ํ•ด Every๋Š” ์—์ด์ „ํŠธ๊ฐ€ ๋™์˜๋˜์ง€ ์•Š์€ ๋‚ด์šฉ์„ ๋ฌธ์„œ์— ์ถ”๊ฐ€ํ•˜์ง€ ๋ชปํ•˜๋„๋ก ํ•˜๋Š” ๊ทœ์น™์„ ์„ค์ •ํ•˜๋Š” ๋“ฑ, AI ์ƒ์„ฑ ์ฝ˜ํ…์ธ ์˜ ํ’ˆ์งˆ๊ณผ ์‹ ๋ขฐ์„ฑ์„ ๋ณด์žฅํ•˜๊ธฐ ์œ„ํ•œ ์ง€์†์ ์ธ ๋…ธ๋ ฅ์„ ๊ธฐ์šธ์ž…๋‹ˆ๋‹ค.

โ€˜์ƒ๊ฐโ€™์— ์ง‘์ค‘ํ•˜๋Š” ์—…๋ฌด ๋ฐฉ์‹

์—์ด์ „ํŠธ ๊ธฐ๋ฐ˜ ์ž‘์—… ํ๋ฆ„์˜ ๊ฐ€์žฅ ํฐ ์ด์  ์ค‘ ํ•˜๋‚˜๋Š” ์ธ๊ฐ„์ด โ€˜์ƒ๊ฐโ€™ ์ž์ฒด์— ๋” ์ง‘์ค‘ํ•  ์ˆ˜ ์žˆ๋„๋ก ์‹œ๊ฐ„์„ ๋ฒŒ์–ด์ค€๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋งŽ์€ ์ง€์‹ ๋…ธ๋™์€ ์ด๋ฏธ ๋๋‚œ ์ƒ๊ฐ์„ ๋‹ค๋ฅธ ์‚ฌ๋žŒ์ด ์ฝ๊ณ  ์†Œ๋น„ํ•  ์ˆ˜ ์žˆ๋Š” ํ˜•ํƒœ๋กœ ๋ฐ”๊พธ๋Š” ๋ฐ ์†Œ์š”๋ฉ๋‹ˆ๋‹ค. ๋ชจ๋“  ํšŒ์˜๊ฐ€ ๊ธฐ๋ก๋˜๊ณ  ์Šคํฌ๋ฆฝํŠธํ™”๋˜๋Š” ํ™˜๊ฒฝ์—์„œ, ์ฝ”๋ฑ์Šค๋Š” ์ด ๋ชจ๋“  ์ •๋ณด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ „๋žต ๋ฌธ์„œ๋ฅผ ์ƒ์„ฑํ•˜๊ณ , ์ธ๊ฐ„์€ ์ด๋ฅผ ๊ฒ€ํ† ํ•˜๊ณ  ์ˆ˜์ •ํ•˜๋Š” ๋ฐ ์‹œ๊ฐ„์„ ํ• ์• ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ํŠนํžˆ ํšŒ์˜๊ฐ€ ๋งŽ์•„ ๊ธด ์‹œ๊ฐ„ ๋™์•ˆ ์ง‘์ค‘ํ•˜๊ธฐ ์–ด๋ ค์šด ๋ฆฌ๋”๋“ค์—๊ฒŒ ํฐ ๋„์›€์ด ๋ฉ๋‹ˆ๋‹ค.

๊ฒฐ๋ก 

Every์˜ ํด๋กœ๋“œ ์ฝ”๋“œ์—์„œ ์ฝ”๋ฑ์Šค๋กœ์˜ ์ „ํ™˜ ์‚ฌ๋ก€๋Š” AI ์—์ด์ „ํŠธ๊ฐ€ ์ง€์‹ ๋…ธ๋™์˜ ๋ฏธ๋ž˜๋ฅผ ์–ด๋–ป๊ฒŒ ์žฌํŽธํ•˜๊ณ  ์žˆ๋Š”์ง€ ๋ช…ํ™•ํ•˜๊ฒŒ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ์ดˆ๊ธฐ์—๋Š” ๋‹จ์ˆœํ•œ ๊ฐœ๋ฐœ์ž ๋„๊ตฌ์— ๋ถˆ๊ณผํ–ˆ๋˜ ์ฝ”๋ฑ์Šค๊ฐ€ ์ด์ œ๋Š” ๋ชจ๋“  ์ง€์‹ ์ž‘์—…์˜ ์ค‘์‹ฌ์ด ๋˜๋Š” ๊ฐ•๋ ฅํ•œ ์—์ด์ „ํŠธ ๊ด€๋ฆฌ ์ธํ„ฐํŽ˜์ด์Šค๋กœ ์ง„ํ™”ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ณ€ํ™”๋Š” ๋‹จ์ˆœํ•œ ๋„๊ตฌ ๊ต์ฒด๋ฅผ ๋„˜์–ด, ์šฐ๋ฆฌ๊ฐ€ ์ผํ•˜๋Š” ๋ฐฉ์‹, ์†Œํ†ตํ•˜๋Š” ๋ฐฉ์‹, ๊ทธ๋ฆฌ๊ณ  โ€˜์ƒ๊ฐโ€™์— ์ง‘์ค‘ํ•˜๋Š” ๋ฐฉ์‹ ์ž์ฒด๋ฅผ ๊ทผ๋ณธ์ ์œผ๋กœ ๋ณ€ํ™”์‹œํ‚ค๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์—์ด์ „ํŠธ ์šฐ์„ (Agent-First)์˜ ์‹œ๋Œ€๋Š” ์ด๋ฏธ ์‹œ์ž‘๋˜์—ˆ์œผ๋ฉฐ, Every์˜ ๊ฒฝํ—˜์€ ์ด ์ƒˆ๋กœ์šด ํ๋ฆ„์— ์ ์‘ํ•˜๊ณ  ์ด๋ฅผ ํ™œ์šฉํ•˜๋Š” ๊ธฐ์—…๋“ค์—๊ฒŒ ์ค‘์š”ํ•œ ํ†ต์ฐฐ์„ ์ œ๊ณตํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค.


โ€œWas Adam Smith Really a Right-Winger? (Update) | Freakonomics Radioโ€ โ€” Freakonomics Radio Network ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

์• ๋ค ์Šค๋ฏธ์Šค๋Š” ์ •๋ง ์ž์œ  ์‹œ์žฅ์˜ ์ˆ˜ํ˜ธ์ž์˜€์„๊นŒ? โ€˜๋ณด์ด์ง€ ์•Š๋Š” ์†โ€™ ๋’ค์— ๊ฐ์ถฐ์ง„ ์ง„์‹ค

์• ๋ค ์Šค๋ฏธ์Šค(Adam Smith)๋Š” ์˜ค๋Š˜๋‚  ํ”ํžˆ ์ž์œ  ์‹œ์žฅ ์ž๋ณธ์ฃผ์˜์˜ ์•„๋ฒ„์ง€์ด์ž ์šฐํŒŒ ๊ฒฝ์ œ ์‚ฌ์ƒ์˜ ์ƒ์ง•์œผ๋กœ ์—ฌ๊ฒจ์ง‘๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ณผ์—ฐ ๊ทธ์˜ ์‚ฌ์ƒ์€ ๊ทธ๋ ‡๊ฒŒ ๋‹จ์ˆœํ–ˆ์„๊นŒ์š”? ์Šคํ‹ฐ๋ธ ๋”๋ธŒ๋„ˆ(Steven Dubner)๊ฐ€ ์ง„ํ–‰ํ•˜๋Š” ์ธ๊ธฐ ํŒŸ์บ์ŠคํŠธ โ€˜ํ”„๋ฆฌ์ฝ”๋…ธ๋ฏน์Šค ๋ผ๋””์˜ค(Freakonomics Radio)โ€˜์˜ ํ•œ ์—ํ”ผ์†Œ๋“œ์—์„œ๋Š” ์ด ์งˆ๋ฌธ์— ๋Œ€ํ•œ ๋‹ต์„ ์ฐพ์•„ ์• ๋ค ์Šค๋ฏธ์Šค์˜ ์ง„์ •ํ•œ ๋ชจ์Šต์„ ํŒŒํ—ค์นฉ๋‹ˆ๋‹ค. ๊ทธ์˜ ์ดˆ๊ธฐ ์ €์ž‘๋ถ€ํ„ฐ ํ˜„๋Œ€์— ์ด๋ฅด๊ธฐ๊นŒ์ง€, ์Šค๋ฏธ์Šค์˜ ์‚ฌ์ƒ์ด ์–ด๋–ป๊ฒŒ ์ดํ•ด๋˜๊ณ  ๋•Œ๋กœ๋Š” ์˜คํ•ด๋˜์–ด ์™”๋Š”์ง€ ์‹ฌ์ธต์ ์œผ๋กœ ์กฐ๋ช…ํ•˜๋ฉฐ, ๊ทธ๊ฐ€ ๋‹จ์ˆœํžˆ โ€˜์šฐํŒŒ ๊ฒฝ์ œํ•™์žโ€™๋ผ๋Š” ๊ผฌ๋ฆฌํ‘œ๋กœ ์„ค๋ช…๋  ์ˆ˜ ์—†๋Š” ๋ณต์žกํ•œ ์ธ๋ฌผ์ด์—ˆ์Œ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

์ดˆ๊ธฐ ์• ๋ค ์Šค๋ฏธ์Šค: ๋„๋• ์ฒ ํ•™์ž๋กœ์„œ์˜ ์‹œ์ž‘

1759๋…„, 30๋Œ€ ์ค‘๋ฐ˜์˜ ์• ๋ค ์Šค๋ฏธ์Šค๋Š” ์ฒซ ์ €์„œ์ธ ใ€Ž๋„๋•๊ฐ์ •๋ก (The Theory of Moral Sentiments)ใ€์„ ์ถœ๊ฐ„ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ์ฑ…์€ ๊ทธ์˜ ์ด์ „ ์ˆ˜๋…„๊ฐ„์˜ ๊ธ€๋ž˜์Šค๊ณ  ๋Œ€ํ•™๊ต(University of Glasgow) ๋„๋• ์ฒ ํ•™ ๊ฐ•์˜ ๊ฒฝํ—˜์„ ๋ฐ”ํƒ•์œผ๋กœ ์“ฐ์˜€์Šต๋‹ˆ๋‹ค. ์ •์น˜ํ•™์ž์ด์ž ์Šค๋ฏธ์Šค ์—ฐ๊ตฌ์ž์ธ ๊ธ€๋กœ๋ฆฌ ๋ฃจ(Glory Lou)์— ๋”ฐ๋ฅด๋ฉด, ์ด ์ฑ…์€ ๋Ÿฐ๋˜๊ณผ ๋ฏธ๊ตญ ์ „์—ญ์—์„œ โ€œ๊ธ€์˜ ์•„๋ฆ„๋‹ค์›€โ€์œผ๋กœ ๊ทน์ฐฌ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค.

ํ•˜์ง€๋งŒ ๋‹จ์ˆœํžˆ ๋ฌธ์žฅ์˜ ์•„๋ฆ„๋‹ค์›€๋งŒ์ด ์•„๋‹ˆ์—ˆ์Šต๋‹ˆ๋‹ค. ใ€Ž๋„๋•๊ฐ์ •๋ก ใ€์€ ์Šค๋ฏธ์Šค์˜ ๊นŠ์€ ์ธ๊ฐ„์• ์™€ ๊ณต๊ฐ(sympathy)์„ ๋“œ๋Ÿฌ๋ƒˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ๋ถ€(wealth)๊ฐ€ ๋ฐ˜๋“œ์‹œ ๋„๋•์  ๋ฏธ๋•์„ ์˜๋ฏธํ•˜์ง€ ์•Š์œผ๋ฉฐ, ๋นˆ๊ณค์ด ๋ฏธ๋•์„ ๋ฐฐ์ œํ•˜์ง€๋„ ์•Š๋Š”๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ์Šต๋‹ˆ๋‹ค. ์ฑ…์˜ ํ•œ ๊ตฌ์ ˆ์€ ์ด๋ฅผ ๋ช…ํ™•ํžˆ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. โ€œ๋ถ€์œ ํ•˜๊ณ  ๊ถŒ๋ ฅ ์žˆ๋Š” ์ž๋“ค์„ ํ ๋ชจํ•˜๊ณ  ๊ฑฐ์˜ ์ˆญ๋ฐฐํ•˜๋ฉฐ, ๊ฐ€๋‚œํ•˜๊ณ  ๋น„์ฒœํ•œ ์‚ฌ๋žŒ๋“ค์„ ๊ฒฝ๋ฉธํ•˜๊ฑฐ๋‚˜ ์ ์–ด๋„ ๋ฌด์‹œํ•˜๋Š” ์ด๋Ÿฌํ•œ ์„ฑํ–ฅ์€ ๊ณ„๊ธ‰์˜ ๊ตฌ๋ณ„๊ณผ ์‚ฌํšŒ ์งˆ์„œ๋ฅผ ํ™•๋ฆฝํ•˜๊ณ  ์œ ์ง€ํ•˜๋Š” ๋ฐ ํ•„์š”ํ•˜์ง€๋งŒ, ๋™์‹œ์— ์šฐ๋ฆฌ์˜ ๋„๋• ๊ฐ์ •์„ ํƒ€๋ฝ์‹œํ‚ค๋Š” ๊ฐ€์žฅ ๋ณดํŽธ์ ์ธ ์›์ธ์ด ๋œ๋‹ค.โ€ ์ด ์ฑ…์„ ํ†ตํ•ด ์Šค๋ฏธ์Šค๋Š” ์ž‘๊ฐ€, ์ฒ ํ•™์ž, ๊ทธ๋ฆฌ๊ณ  ๊ณต์  ์ง€์‹์ธ์œผ๋กœ์„œ ๋ช…์„ฑ์„ ์Œ“์•˜์Šต๋‹ˆ๋‹ค.

ใ€Ž๊ตญ๋ถ€๋ก ใ€์˜ ํƒ„์ƒ: ๊ฒฉ๋ณ€์˜ ์‹œ๋Œ€์— ๋˜์ง„ ๊ฒฝ๊ณ 

ใ€Ž๋„๋•๊ฐ์ •๋ก ใ€์˜ ์„ฑ๊ณต์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ์Šค๋ฏธ์Šค๋Š” 17์„ธ์˜ ๊ณต์ž‘์˜ ๊ฐœ์ธ ๊ต์‚ฌ์ง์„ ์ˆ˜๋ฝํ•˜๊ณ  ์œ ๋Ÿฝ ๋Œ€๋ฅ™์„ ์—ฌํ–‰ํ•˜๋ฉฐ ๋ณผํ…Œ๋ฅด(Voltaire), ๊ฒฝ์ œํ•™์ž ํ”„๋ž‘์ˆ˜์•„ ์ผ€๋„ค(Franรงois Quesnay), ๋ฒค์ž๋ฏผ ํ”„๋žญํด๋ฆฐ(Benjamin Franklin) ๋“ฑ ๋‹น๋Œ€ ์ง€์„ฑ์ธ๋“ค๊ณผ ๊ต๋ฅ˜ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ๊ฒฝํ—˜์€ ๊ทธ์—๊ฒŒ ๋‹ค๋ฅธ ๋‚˜๋ผ๋“ค์ด ๊ธ€๋กœ๋ฒŒ ๋ฌด์—ญ์˜ ์„ฑ์žฅ๊ณผ ์‚ฐ์—… ํ˜๋ช…(Industrial Revolution)์ด๋ผ๋Š” ๊ฑฐ๋Œ€ํ•œ ๊ฒฝ์ œ์  ๋ณ€ํ™”์— ์–ด๋–ป๊ฒŒ ๋Œ€์ฒ˜ํ•˜๋Š”์ง€ ๊ด€์ฐฐํ•  ๊ธฐํšŒ๋ฅผ ์ฃผ์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ •๋ถ€๋“ค์ด ์ข…์ข… ๋ณดํ˜ธ์ฃผ์˜์ (protectionist) ๋ณธ๋Šฅ์„ ๊ฐ€์ง€๊ณ  ์žˆ์ง€๋งŒ, ์ž์œ  ๋ฌด์—ญ(free trade)์— ๋” ๊ฐœ๋ฐฉ์ ์ด์–ด์•ผ ํ•œ๋‹ค๊ณ  ์ƒ๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค.

์Šค์ฝ”ํ‹€๋žœ๋“œ๋กœ ๋Œ์•„์˜จ ์Šค๋ฏธ์Šค๋Š” 17๋…„๊ฐ„์˜ ์ง‘ํ•„ ๋์— 1776๋…„, ๊ทธ์˜ ๋‘ ๋ฒˆ์งธ์ด์ž ๋งˆ์ง€๋ง‰ ์ €์„œ์ธ ใ€Ž๊ตญ๋ถ€๋ก (The Wealth of Nations)ใ€์„ ์ถœ๊ฐ„ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ํ•ด๋Š” ๊ทธ์˜ ์ ˆ์นœํ•œ ์นœ๊ตฌ์ด์ž ๋ฉ˜ํ† ์˜€๋˜ ์ฒ ํ•™์ž ๋ฐ์ด๋น„๋“œ ํ„(David Hume)์ด ์‚ฌ๋งํ•œ ํ•ด์ด์ž, ์˜๊ตญ์ด ์•„๋ฉ”๋ฆฌ์นด ์‹๋ฏผ์ง€์— ๋Œ€ํ•œ ํ†ต์ œ๊ถŒ์„ ์ƒ์‹คํ•œ ํ•ด์ด๊ธฐ๋„ ํ•ฉ๋‹ˆ๋‹ค.

์• ๋ค ์Šค๋ฏธ์Šค ์—ฐ๊ตฌ์†Œ(Adam Smith Institute) ์†Œ์žฅ ์ด๋ชฌ ๋ฒ„ํ‹€๋Ÿฌ(Eamonn Butler)๋Š” ใ€Ž๊ตญ๋ถ€๋ก ใ€์„ โ€œ๊ฒฝ์ œ์  ์ค‘์•™์ง‘๊ถŒ์ฃผ์˜(economic centralism)์™€ ๋ฌด์—ญ ์ œํ•œ์— ๋Œ€ํ•œ ๋…ผ์Ÿ์„œ(polemic)โ€œ๋ผ๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ์Šค๋ฏธ์Šค๋Š” ํŠนํžˆ ์™ธ๊ตญ ์ƒํ’ˆ ์ˆ˜์ž…์„ ๋ง‰๊ณ  ์ˆ˜์ถœ๋งŒ์„ ์žฅ๋ คํ•˜๋ ค๋Š” ๋‹น์‹œ ์ •์น˜์ธ๋“ค์˜ ์‚ฌ๊ณ ๋ฐฉ์‹, ์ฆ‰ ๊ตญ๋ถ€๋ฅผ ๊ธˆ๊ณผ ์€์˜ ์ถ•์ ์—์„œ ์ฐพ๋Š” ์ค‘์ƒ์ฃผ์˜(mercantilism)๋ฅผ ๋น„ํŒํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์‹ค์ œ๋กœ ์ด ์ฑ…์„ ๋‹น์‹œ์˜ ์ •์น˜์ธ๋“ค์„ ์œ„ํ•ด ์ผ์œผ๋ฉฐ, ํŠนํžˆ ์˜๊ตญ์œผ๋กœ๋ถ€ํ„ฐ์˜ ๋ฌด์—ญ ํ†ต์ œ์—์„œ ๋ฒ—์–ด๋‚˜๊ณ ์ž ํ–ˆ๋˜ ๋ฏธ๊ตญ ์‹๋ฏผ์ง€ ๊ฐœ์ฒ™์ž๋“ค์„ ์ ๊ทน์ ์œผ๋กœ ์ง€์ง€ํ–ˆ์Šต๋‹ˆ๋‹ค.

๊ธ€๋กœ๋ฆฌ ๋ฃจ๋Š” ใ€Ž๊ตญ๋ถ€๋ก ใ€์˜ ๋งˆ์ง€๋ง‰ ๋‹จ๋ฝ์— ๋‚˜์˜ค๋Š” ์Šค๋ฏธ์Šค์˜ ์‹ ๋ž„ํ•œ ๋น„ํŒ์„ ์ธ์šฉํ•ฉ๋‹ˆ๋‹ค. ์Šค๋ฏธ์Šค๋Š” ์˜๊ตญ ์ œ๊ตญ์ด ๋Œ€์„œ์–‘ ์„œ์ชฝ์— โ€œ์œ„๋Œ€ํ•œ ์ œ๊ตญโ€์„ ์†Œ์œ ํ•˜๊ณ  ์žˆ๋‹ค๋Š” ์ƒ๊ฐ์€ โ€œํ™˜์ƒ ์†์—์„œ๋งŒ ์กด์žฌโ€ํ•˜๋ฉฐ, โ€œ๊ธˆ๊ด‘์ด ์•„๋‹ˆ๋ผ ๊ธˆ๊ด‘์˜ ํ”„๋กœ์ ํŠธ์— ๋ถˆ๊ณผโ€ํ•˜๋‹ค๊ณ  ์ผ๊ฐˆํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์‹๋ฏผ์ง€ ํ”„๋กœ์ ํŠธ๊ฐ€ ์—„์ฒญ๋‚œ ์žฌ์ •์  ๋ถ€๋‹ด๋งŒ ์ดˆ๋ž˜ํ•  ๋ฟ ์ด๋“์ด ์—†๋‹ค๊ณ  ๋ณด์•˜์Šต๋‹ˆ๋‹ค.

๋ฏธ๊ตญ ์ž๋ณธ์ฃผ์˜์˜ ์•„์ด์ฝ˜์ด ๋˜๊ธฐ๊นŒ์ง€: ์Šค๋ฏธ์Šค ์‚ฌ์ƒ์˜ ์ˆ˜์šฉ๊ณผ ๋ณ€๋ชจ

๋ฏธ๊ตญ ๊ฑด๊ตญ ์ดˆ๊ธฐ, ใ€Ž๊ตญ๋ถ€๋ก ใ€์€ โ€œ๊ธฐ์ˆ ์ ์ธ ์ž์›(technical resource)โ€œ์œผ๋กœ์„œ ์ค‘์š”ํ•˜๊ฒŒ ์—ฌ๊ฒจ์กŒ์ง€๋งŒ, ์•„์ง โ€œํ›„๊ด‘(halo)โ€œ์„ ์–ป์ง€๋Š” ๋ชปํ–ˆ์Šต๋‹ˆ๋‹ค. ์ œ์ž„์Šค ๋งค๋””์Šจ(James Madison)์ด๋‚˜ ์•Œ๋ ‰์‚ฐ๋” ํ•ด๋ฐ€ํ„ด(Alexander Hamilton) ๊ฐ™์€ ๊ฑด๊ตญ์˜ ์•„๋ฒ„์ง€๋“ค์€ ์ด ์ฑ…์„ ์ƒ์—…, ๋†์—…๊ณผ ์ œ์กฐ์—…์˜ ๊ด€๊ณ„, ์ž์œ  ๋ฌด์—ญ๊ณผ ๊ตญ๋ฐฉ์˜ ์šฐ์„ ์ˆœ์œ„ ๋“ฑ์„ ์ดํ•ดํ•˜๋Š” ๊ฐ€์žฅ ์ •๊ตํ•˜๊ณ  ์ตœ์‹  ๋ถ„์„์œผ๋กœ ์ฝ์—ˆ์Šต๋‹ˆ๋‹ค. ํ•ด๋ฐ€ํ„ด์€ ์‹ค์ œ๋กœ ๊ตญ๋ฆฝ ์€ํ–‰์— ๋Œ€ํ•œ ์ž์‹ ์˜ ๋ณด๊ณ ์„œ์—์„œ ์Šค๋ฏธ์Šค์˜ ๊ธ€์„ ํ‘œ์ ˆํ•˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด์ฒ˜๋Ÿผ ์Šค๋ฏธ์Šค์˜ ์‚ฌ์ƒ์€ ๋ฏธ๊ตญ ๊ฑด๊ตญ์˜ ์ดˆ์„์— ์Šค๋ฉฐ๋“ค๊ธฐ ์‹œ์ž‘ํ–ˆ์Šต๋‹ˆ๋‹ค.

19์„ธ๊ธฐ ์ค‘๋ฐ˜์— ์ด๋ฅด๋Ÿฌ ์ •์น˜๊ฒฝ์ œํ•™(political economy)์ด ํ•™๋ฌธ ๋ถ„์•ผ๋กœ ํ™•๊ณ ํžˆ ์ž๋ฆฌ ์žก์œผ๋ฉด์„œ, ์Šค๋ฏธ์Šค๋Š” ๊ทธ ์ฐฝ์‹œ์ž๋กœ ์ถ”์•™๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ์˜ ์‚ฌ์ƒ์€ ์–‘๋ฉด์ ์œผ๋กœ ํ•ด์„๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ์—ฐ๋ฐฉ ์ •๋ถ€์˜ ์ฃผ์š” ์ˆ˜์ž…์›์ด์—ˆ๋˜ ์ˆ˜์ž… ๊ด€์„ธ(import taxes)๋ฅผ ๋‘˜๋Ÿฌ์‹ผ ๊ฒฉ๋ ฌํ•œ ๋…ผ์Ÿ ์†์—์„œ, ์Šค๋ฏธ์Šค๋Š” ์ž์œ  ๋ฌด์—ญ๋ก ์ž์™€ ๋ณดํ˜ธ๋ฌด์—ญ๋ก ์ž ์–‘์ธก ๋ชจ๋‘์—๊ฒŒ ์ธ์šฉ๋˜๋Š” โ€˜์๊ธฐ(wedge)โ€˜๊ฐ€ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. โ€œ์ž์œ  ๋ฌด์—ญ์˜ ์‚ฌ๋„(apostle)โ€œ์กฐ์ฐจ๋„ ๊ตญ๋‚ด ์‹œ์žฅ์˜ ์ค‘์š”์„ฑ์„ ์–ธ๊ธ‰ํ–ˆ๋‹ค๊ณ  ์ฃผ์žฅํ•˜๋ฉฐ ์„œ๋กœ ์ž์‹ ์˜ ์ž…์žฅ์„ ์ •๋‹นํ™”ํ•˜๋Š” ๋ฐ ์Šค๋ฏธ์Šค์˜ ๊ถŒ์œ„(authority)๋ฅผ ๋นŒ๋ ค ์ผ์Šต๋‹ˆ๋‹ค.

20์„ธ๊ธฐ ์ดˆ, ๋…ธ๋™ ์šด๋™์ด ์„ฑ์žฅํ•˜๋ฉด์„œ ์ง„๋ณด ๊ฒฝ์ œํ•™์ž ๋ฆฌ์ฒ˜๋“œ ์—˜๋ฆฌ(Richard T. Ely)๋Š” ์Šค๋ฏธ์Šค๊ฐ€ ๋…ธ๋™ ์กฐํ•ฉ ํŽธ์— ์„ฐ์„ ๊ฒƒ์ด๋ผ๊ณ  ์ฃผ์žฅํ•˜๊ธฐ๋„ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์˜ค๋Š˜๋‚  ์Šค๋ฏธ์Šค์˜ ํ‰ํŒ์ด ๋ณด์ˆ˜์ (conservative) ๋˜๋Š” ์ž์œ ์ง€์ƒ์ฃผ์˜์ (libertarian)์œผ๋กœ ๊ธฐ์šธ์–ด์ ธ ์žˆ์Œ์„ ๊ณ ๋ คํ•˜๋ฉด ๋†€๋ผ์šด ์‚ฌ์‹ค์ž…๋‹ˆ๋‹ค. ๊ทธ๋ ‡๋‹ค๋ฉด ์Šค๋ฏธ์Šค์˜ ์ด๋Ÿฌํ•œ ๋ณด์ˆ˜์  ํ‰ํŒ์€ ์–ด๋””์—์„œ ๋น„๋กฏ๋œ ๊ฒƒ์ผ๊นŒ์š”?

์‹œ์นด๊ณ  ํ•™ํŒŒ์˜ โ€˜์Šค๋ฏธ์Šค ์žฌํ•ด์„โ€™: โ€˜๋ณด์ด์ง€ ์•Š๋Š” ์†โ€™์˜ ์‹ ํ™”

๊ธ€๋กœ๋ฆฌ ๋ฃจ์˜ ์ €์„œ ใ€Ž์• ๋ค ์Šค๋ฏธ์Šค์˜ ์•„๋ฉ”๋ฆฌ์นด: ์Šค์ฝ”ํ‹€๋žœ๋“œ ์ฒ ํ•™์ž๊ฐ€ ์–ด๋–ป๊ฒŒ ๋ฏธ๊ตญ ์ž๋ณธ์ฃผ์˜์˜ ์•„์ด์ฝ˜์ด ๋˜์—ˆ๋Š”๊ฐ€(Adam Smithโ€™s America: How a Scottish Philosopher Became an icon of American Capitalism)ใ€์— ๋”ฐ๋ฅด๋ฉด, ์Šค๋ฏธ์Šค์˜ ํ˜„๋Œ€์  ํ‰ํŒ์€ ์ฃผ๋กœ 20์„ธ๊ธฐ ์ค‘๋ฐ˜ ์‹œ์นด๊ณ  ๋Œ€ํ•™๊ต(University of Chicago)์—์„œ ํ˜•์„ฑ๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๋ฃจ๋Š” ์‹œ์นด๊ณ  ๋Œ€ํ•™๊ต ๊ฒฝ์ œํ•™๊ณผ๊ฐ€ โ€œ์ดˆ๊ธฐ ์Šค๋ฏธ์Šค ํ•ด์„์˜ ๋ณต์žก์„ฑ, ๊ธด์žฅ, ๊ธฐํƒ€ ๋ฌธ์ œ์  ์ธก๋ฉด์„ ๋งค๋„๋Ÿฝ๊ฒŒ ๋งŒ๋“ค๊ฑฐ๋‚˜ ์™„์ „ํžˆ ๊ฐ€๋ ค๋ฒ„๋ ธ๋‹คโ€๊ณ  ์ง€์ ํ•ฉ๋‹ˆ๋‹ค.

์ดˆ๊ธฐ ์‹œ์นด๊ณ  ํ•™ํŒŒ์˜ ์ œ์ด์ฝฅ ๋ฐ”์ด๋„ˆ(Jacob Viner)์™€ ํ”„๋žญํฌ ๋‚˜์ดํŠธ(Frank Knight)๋Š” ์Šค๋ฏธ์Šค๋ฅผ ๊ฐ€๊ฒฉ ์ด๋ก (price theory)์˜ ์ดˆ๊ธฐ ์ด๋ก ๊ฐ€๋กœ ๊ฐ€๋ฅด์น˜๋ฉฐ ๊ฒฝ์ œํ•™์— ๊ณผํ•™์  ๊ฐ€์น˜์™€ ๊ฐ๊ด€์„ฑ์„ ๋ถ€์—ฌํ•˜๋Š” ๋ฐ ๊ธฐ์—ฌํ–ˆ์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ดํ›„ ํ”„๋ฆฌ๋“œ๋ฆฌํžˆ ํ•˜์ด์—ํฌ(Friedrich Hayek), ์กฐ์ง€ ์Šคํ‹ฐ๊ธ€๋Ÿฌ(George Stigler), ๋ฐ€ํ„ด ํ”„๋ฆฌ๋“œ๋จผ(Milton Friedman) ๊ฐ™์€ ์ƒˆ๋กœ์šด ์„ธ๋Œ€์˜ ์‚ฌ์ƒ๊ฐ€๋“ค์€ ์Šค๋ฏธ์Šค์˜ ๊ฐœ๋…์ธ ๊ฐœ์ธ์ฃผ์˜(individualism), ์ž๊ธฐ ์ด์ต(self-interest), ๋ณด์ด์ง€ ์•Š๋Š” ์†(invisible hand)์„ ์žฌํ•ด์„ํ•˜์—ฌ ๊ฐœ์ธ์ฃผ์˜์  ์‹œ์žฅ ์ค‘์‹ฌ ์‚ฌํšŒ๋ฅผ ์ •๋‹นํ™”ํ•˜๋Š” ๋…์ฐฝ์ ์ธ ์‚ฌ๊ณ ๋ฐฉ์‹์œผ๋กœ ๋ณ€๋ชจ์‹œ์ผฐ์Šต๋‹ˆ๋‹ค.

ํŠนํžˆ โ€˜์ž๊ธฐ ์ด์ตโ€™์˜ ๊ฐœ๋…์ด ํฌ๊ฒŒ ๋ณ€ํ™”ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ดˆ๊ธฐ ์‹œ์นด๊ณ  ํ•™ํŒŒ์—์„œ ์ž๊ธฐ ์ด์ต์€ ํ•ฉ๋ฆฌ์ ์ธ ํšจ์šฉ ๊ทน๋Œ€ํ™”(rational utility maximizing)๋ฅผ ์ถ”๊ตฌํ•˜๋Š” ๊ฐœ์ธ์ฃผ์˜์ผ ๋ฟ ์•„๋‹ˆ๋ผ, ๋งŽ์€ ์ธ๊ฐ„ ๋™๊ธฐ ์ค‘ ํ•˜๋‚˜์˜€์œผ๋ฉฐ ๊ทน๋‹จ์ ์ธ ํ˜•ํƒœ๋Š” ์œ„ํ—˜ํ•˜๋‹ค๊ณ  ๋ณด์•˜์Šต๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์Šคํ‹ฐ๊ธ€๋Ÿฌ์™€ ๊ฐ™์€ ํ•™์ž๋“ค์€ ์ž๊ธฐ ์ด์ต์„ โ€œ๊ฒฝ์ œํ•™์˜ ํ”„๋กœ๋ฉ”ํ…Œ์šฐ์Šคโ€๋กœ ์—ฌ๊ธฐ๋ฉฐ, ๊ฐ€์žฅ ๊ฐ•๋ ฅํ•œ ์„ค๋ช…๋ ฅ์„ ๊ฐ€์ง„ ์ธ๊ฐ„ ๋™๊ธฐ๋กœ ๊ฐ„์ฃผํ–ˆ์Šต๋‹ˆ๋‹ค. ์Šคํ‹ฐ๊ธ€๋Ÿฌ๋Š” ์Šค๋ฏธ์Šค์˜ ๊ธ€์—์„œ ์ž์‹ ์˜ ๊ฒฝ์ œํ•™์  ๊ด€์ ๊ณผ ์ผ์น˜ํ•˜๋Š” โ€œ์™„๋ฒฝํ•œ ๋งˆ์Šค์ฝ”ํŠธโ€๋ฅผ ๋ฐœ๊ฒฌํ–ˆ์Šต๋‹ˆ๋‹ค.

์˜คํ•ด๋ฐ›๋Š” โ€˜๋ณด์ด์ง€ ์•Š๋Š” ์†โ€™: ์Šค๋ฏธ์Šค์˜ ์ง„์ •ํ•œ ๋ฉ”์‹œ์ง€

์‹œ๋Ÿฌํ์Šค ๋Œ€ํ•™๊ต(Syracuse University)์˜ ์ •์น˜ํ•™์ž์ด์ž ์Šค๋ฏธ์Šค ์—ฐ๊ตฌ์ž์ธ ๋ฐ๋‹ˆ์Šค ๋ผ์Šค๋ฌด์„ผ(Dennis Rasmusen)์€ ์‹œ์นด๊ณ  ํ•™ํŒŒ๊ฐ€ โ€œ์Šค๋ฏธ์Šค ์‚ฌ์ƒ์˜ ๋ช‡ ๊ฐ€์ง€ ์ธก๋ฉด์„ ํƒํ•ด ๊ทธ๊ฒƒ์„ ์Šค๋ฏธ์Šค ์‚ฌ์ƒ ์ „์ฒด๋กœ ๋งŒ๋“ค์—ˆ๋‹คโ€๊ณ  ๋น„ํŒํ•ฉ๋‹ˆ๋‹ค. ํŠนํžˆ ์Šค๋ฏธ์Šค์˜ ์ €์ž‘์—์„œ ๋‘์„ธ ๋ฒˆ๋งŒ ๋“ฑ์žฅํ•˜๋Š” โ€œ๋ณด์ด์ง€ ์•Š๋Š” ์†โ€์ด๋ผ๋Š” ๋ฌธ๊ตฌ๋ฅผ ์Šค๋ฏธ์Šค ์‚ฌ์ƒ์˜ ํ•ต์‹ฌ์œผ๋กœ ๋ถ€๊ฐ์‹œํ‚จ ๊ฒƒ์€ โ€œ๋ถˆํ–‰ํ•œ ์ผโ€์ด๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค.

๊ธ€๋ž˜์Šค๊ณ  ๋Œ€ํ•™๊ต์˜ ํฌ๋ ˆ์ด๊ทธ ์Šค๋ฏธ์Šค(Craig Smith) ์—ญ์‹œ ์ด โ€œ๋ณด์ด์ง€ ์•Š๋Š” ์†โ€์ด ์˜ค๋Š˜๋‚  ์‹œ์žฅ์ด ์™„๋ฒฝํ•˜๊ฒŒ ์ž‘๋™ํ•  ๊ฒƒ์ด๋ผ๋Š” ํ˜„๋Œ€์  ์•„์ด๋””์–ด๋ฅผ ์ƒ์ง•ํ•˜๋Š” ์šฉ์–ด๋กœ ๋ณ€์งˆ๋˜์—ˆ๋‹ค๊ณ  ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ์Šค๋ฏธ์Šค๊ฐ€ ์ด ๊ตฌ์ ˆ์„ ์‚ฌ์šฉํ•œ ์˜๋„๋Š” ํŠน์ • ํ–‰์œ„์ž๋“ค์˜ ์˜๋„์™€๋Š” ๋ฌด๊ด€ํ•˜๊ฒŒ ์‚ฌํšŒ์  ์ƒํ˜ธ์ž‘์šฉ์„ ํ†ตํ•ด ์–ด๋–ค ๊ฒฐ๊ณผ๊ฐ€ ๋„์ถœ๋˜๋Š” โ€˜์˜๋„ํ•˜์ง€ ์•Š์€ ๊ฒฐ๊ณผ(unintended consequences)โ€˜๋ฅผ ์„ค๋ช…ํ•˜๋Š” ์€์œ (metaphor)์— ๊ฐ€๊นŒ์› ์Šต๋‹ˆ๋‹ค. ์Šค๋ฏธ์Šค์˜ ์ €์ž‘์—๋Š” ๋ถ€์ •์ ์ธ ๊ฒฐ๊ณผ๋ฅผ ์ดˆ๋ž˜ํ•˜๋Š” ์˜๋„ํ•˜์ง€ ์•Š์€ ๊ฒฐ๊ณผ์— ๋Œ€ํ•œ ๋…ผ์ฆ๋„ ์กด์žฌํ•˜์ง€๋งŒ, โ€˜๋ณด์ด์ง€ ์•Š๋Š” ์†โ€™์€ ๊ธ์ •์ ์ธ ๊ฒฐ๊ณผ์™€๋งŒ ์—ฐ๊ด€๋˜์–ด ์˜คํ•ด๋ฅผ ๋‚ณ์•˜๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋ผ์Šค๋ฌด์„ผ์€ ์Šค๋ฏธ์Šค ์‚ฌ์ƒ์˜ ๊ฐ€์žฅ ๊ฐ€์น˜ ์žˆ๋Š” ์ธก๋ฉด ์ค‘ ํ•˜๋‚˜๋Š” ์ƒ์—… ์‚ฌํšŒ(commercial society)์˜ ์ž ์žฌ์  ๋‹จ์ ๊ณผ ์œ„ํ—˜์„ ์ •ํ™•ํžˆ ์ธ์‹ํ–ˆ๋‹ค๋Š” ์ ์ด๋ผ๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ์ƒ์—…์ด ์—„์ฒญ๋‚œ ๋ถˆํ‰๋“ฑ์„ ๋‚ณ๊ณ , ๋ถ€์œ ํ•œ ์ƒ์ธ๊ณผ ์ œ์กฐ์—…์ž๋“ค์ด ๊ณต์ต(public interest)์— ๋ฐ˜ํ•˜์—ฌ ๋‹ดํ•ฉํ•˜๋ฉฐ, ๋ถ€์— ๋Œ€ํ•œ ์š•๋ง์ด ์‚ฌ๋žŒ๋“ค์„ ๋์—†๋Š” ๋…ธ๊ณ ์™€ ๋ถˆ์•ˆ์— ๋น ๋œจ๋ ค ๋ง์—†๋Š” ๋ฌผ์งˆ์  ๋งŒ์กฑ๋งŒ์„ ์ถ”๊ตฌํ•˜๊ฒŒ ๋งŒ๋“ค ์ˆ˜ ์žˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์Šค๋ฏธ์Šค๋ฅผ ๋‹จ์ˆœํžˆ ์ƒ์—… ์‚ฌํšŒ์˜ ์˜นํ˜ธ์ž(apologist)๋กœ ์ฝ๋Š” ๊ฒƒ์€ ๊ทธ์˜ ๋ณต์žกํ•œ ์‚ฌ์ƒ์„ ๊ฐ„๊ณผํ•˜๋Š” ๊ฒƒ์ด๋ผ๊ณ  ๋ผ์Šค๋ฌด์„ผ์€ ๋งํ•ฉ๋‹ˆ๋‹ค. ์Šค๋ฏธ์Šค๋Š” ์ƒ์—… ์‚ฌํšŒ์˜ ๊ฒฐํ•จ์ด ์‹ค์žฌํ•˜๊ณ  ์ค‘์š”ํ•จ์—๋„ ๋ถˆ๊ตฌํ•˜๊ณ , ๋‹ค๋ฅธ ํ˜•ํƒœ์˜ ์‚ฌํšŒ๋ณด๋‹ค ๊ทธ ์ˆ˜๊ฐ€ ์ ๊ณ  ๋œ ์‹ฌ๊ฐํ•˜๋ฉฐ, ์ƒ์—… ์‚ฌํšŒ๊ฐ€ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ์•ˆ๋ณด, ์ž์œ , ๋ฒˆ์˜์ด ๋‹ค๋ฅธ ๋Œ€์•ˆ๋“ค๋ณด๋‹ค ์ง„์ •ํ•œ ์ง„๋ณด๋ฅผ ์ด๋ฃฌ๋‹ค๊ณ  ํ™•์‹ ํ–ˆ๊ธฐ ๋•Œ๋ฌธ์— ๊ถ๊ทน์ ์œผ๋กœ ์ƒ์—… ์‚ฌํšŒ๋ฅผ ์˜นํ˜ธํ–ˆ์Šต๋‹ˆ๋‹ค.

๋ฐ€ํ„ด ํ”„๋ฆฌ๋“œ๋จผ์˜ โ€˜์›…๋ณ€์  ์ฒœ์žฌ์„ฑโ€™๊ณผ ์‹œ์žฅ์˜ ๋„๋•์  ์žฌ๊ตฌ์„ฑ

์‹œ์นด๊ณ  ํ•™ํŒŒ, ํŠนํžˆ ๋ฐ€ํ„ด ํ”„๋ฆฌ๋“œ๋จผ(Milton Friedman)์€ ์• ๋ค ์Šค๋ฏธ์Šค๋ฅผ โ€œ๊ฒฝ์ œ ์‚ฌ์ƒ์˜ ์Šˆํผํžˆ์–ด๋กœโ€๋กœ ๊ฒฉ์ƒ์‹œ์ผฐ์Šต๋‹ˆ๋‹ค. ๊ธ€๋กœ๋ฆฌ ๋ฃจ๋Š” ํ”„๋ฆฌ๋“œ๋จผ์„ โ€œ์›…๋ณ€์  ์ฒœ์žฌ(rhetorical genius)โ€œ์ด์ž ๋Œ€์ค‘์—๊ฒŒ ๋งํ•˜๋Š” ๋ฐ ๋งค์šฐ ๋Šฅ์ˆ™ํ•œ ์นด๋ฆฌ์Šค๋งˆ ๋„˜์น˜๋Š” ์ธ๋ฌผ์ด๋ผ๊ณ  ๋ฌ˜์‚ฌํ•ฉ๋‹ˆ๋‹ค. ํ”„๋ฆฌ๋“œ๋จผ์€ ์ž์‹ ์˜ ๊ณต์˜ TV ํ”„๋กœ๊ทธ๋žจ โ€˜์ž์œ ๋ฅผ ์„ ํƒํ•˜๋ผ(Free to Choose)โ€˜์—์„œ ์Šค๋ฏธ์Šค์˜ โ€˜๋ณด์ด์ง€ ์•Š๋Š” ์†โ€™์„ โ€œ๊ฐ€๊ฒฉ ๋ฉ”์ปค๋‹ˆ์ฆ˜(price mechanism)โ€œ๊ณผ ์—ฐ๊ฒฐํ•˜์—ฌ ์„ค๋ช…ํ–ˆ์Šต๋‹ˆ๋‹ค. ์‹œ์žฅ์—์„œ ํ˜•์„ฑ๋˜๋Š” ๊ฐ€๊ฒฉ์ด ์ˆ˜๋ฐฑ๋งŒ ๋ช…์˜ ๋…๋ฆฝ์ ์ธ ๊ฐœ์ธ๋“ค์˜ ํ™œ๋™์„ ์กฐ์œจํ•˜๋ฉฐ, ๋”ฐ๋ผ์„œ ์ค‘์•™ ๊ณ„ํš(centralized planning)์ด ํ•„์š” ์—†๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ํ•ด์„์€ ์‹œ์žฅ์ด ๊ฐ€๊ฒฉ ๋ฉ”์ปค๋‹ˆ์ฆ˜์„ ํ†ตํ•ด ์Šค์Šค๋กœ ํšจ์œจ์ ์œผ๋กœ ์กฐ์ง๋  ์ˆ˜ ์žˆ๋‹ค๋ฉด, ์ •๋ถ€๊ฐ€ ๋ถˆํ•„์š”ํ•œ ๊ทœ์ œ๋‚˜ ๊ฐ€๊ฒฉ ํ†ต์ œ๋กœ ๋ฐฉํ•ดํ•ด์„œ๋Š” ์•ˆ ๋œ๋‹ค๋Š” ๋…ผ๋ฆฌ๋กœ ์ด์–ด์กŒ์Šต๋‹ˆ๋‹ค. ๊ธ€๋กœ๋ฆฌ ๋ฃจ๋Š” ์ด๋ฅผ โ€œ๋ณด์ด์ง€ ์•Š๋Š” ์† ํ”๋“ค๊ธฐ(invisible handwaving)โ€œ๋ผ๊ณ  ๋ถ€๋ฅด๋ฉฐ, ์‹œ์žฅ์„ ๊ทธ ์ž์ฒด๋กœ โ€œ๋„๋•์ ์ธ ๊ฒƒ(moral thing)โ€œ์œผ๋กœ ์ทจ๊ธ‰ํ•˜๋Š” ๋ฐฉ์‹์ด๋ผ๊ณ  ๋น„ํŒํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ ‘๊ทผ ๋ฐฉ์‹์€ ๊ฐ๊ด€์ ์ด๊ณ  ๊ณผํ•™์ ์ด๋ฉฐ ์ •์น˜์ ์œผ๋กœ ์ค‘๋ฆฝ์ ์œผ๋กœ ๋ณด์ด์ง€๋งŒ, ์‹ค์ œ๋กœ๋Š” ํšจ์œจ์„ฑ์„ ํ˜•ํ‰์„ฑ(equity), ๋ณดํŽธ์ฃผ์˜(universalism), ๋ฏผ์ฃผ์ฃผ์˜(democracy)๋ณด๋‹ค ์ค‘์š”ํ•œ ๊ฐ€์น˜๋กœ ์—ฌ๊ธฐ๋Š” ์•”๋ฌต์ ์ธ ๋„๋•์  ์ฃผ์žฅ์„ ๋‹ด๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

์‹œ์นด๊ณ  ํ•™ํŒŒ์˜ ์Šค๋ฏธ์Šค ํ•ด์„์˜ ๊ฐ€์žฅ ํฐ ๊ฒฐ๊ณผ ์ค‘ ํ•˜๋‚˜๋Š” ํ˜„๋Œ€ ๋ฏธ๊ตญ ์ž๋ณธ์ฃผ์˜์™€ ์‚ฌํšŒ์˜ ๋ฌธ์ œ๋“ค์ด ์‹œ์žฅ ์ž์ฒด๋ณด๋‹ค๋Š” ์ •๋ถ€์—์„œ ๋น„๋กฏ๋œ ๊ฒƒ์œผ๋กœ ์žฌ๊ตฌ์„ฑ๋˜์—ˆ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค. ๋ฃจ๋Š” ์˜คํ”ผ์˜ค์ด๋“œ(opioid) ์œ„๊ธฐ๋ฅผ ์˜ˆ๋กœ ๋“ค๋ฉฐ, ๊ทœ์ œ ๊ธฐ๊ด€์˜ ์‹คํŒจ์™€ ์•ฝ๋ฌผ ํŒ๋งค๋ฅผ ๋ถ€์ถ”๊ธฐ๋Š” ์‹œ์žฅ ์ธ์„ผํ‹ฐ๋ธŒ๋ฅผ ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ํ• ๋‹น ์ธก๋ฉด์—์„œ๋Š” ํšจ์œจ์ ์ด์—ˆ์„์ง€ ๋ชจ๋ฅด์ง€๋งŒ, ์ธ๊ฐ„ ๋ณต์ง€(human welfare) ๊ด€์ ์—์„œ๋Š” ์ฐธํ˜นํ•œ ๊ฒฐ๊ณผ์˜€๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋งˆ๊ฑฐ๋ฆฟ ๋Œ€์ฒ˜์™€ โ€˜์• ๋ค ์Šค๋ฏธ์Šค ์—ฐ๊ตฌ์†Œโ€™: ์Šค๋ฏธ์Šค์˜ ๊ท€ํ™˜

๋ฐ€ํ„ด ํ”„๋ฆฌ๋“œ๋จผ์„ ๋น„๋กฏํ•œ ์‹œ์นด๊ณ  ํ•™ํŒŒ๊ฐ€ ์ฃผ์ฐฝํ•œ ์• ๋ค ์Šค๋ฏธ์Šค ๋ฒ„์ „์€ ํ•™๊ณ„๋ฅผ ๋„˜์–ด ์ •์น˜๊ถŒ์—๋„ ํฐ ์˜ํ–ฅ์„ ๋ฏธ์ณค์Šต๋‹ˆ๋‹ค. 1970๋…„๋Œ€ ํ›„๋ฐ˜, ์˜๊ตญ ๊ฒฝ์ œ๊ฐ€ ์นจ์ฒด๊ธฐ์— ๋น ์ง€์ž ์ด๋ชฌ ๋ฒ„ํ‹€๋Ÿฌ๋Š” ์˜๊ตญ ์ •๋ถ€์˜ ๊ทœ์ œ์™€ ์‚ฐ์—… ๊ตญ์œ ํ™”(nationalization)์— ์‹ค๋งํ•˜์—ฌ ๋ฏธ๊ตญ์œผ๋กœ ๊ฑด๋„ˆ๊ฐ”์Šต๋‹ˆ๋‹ค. ๋ฏธ๊ตญ์—์„œ ๊ทธ๋Š” ์ •๋ถ€๊ฐ€ ์‚ฐ์—…์„ ๋œ ๊ทœ์ œํ•˜๊ณ  ๊ตญ์œ ํ™”ํ•˜์ง€ ์•Š๋Š” ๋ฐฉ์‹์— ๊นŠ์€ ์ธ์ƒ์„ ๋ฐ›์•˜์Šต๋‹ˆ๋‹ค. ์Šค๋ฏธ์Šค์˜ ์ž์œ  ์‹œ์žฅ ์‚ฌ์ƒ์ด ๊ทธ๋ฅผ ๋งค๋ฃŒ์‹œ์ผฐ๊ณ , ์˜๊ตญ๋ณด๋‹ค ๋ฏธ๊ตญ์ด ์Šค๋ฏธ์Šค์˜ ๊ฐ€๋ฅด์นจ์— ๋” ๋ถ€ํ•ฉํ•œ๋‹ค๊ณ  ๋А๊ผˆ์Šต๋‹ˆ๋‹ค.

1977๋…„, ๋ฒ„ํ‹€๋Ÿฌ๋Š” ๋œป์„ ๊ฐ™์ดํ•˜๋Š” ์นœ๊ตฌ๋“ค๊ณผ ํ•จ๊ป˜ ๋Ÿฐ๋˜์— ์• ๋ค ์Šค๋ฏธ์Šค ์—ฐ๊ตฌ์†Œ(Adam Smith Institute)๋ฅผ ์„ค๋ฆฝํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  1979๋…„, ๋งˆ๊ฑฐ๋ฆฟ ๋Œ€์ฒ˜(Margaret Thatcher) ์ด๋ฆฌ๊ฐ€ ์ง‘๊ถŒํ•˜๋ฉด์„œ ์—ฐ๊ตฌ์†Œ์—๋Š” โ€œ๋นˆ ๊ณจ๋Œ€(open goal)โ€œ๊ฐ€ ์—ด๋ ธ์Šต๋‹ˆ๋‹ค. ๋Œ€์ฒ˜๋Š” โ€œ์ž์œ  ์‹œ์žฅ, ๊ฒฝ์ œ์  ์ž์œ , ์ž‘์€ ์ •๋ถ€โ€๋ฅผ ์ƒ์ง•ํ•˜๋Š” ์ธ๋ฌผ๋กœ, ์Šค๋ฏธ์Šค์˜ ๋ณด์ˆ˜์  ํ•ด์„์„ ์ •์น˜์— ๊ตฌํ˜„ํ•˜๋ ค ํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋…€๋Š” ์„ธ๊ธˆ์„ ์ค„์ด๊ณ  ์ •๋ถ€ ์ง€์ถœ์„ ์‚ญ๊ฐํ–ˆ์œผ๋ฉฐ, ๋…ธ๋™ ์กฐํ•ฉ์˜ ๊ถŒํ•œ์„ ์•ฝํ™”์‹œํ‚ค๊ณ  ์ˆ˜๋งŽ์€ ๊ตญ์˜ ์‚ฐ์—…์„ ๋ฏผ์˜ํ™”(privatization)ํ–ˆ์Šต๋‹ˆ๋‹ค.

์• ๋ค ์Šค๋ฏธ์Šค ์—ฐ๊ตฌ์†Œ๋Š” ๋Œ€์ฒ˜ ์ •๋ถ€์— ๊ตฌ์ฒด์ ์ธ ์ •์ฑ… ์•„์ด๋””์–ด๋ฅผ ์ œ๊ณตํ–ˆ์Šต๋‹ˆ๋‹ค. ์ •๋ถ€ ์œ„์›ํšŒ์™€ ์ž๋ฌธ ๊ธฐ๊ตฌ์ธ โ€˜์พ…๊ณ (quangos, quasi autonomous non-government organizations)โ€˜์˜ ๋น„ํšจ์œจ์„ฑ์„ ์ง€์ ํ•˜๋ฉฐ ๋Œ€ํญ ์ถ•์†Œ๋ฅผ ์ œ์•ˆํ–ˆ๊ณ , ์ง€๋ฐฉ ์ •๋ถ€ ์„œ๋น„์Šค(์˜ˆ: ๋„๋กœ ๋ณด์ˆ˜, ์“ฐ๋ ˆ๊ธฐ ์ˆ˜๊ฑฐ)์˜ ๋ฏผ๊ฐ„ ์œ„ํƒ(contracting out)์„ ํ†ตํ•ด ๋น„์šฉ ์ ˆ๊ฐ๊ณผ ์„œ๋น„์Šค ๊ฐœ์„ ์ด ๊ฐ€๋Šฅํ•˜๋‹ค๊ณ  ์ฃผ์žฅํ–ˆ์Šต๋‹ˆ๋‹ค. ์ฒ ๋„, ๊ฐ€์Šค, ์ˆ˜๋„, ์ „๊ธฐ, ํ†ต์‹  ๋“ฑ ๋Œ€๊ทœ๋ชจ ๊ตญ์˜ ์‚ฐ์—…์˜ ๋ฏผ์˜ํ™”์—๋„ ์ง€์  ๊ธฐ๋ฐ˜์„ ์ œ๊ณตํ–ˆ์Šต๋‹ˆ๋‹ค.

๋ฒ„ํ‹€๋Ÿฌ๋Š” ์ด๋Ÿฌํ•œ ๋ฏผ์˜ํ™”๊ฐ€ โ€œ์ž๋ณธ ์†Œ์œ  ๋ฏผ์ฃผ์ฃผ์˜(capital-owning democracy)โ€œ๋ฅผ ์ด‰์ง„ํ–ˆ๋‹ค๊ณ  ์˜นํ˜ธํ•ฉ๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์ €๋ ดํ•œ ๊ฐ€๊ฒฉ์œผ๋กœ ์ฃผํƒ์„ ๊ตฌ๋งคํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ•˜์—ฌ ์‚ฌ๋žŒ๋“ค์ด ์ž์‚ฐ์„ ํ˜•์„ฑํ•˜๊ณ  ์‚ฌ์—…์„ ์‹œ์ž‘ํ•  ์ˆ˜ ์žˆ๊ฒŒ ํ–ˆ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ๋ฌผ๋ก  ๋ฏผ์˜ํ™” ๊ณผ์ •์—์„œ ์‹ค์ˆ˜๊ฐ€ ์žˆ์—ˆ์ง€๋งŒ, ์˜๊ตญ์ด ์ตœ์ดˆ๋กœ ์‹œ๋„ํ•œ ๋งŒํผ ๋ถˆ๊ฐ€ํ”ผํ–ˆ์œผ๋ฉฐ, ๋Œ€๋ถ€๋ถ„์˜ ๋ฏผ์˜ํ™”๋Š” ๋˜๋Œ๋ ค์ง€์ง€ ์•Š์•˜๋‹ค๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ตญ๋ฏผ๋ณด๊ฑด์„œ๋น„์Šค(NHS)๋Š” ์—ฌ์ „ํžˆ ๋ฏผ์˜ํ™”๋˜์ง€ ์•Š์€ โ€œํฐ ์‹คํŒจโ€๋กœ ๋‚จ์•„์žˆ๋‹ค๊ณ  ์•„์‰ฌ์›€์„ ํ‘œํ•ฉ๋‹ˆ๋‹ค.

โ€˜์• ๋ค ์Šค๋ฏธ์Šค ๋ฌธ์ œโ€™์™€ ํ˜„๋Œ€์  ํ•ด์„์˜ ๊ณผ์ œ

์• ๋ค ์Šค๋ฏธ์Šค ์—ฐ๊ตฌ์†Œ์˜ ์†Œ์žฅ์ด ์Šค๋ฏธ์Šค์˜ ์ฑ…์„ ์ฝ์„ ํ•„์š”๊ฐ€ ์—†๋‹ค๊ณ  ๋งํ•˜๋Š” ๊ฒƒ์€ ์•„์ด๋Ÿฌ๋‹ˆํ•˜๊ฒŒ ๋“ค๋ฆด ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋ชฌ ๋ฒ„ํ‹€๋Ÿฌ๋Š” ใ€Ž๊ตญ๋ถ€๋ก ใ€์˜ 5๊ถŒ, ์ฆ‰ ์ •๋ถ€์˜ ์—ญํ• (๊ต์œก, ์ธํ”„๋ผ, ๋ฒ•๊ณผ ์งˆ์„œ ๋“ฑ)์„ ๋‹ค๋ฃจ๋Š” ๋ถ€๋ถ„์ด โ€œ์„œ๋‘˜๋Ÿฌ ์“ฐ์—ฌ์กŒ๋‹คโ€๊ณ  ์ฃผ์žฅํ•˜๋ฉฐ, ์Šค๋ฏธ์Šค ์‚ฌ์ƒ์˜ ํ•ต์‹ฌ์ด ์•„๋‹ˆ๋ผ๊ณ  ์ผ์ถ•ํ•ฉ๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ์ƒ์ดํ•œ ํ•ด์„์€ 19์„ธ๊ธฐ ๋…์ผ ํ•™์ž๋“ค์— ์˜ํ•ด โ€˜์• ๋ค ์Šค๋ฏธ์Šค ๋ฌธ์ œ(das Adam Smith Problem)โ€˜๋กœ ๋ถˆ๋ฆฌ๊ฒŒ ๋œ ํ˜„์ƒ๊ณผ ๋งž๋‹ฟ์•„ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ใ€Ž๋„๋•๊ฐ์ •๋ก ใ€์˜ ์‹ฌ์˜คํ•œ ์ธ๊ฐ„์ฃผ์˜์™€ ใ€Ž๊ตญ๋ถ€๋ก ใ€์˜ ์ž์œ  ์‹œ์žฅ ์ง€์นจ์„œ ์‚ฌ์ด์˜ ์ธ์ง€๋œ ๋ถˆ์ผ์น˜, ์ฆ‰ ์Šค๋ฏธ์Šค๊ฐ€ ๋‘ ์ €์„œ ์‚ฌ์ด์— ๋งˆ์Œ์„ ๋ฐ”๊ฟจ๋‹ค๋Š” ์ด๋ก ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค. ๊ธ€๋กœ๋ฆฌ ๋ฃจ๋Š” ์ด๋ฅผ โ€œ๊ฐ€์งœ ๋ฌธ์ œ(pseudo-problem)โ€œ๋ผ๊ณ  ๋ถ€๋ฅด๋ฉฐ, ๋…์ผ ํ•™์ž๋“ค์ด ์Šค๋ฏธ์Šค ์‚ฌ์ƒ์˜ ์ฒ ํ•™์  ์ผ๊ด€์„ฑ์„ ํšŒ๋ณตํ•˜๋Š” ๋ฐ ๊ด€์‹ฌ์„ ๊ฐ€์กŒ๋˜ ๋ฐ˜๋ฉด, ์˜๊ตญ๊ณผ ๋ฏธ๊ตญ์—์„œ๋Š” ๊ทธ์˜ ์‚ฌ์ƒ์„ ์‹ค์šฉ์ ์ธ ๋ชฉ์ ์— ๋งž๊ฒŒ ํ•ด์„ํ•˜๋Š” ๋ฐ ๋” ์ง‘์ค‘ํ–ˆ๊ธฐ ๋•Œ๋ฌธ์— ๋ฐœ์ƒํ–ˆ๋‹ค๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค.

๊ฒฝ์ œ์‚ฌํ•™์ž ๋กœ๋ฒ„ํŠธ ํ•˜์ผ๋ธŒ๋กœ๋„ˆ(Robert Heilbroner)๊ฐ€ โ€œ์• ๋ค ์Šค๋ฏธ์Šค๋งŒํผ ์ž์ฃผ ์ธ์šฉ๋˜๋Š” ๊ฒฝ์ œํ•™์ž์˜ ์ด๋ฆ„์€ ์—†์ง€๋งŒ, ๊ทธ์˜ ์ €์ž‘๋งŒํผ ๋œ ์ฝํžˆ๋Š” ๊ฒƒ๋„ ์—†๋‹คโ€๊ณ  ๋งํ–ˆ๋“ฏ์ด, ์Šค๋ฏธ์Šค์˜ ์ด๋ฆ„์€ ์˜ค๋Š˜๋‚ ์—๋„ ๋Š์ž„์—†์ด ์†Œํ™˜๋˜์ง€๋งŒ, ๊ทธ์˜ ๋ณต์žกํ•œ ์‚ฌ์ƒ ์ „์ฒด๋Š” ์ œ๋Œ€๋กœ ์ดํ•ด๋˜์ง€ ๋ชปํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

์Šค๋ฏธ์Šค๋ฅผ ๋‹ค์‹œ ์ฝ์œผ๋ฉฐ: ์ง„์ •ํ•œ ์œ ์‚ฐ์˜ ํƒ์ƒ‰

์• ๋ค ์Šค๋ฏธ์Šค๋Š” ๋‹จ์ˆœํžˆ ์ž์œ  ์‹œ์žฅ์„ ๋งน๋ชฉ์ ์œผ๋กœ ์˜นํ˜ธํ•œ ์ธ๋ฌผ์ด ์•„๋‹ˆ์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ธ๊ฐ„์˜ ๋„๋•์  ๊ฐ์ •์„ ํƒ๊ตฌํ•˜๊ณ , ์ƒ์—… ์‚ฌํšŒ๊ฐ€ ๊ฐ€์ ธ์˜ฌ ์ˆ˜ ์žˆ๋Š” ์œ„ํ—˜๊ณผ ๋ถˆํ‰๋“ฑ์„ ๊ฒฝ๊ณ ํ•˜๋ฉด์„œ๋„, ๊ถ๊ทน์ ์œผ๋กœ๋Š” ๋‹ค๋ฅธ ์‚ฌํšŒ ํ˜•ํƒœ๋ณด๋‹ค ์ƒ์—… ์‚ฌํšŒ๊ฐ€ ๋” ๋งŽ์€ ์ž์œ ์™€ ๋ฒˆ์˜์„ ๊ฐ€์ ธ๋‹ค์ค„ ๊ฒƒ์ด๋ผ๊ณ  ๋ฏฟ์—ˆ๋˜ ๋ณตํ•ฉ์ ์ธ ์‚ฌ์ƒ๊ฐ€์˜€์Šต๋‹ˆ๋‹ค. ๊ทธ์˜ ์‚ฌ์ƒ์€ ์‹œ๋Œ€์™€ ๋งฅ๋ฝ์— ๋”ฐ๋ผ ๋‹ค์–‘ํ•˜๊ฒŒ ํ•ด์„๋˜๊ณ  ํ™œ์šฉ๋˜์–ด ์™”์œผ๋ฉฐ, ํŠนํžˆ 20์„ธ๊ธฐ ์‹œ์นด๊ณ  ํ•™ํŒŒ์— ์˜ํ•ด โ€˜๋ณด์ด์ง€ ์•Š๋Š” ์†โ€™๊ณผ โ€˜์ž๊ธฐ ์ด์ตโ€™์ด ๊ณผ๋„ํ•˜๊ฒŒ ๊ฐ•์กฐ๋˜๋ฉด์„œ ๊ทธ์˜ ์ด๋ฏธ์ง€๋Š” ํŠน์ • ์ •์น˜์  ์ด๋…๊ณผ ๋™์ผ์‹œ๋˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€์Šต๋‹ˆ๋‹ค.

์˜ค๋Š˜๋‚ ์—๋„ ์• ๋ค ์Šค๋ฏธ์Šค์˜ ์œ ์‚ฐ์€ ๊ณ„์†ํ•ด์„œ ๋…ผ์Ÿ์˜ ๋Œ€์ƒ์ด ๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ์˜ ์ง„์ •ํ•œ ๋ฉ”์‹œ์ง€๋ฅผ ์ดํ•ดํ•˜๊ธฐ ์œ„ํ•ด์„œ๋Š” ใ€Ž๊ตญ๋ถ€๋ก ใ€๋ฟ๋งŒ ์•„๋‹ˆ๋ผ ใ€Ž๋„๋•๊ฐ์ •๋ก ใ€์„ ํ•จ๊ป˜ ์ฝ๊ณ , ๊ทธ์˜ ์‚ฌ์ƒ์  ๋ฐฐ๊ฒฝ๊ณผ ๋‹น๋Œ€์˜ ๋งฅ๋ฝ์„ ๊นŠ์ด ์žˆ๊ฒŒ ํƒ๊ตฌํ•˜๋ ค๋Š” ๋…ธ๋ ฅ์ด ํ•„์š”ํ•  ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์• ๋ค ์Šค๋ฏธ์Šค๋Š” ๋‹จ์ˆœํ•œ โ€˜์šฐํŒŒ ๊ฒฝ์ œํ•™์žโ€™๋ผ๋Š” ๊ผฌ๋ฆฌํ‘œ๋ฅผ ๋„˜์–ด, ์ธ๊ฐ„ ์‚ฌํšŒ์™€ ๊ฒฝ์ œ์— ๋Œ€ํ•œ ๊นŠ์€ ํ†ต์ฐฐ์„ ์ œ๊ณตํ–ˆ๋˜ ์œ„๋Œ€ํ•œ ๋„๋• ์ฒ ํ•™์ž์ด์ž ๊ฒฝ์ œํ•™์ž์˜€์Šต๋‹ˆ๋‹ค. ๊ทธ์˜ ๋ณต์žกํ•œ ์‚ฌ์ƒ์„ ์˜จ์ „ํžˆ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์€ ํ˜„๋Œ€ ์‚ฌํšŒ๊ฐ€ ์ง๋ฉดํ•œ ๋‹ค์–‘ํ•œ ๊ฒฝ์ œ์ , ์‚ฌํšŒ์  ๋ฌธ์ œ์— ๋Œ€ํ•œ ์ƒˆ๋กœ์šด ํ•ด๋‹ต์„ ์ฐพ๋Š” ๋ฐ ์ค‘์š”ํ•œ ์ถœ๋ฐœ์ ์ด ๋  ๊ฒƒ์ž…๋‹ˆ๋‹ค.


โ€œQuests, token leaderboards, and a skills marketplace: the elite AI adoption playbook | John Kimโ€ โ€” How I AI ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

AI โ€˜์‹ (็ฅž)โ€˜์„ ํ‚ค์šฐ๋Š” ๊ธฐ์—…: ํ€˜์ŠคํŠธ, ํ† ํฐ ๋ฆฌ๋”๋ณด๋“œ, ๊ทธ๋ฆฌ๊ณ  ์ „์‚ฌ์  AI ๋„์ž…์˜ ๋น„๋ฐ€

AI๊ฐ€ ๋‹จ์ˆœํžˆ ์—…๋ฌด ํšจ์œจ์„ ๋†’์ด๋Š” ๋„๊ตฌ๋ฅผ ๋„˜์–ด, ๊ธฐ์—…์˜ ๋ฌธํ™”์™€ ์ƒ์‚ฐ์„ฑ์„ ๊ทผ๋ณธ์ ์œผ๋กœ ๋ณ€ํ™”์‹œํ‚ค๋Š” ํ•ต์‹ฌ ๋™๋ ฅ์œผ๋กœ ๋ถ€์ƒํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. โ€˜How I AIโ€™ ์ฑ„๋„์— ์ถœ์—ฐํ•œ ์„ ๋ฒ„๋“œ(Sunbird)์˜ ์ฐฝ๋ฆฝ์ž์ด์ž CEO์ธ ์กด ๊น€(John Kim)์€ AI๋ฅผ ํ†ตํ•ด ์ง์› ๊ฐœ๊ฐœ์ธ์ด ์ฐฝ์˜์„ฑ์„ ๋ฐœํœ˜ํ•˜๊ณ , ๊ธฐ์—… ์ „์ฒด๊ฐ€ โ€˜AI ์šฐ์„ (AI-First)โ€™ ์กฐ์ง์œผ๋กœ ๊ฑฐ๋“ญ๋‚˜๋Š” ํ˜์‹ ์ ์ธ ์ „๋žต์„ ์†Œ๊ฐœํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ๋งˆ์ผ€ํ„ฐ๊ฐ€ ์ฝ”๋”ฉ ์—†์ด ์›น์‚ฌ์ดํŠธ๋ฅผ ๋งŒ๋“ค๊ณ , ๋ชจ๋“  ์ง์›์ด AI ์ž๋™ํ™” โ€˜ํ€˜์ŠคํŠธโ€™์— ์ฐธ์—ฌํ•˜๋ฉฐ, AI ํ† ํฐ ์†Œ๋น„๋Ÿ‰์œผ๋กœ โ€˜AI ์‹ (็ฅž)โ€˜์˜ ๋“ฑ๊ธ‰์„ ๋งค๊ธฐ๋Š” ๋…ํŠนํ•œ ์‹œ์Šคํ…œ์„ ํ†ตํ•ด ์ „์‚ฌ์  AI ๋„์ž…์˜ ์ƒˆ๋กœ์šด ์ฒญ์‚ฌ์ง„์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค.

AI ์‹œ๋Œ€๋ฅผ ์„ ๋„ํ•˜๋Š” ๊ธฐ์—… ๋ฌธํ™”: ๋งˆ์ผ€ํ„ฐ๋ฅผ ๋นŒ๋”๋กœ

์กด ๊น€ CEO๋Š” AI๊ฐ€ ๋” ์ด์ƒ ์†Œ์ˆ˜์˜ ์—”์ง€๋‹ˆ์–ด์—๊ฒŒ๋งŒ ๊ตญํ•œ๋œ ๊ธฐ์ˆ ์ด ์•„๋‹ˆ๋ผ๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Š” AI์˜ ํž˜์„ ๋งˆ์ผ€ํ„ฐ, ์˜์—…์‚ฌ์› ๋“ฑ ๋ชจ๋“  ์ง๋ฌด์— ๋ถ€์—ฌํ•จ์œผ๋กœ์จ ๊ธฐ์—…์ด ๋†€๋ผ์šด ์•„์ด๋””์–ด๋ฅผ ์‹ ์†ํ•˜๊ฒŒ ์‹œ์žฅ์— ์„ ๋ณด์ผ ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ์„ ๋ฒ„๋“œ์˜ ๋งˆ์ผ€ํŒ…ํŒ€์ด ์—”์ง€๋‹ˆ์–ด ์ง€์› ์—†์ด ์ง์ ‘ ๊ตฌ์ถ•ํ•œ โ€˜๋น… S ์—๋„ˆ์ง€(Big S Energy)โ€™ ์Šค์›จ๊ทธ ์Šคํ† ์–ด๋Š” ์ด๋Ÿฌํ•œ ์ฒ ํ•™์˜ ์ƒ์ƒํ•œ ์ฆ๊ฑฐ์ž…๋‹ˆ๋‹ค.

์ด ์Šคํ† ์–ด๋Š” ๋‹จ์ˆœํžˆ ์ƒํ’ˆ์„ ํŒ๋งคํ•˜๋Š” ๊ฒƒ์„ ๋„˜์–ด, ์„ ๋ฒ„๋“œ์˜ ๋…ํŠนํ•œ ๋ฌธํ™”๋ฅผ ๋ฐ˜์˜ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋งˆ์ผ€ํŒ…ํŒ€์€ ์ŠคํŠธ๋ผ์ดํ”„(Stripe) ๊ฒฐ์ œ ์‹œ์Šคํ…œ๊นŒ์ง€ ํ†ตํ•ฉํ•˜๋ฉฐ, โ€˜๋‚ด ์—‰๋ฉ์ด๋Š” ๋„ˆ์˜ SAS๋ณด๋‹ค ํฌ๋‹ค(My ass is bigger than your SAS)โ€™ ๊ฐ™์€ ์žฌ์น˜ ์žˆ๋Š” ๋ฌธ๊ตฌ๊ฐ€ ๋‹ด๊ธด ์ƒํ’ˆ๋“ค์„ ์„ ๋ณด์˜€์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ๊ฒŒ์ด๋จธ๋“ค์„ ์œ„ํ•œ โ€˜์ฝ”๋‚˜๋ฏธ ์ฝ”๋“œ(Konami Code)โ€™ ์ด์Šคํ„ฐ ์—๊ทธ๋ฅผ ์ˆจ๊ฒจ, ํŠน์ • ํ‚ค ์กฐํ•ฉ์„ ์ž…๋ ฅํ•˜๋ฉด 5์›” 7์ผ ์ƒŒํ”„๋ž€์‹œ์Šค์ฝ”์—์„œ ์—ด๋ฆฌ๋Š” โ€˜๋”œ๋ผ์ดํŠธ ์ŠคํŒŒํฌ(Delight Spark)โ€™ ์ปจํผ๋Ÿฐ์Šค ์ •๋ณด๋ฅผ ์–ป์„ ์ˆ˜ ์žˆ๋„๋ก ํ–ˆ์Šต๋‹ˆ๋‹ค.

์กด ๊น€ CEO๋Š” โ€œ๋งˆ์ผ€ํ„ฐ์—๊ฒŒ ๋งˆ์Œ๊ป ์š”๋ฆฌํ•  ์ˆ˜ ์žˆ๋Š” ํ™˜๊ฒฝ์„ ์ œ๊ณตํ•˜๋ผโ€๋Š” ๋ฐˆ๋กœ๋“œ(Memelord) CEO ์ œ์ด์Šจ ๋ฆฌ๋ฒค(Jason Leven)์˜ ๋ง์„ ์ธ์šฉํ•˜๋ฉฐ, ๋งˆ์ผ€ํ„ฐ๊ฐ€ ์ง์ ‘ ๋นŒ๋”๊ฐ€ ๋  ๋•Œ ๊ณ ๊ฐ์„ ๊ธฐ์˜๊ฒŒ ํ•˜๊ณ  ์ƒˆ๋กœ์šด ๊ณ ๊ฐ์„ ์œ ์น˜ํ•˜๋Š” ์ฐฝ์˜์ ์ธ ๊ฒฐ๊ณผ๋ฌผ์„ ๋งŒ๋“ค์–ด๋‚ผ ์ˆ˜ ์žˆ๋‹ค๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค. ๊ณผ๊ฑฐ์—๋Š” ๋งˆ์ผ€ํŒ…ํŒ€์˜ ์•„์ด๋””์–ด๊ฐ€ ์—”์ง€๋‹ˆ์–ด๋ง ๋ฆฌ์†Œ์Šค์˜ ์šฐ์„ ์ˆœ์œ„ ๋ฌธ์ œ๋กœ ์ขŒ์ ˆ๋˜๊ธฐ ์ผ์‘ค์˜€์ง€๋งŒ, AI ์‹œ๋Œ€์—๋Š” ๋งˆ์ผ€ํ„ฐ๊ฐ€ ๋‹จ ๋ฉฐ์น  ๋งŒ์— ์•„์ด๋””์–ด๋ฅผ ํ˜„์‹ค๋กœ ๋งŒ๋“ค ์ˆ˜ ์žˆ๊ฒŒ ๋œ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๋‹จ์ˆœํžˆ โ€˜๋” ๋น ๋ฅด๊ฒŒโ€™ ์ผํ•˜๋Š” ๊ฒƒ์„ ๋„˜์–ด, โ€˜๋” ํฐ ์•ผ๋งโ€™์„ ๊ฐ€์ง€๊ณ  โ€˜๋” ์žฌ๋ฏธ์žˆ๋Š”โ€™ ์ผ๋“ค์„ ํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋จ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

์ „์‚ฌ์  AI ๋„์ž…์˜ ํ•ต์‹ฌ: โ€˜์˜คํ† ๋ฉ”์ดํ„ฐ ํ”Œ๋žซํผโ€™๊ณผ โ€˜ํ€˜์ŠคํŠธโ€™

์„ ๋ฒ„๋“œ๋Š” ์ด๋Ÿฌํ•œ ๋ณ€ํ™”๋ฅผ ์ด‰์ง„ํ•˜๊ธฐ ์œ„ํ•ด โ€˜์˜คํ† ๋ฉ”์ดํ„ฐ ํ”Œ๋žซํผ(Automator Platform)โ€˜์ด๋ผ๋Š” ๋…์ž์ ์ธ ์‚ฌ๋‚ด ํ”Œ๋žซํผ์„ ๊ตฌ์ถ•ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ํ”Œ๋žซํผ์€ ํšŒ์‚ฌ ๋‚ด ๋ˆ„๊ตฌ๋“  โ€˜ํ€˜์ŠคํŠธ(Quest)โ€˜๋ฅผ ์ƒ์„ฑํ•˜์—ฌ ํŠน์ • AI ์ž๋™ํ™” ๋˜๋Š” ๋„๊ตฌ ๊ฐœ๋ฐœ์„ ์š”์ฒญํ•  ์ˆ˜ ์žˆ๋Š” ์ผ์ข…์˜ ๋‚ด๋ถ€ ๋งˆ์ผ“ํ”Œ๋ ˆ์ด์Šค์ž…๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์žฌ๋ฌดํŒ€ ์ง์›์ด ์ˆ˜๊ธˆ ๋ฐ ์ง€๊ธ‰ ์›Œํฌํ”Œ๋กœ์šฐ ์ž๋™ํ™”๋ฅผ ์š”์ฒญํ•˜๋ฉด, ๋‹ค๋ฅธ ์—”์ง€๋‹ˆ์–ด๋“ค์ด ๋•๊ฑฐ๋‚˜ AI ์—ญ๋Ÿ‰์„ ๊ฐ–์ถ˜ ์ง์›๋“ค์ด ์ง์ ‘ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

๋†€๋ผ์šด ์ ์€ ์ด์ œ AI๊ฐ€ ์ง์ ‘ ํ€˜์ŠคํŠธ์— ์ฐธ์—ฌํ•œ๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. AI๋Š” ํ€˜์ŠคํŠธ ์‚ฌ์–‘(specification)์„ ์ฝ๊ณ  ์ œํ’ˆ ์š”๊ตฌ์‚ฌํ•ญ ๋ฌธ์„œ(PRD)๋ฅผ ์ž‘์„ฑํ•˜๋ฉฐ, ์‹ฌ์ง€์–ด ์ฝ”๋”ฉ๊นŒ์ง€ ์‹œ์ž‘ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ์ธ๊ฐ„ ์—”์ง€๋‹ˆ์–ด์™€ ํŒ€์›๋“ค ์™ธ์— AI ์—์ด์ „ํŠธ(AI Agents)๊นŒ์ง€ ์ž๋™ํ™” ๋ฐ ์›Œํฌํ”Œ๋กœ์šฐ ๊ตฌ์ถ•์— ์ฐธ์—ฌํ•˜๋Š” ๋‹ค์Œ ๋‹จ๊ณ„์˜ ํ˜์‹ ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

ํ€˜์ŠคํŠธ ์‹œ์Šคํ…œ์€ ์ „ํ†ต์ ์ธ ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋ฐœ์˜ โ€˜์Šคํ”„๋ฆฐํŠธ(Sprint)โ€™ ๋ฐ โ€˜์šฐ์„ ์ˆœ์œ„(Prioritization)โ€˜์˜ ์ œ์•ฝ์„ ๋›ฐ์–ด๋„˜์Šต๋‹ˆ๋‹ค. ์ง์›๋“ค์€ ์ž ์‹œ ์—ฌ์œ  ์‹œ๊ฐ„์ด ์ƒ๊ธธ ๋•Œ ์ฃผ์š” ์ œํ’ˆ ๋กœ๋“œ๋งต์— ๋ฌถ์ด์ง€ ์•Š์€ ์ž‘์€ ์‚ฌ์ด๋“œ ํ”„๋กœ์ ํŠธ๋‚˜ ์ฆ‰๊ฐ์ ์ธ ์‚ฌ๋‚ด ๊ณ ๊ฐ์˜ ๋ฌธ์ œ๋ฅผ ํ•ด๊ฒฐํ•˜๋Š” ๋ฐ ๊ธฐ์—ฌํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ํ€˜์ŠคํŠธ๋ฅผ ์™„๋ฃŒํ•œ ์ง์›๋“ค์€ ๊ฒฝํ—˜์น˜(XP)๋ฅผ ์–ป๊ณ , ์ด๋ฅผ ๊ธฐํ”„ํŠธ์นด๋“œ, ์ž„์›๊ณผ์˜ ํ‹ฐํƒ€์ž„, ์ „์‚ฌ ๋ฐœํ‘œ ๊ธฐํšŒ ๋“ฑ์œผ๋กœ ๊ตํ™˜ํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๋งค์ฃผ ์ˆ˜์š”์ผ ์Šคํƒ ๋“œ์—… ๋ฏธํŒ…์—์„œ๋Š” ๋‹ค์–‘ํ•œ ํŒ€(์˜์—…, ๋งˆ์ผ€ํŒ…, ์ฑ„์šฉ ๋“ฑ)์ด ์ž์‹ ๋“ค์ด AI๋กœ ๊ตฌ์ถ•ํ•œ ๊ฒฐ๊ณผ๋ฌผ์„ ๊ณต์œ ํ•˜๋ฉฐ ์ „์‚ฌ์ ์ธ ๋™๊ธฐ ๋ถ€์—ฌ๋ฅผ ์ด๋Œ์–ด๋ƒ…๋‹ˆ๋‹ค.

๋˜ํ•œ, ์„ ๋ฒ„๋“œ๋Š” AI ๋„๊ตฌ ๊ตฌ์ถ•์„ ์œ„ํ•œ โ€˜ํ•ดํ”ผ ํŒจ์Šค(Happy Path)โ€˜๋ฅผ ์ œ๊ณตํ•ฉ๋‹ˆ๋‹ค. ๊นƒํ—ˆ๋ธŒ(GitHub) ์„ค์ •, ์ƒˆ๋กœ์šด ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜ ์ƒ์„ฑ ๋ฐฉ๋ฒ• ๋“ฑ ํ•ต์‹ฌ ๊ธฐ์ˆ  ํ•™์Šต ๊ฐ€์ด๋“œ๋ฅผ ์ œ๊ณตํ•˜๊ณ , ์ธ์ฆ ๋ฐ ํ™˜๊ฒฝ ์„ค์ •์ด ์™„๋ฃŒ๋œ ์•ฑ ํ…œํ”Œ๋ฆฟ์„ ์ œ๊ณตํ•˜์—ฌ ๋งˆ์ผ€ํ„ฐ๋‚˜ ๊ณ ๊ฐ ์„ฑ๊ณต ๊ด€๋ฆฌ์ž(CSM)๊ฐ€ ์•„์ด๋””์–ด๋งŒ ์žˆ์œผ๋ฉด ์ธํ”„๋ผ ๊ฑฑ์ • ์—†์ด ์•ˆ์ „ํ•˜๊ณ  ๊ทœ์ •์„ ์ค€์ˆ˜ํ•˜๋Š” ์• ํ”Œ๋ฆฌ์ผ€์ด์…˜์„ ๋น ๋ฅด๊ฒŒ ๊ตฌ์ถ•ํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ์ „์‚ฌ์  AI ์ „ํ™˜์„ ๊ฐ€์†ํ™”ํ•˜๊ธฐ ์œ„ํ•ด ์„ ๋ฒ„๋“œ๋Š” โ€˜๋‚ด๋ถ€ ์šด์˜์„ ์œ„ํ•œ AI ์—”์ง€๋‹ˆ์–ด(AI Engineer for Internal Operations)โ€˜๋ผ๋Š” ์ „๋‹ดํŒ€์„ ์‹ ์„คํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ํŒ€์€ ์กด ๊น€ CEO์™€ ์ตœ๊ณ ์šด์˜์ฑ…์ž„์ž(Chief of Staff)์—๊ฒŒ ์ง์ ‘ ๋ณด๊ณ ํ•˜๋ฉฐ, ์ตœ๊ณ ๊ธฐ์ˆ ์ฑ…์ž„์ž(CTO) ๋ฐ ์ •๋ณด ๋ณด์•ˆ(Infosec) ํŒ€๊ณผ ๊ธด๋ฐ€ํžˆ ํ˜‘๋ ฅํ•˜์—ฌ ์ปดํ”Œ๋ผ์ด์–ธ์Šค, ๋กœ๊น…, ์†Œํ”„ํŠธ์›จ์–ด ๊ฒ€์ฆ ๋“ฑ AI ๋„์ž…์˜ ๋ชจ๋“  ์žฅ์• ๋ฌผ์„ ์ œ๊ฑฐํ•˜๋Š” ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค.

์‚ฌ๋‚ด AI โ€˜์Šคํ‚ฌ ๋งˆ์ผ“ํ”Œ๋ ˆ์ด์Šคโ€™ ๊ตฌ์ถ•

์„ ๋ฒ„๋“œ๋Š” โ€˜์Šคํ‚ฌ ๋งˆ์ผ“ํ”Œ๋ ˆ์ด์Šค(Skills Marketplace)โ€˜๋ฅผ ๊ตฌ์ถ•ํ•˜์—ฌ ์ง์›๋“ค์ด ํ”Œ๋Ÿฌ๊ทธ์ธ(Plugin) ํ˜•ํƒœ๋กœ AI ์Šคํ‚ฌ(Skills)์„ ์ƒ์„ฑํ•˜๊ณ  ๊ณต์œ ํ•˜๋ฉฐ ๋‹ค์šด๋กœ๋“œํ•  ์ˆ˜ ์žˆ๋„๋ก ํ–ˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์˜์—…ํŒ€์€ โ€˜๋ฉ”๋”• ํ”„๋ ˆ์ž„์›Œํฌ(Medic framework)โ€˜์— ๋Œ€ํ•œ ์Šคํ‚ฌ์„ ๋‹ค์šด๋กœ๋“œํ•˜์—ฌ ์˜์—… ์ „๋žต์— ๋Œ€ํ•œ ์กฐ์–ธ์„ ์–ป๊ฑฐ๋‚˜ ์ž์‹ ์˜ ์›Œํฌํ”Œ๋กœ์šฐ์— ํ†ตํ•ฉํ•  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๊ฐ ๊ธฐ๋Šฅ๋ณ„๋กœ ๋™์ผํ•œ ์•ฑ์ด๋‚˜ ์Šคํ‚ฌ์„ ์ค‘๋ณตํ•ด์„œ ๊ตฌ์ถ•ํ•˜๋Š” ๋น„ํšจ์œจ์„ ๋ฐฉ์ง€ํ•˜๊ณ , ์ „์‚ฌ์ ์œผ๋กœ โ€˜๊ณต๋™ ์ง„ํ™”(co-evolve)โ€˜ํ•  ์ˆ˜ ์žˆ๋Š” ํ™˜๊ฒฝ์„ ๋งŒ๋“ญ๋‹ˆ๋‹ค.

์Šคํ‚ฌ ๋„์ž…์€ โ€˜ํ•˜ํ–ฅ์‹(top-down)โ€™ ์ ‘๊ทผ(CEO ๋ฐ ์ž„์›๋“ค์˜ ์‚ฌ์šฉ ๋…๋ ค)๊ณผ โ€˜์ƒํ–ฅ์‹(bottom-up)โ€™ ์ ‘๊ทผ(์ง์›๋“ค์˜ ์ž๋ฐœ์  ํ˜ธ๊ธฐ์‹ฌ๊ณผ ํ•™์Šต)์ด ๊ฒฐํ•ฉ๋˜์–ด ์ด๋ฃจ์–ด์กŒ์Šต๋‹ˆ๋‹ค. ์ž„์›๋“ค์€ AI ํ† ํฐ ์†Œ๋น„๋Ÿ‰์ด ์ ์€ ์ง์›๋“ค์„ ๊ฐœ๋ณ„์ ์œผ๋กœ ์ฐพ์•„๊ฐ€ ์ง€์›์„ ์ œ์•ˆํ–ˆ๊ณ , ํ˜ธ๊ธฐ์‹ฌ ๋งŽ์€ ์ง์›๋“ค์€ ์Šฌ๋ž™(Slack) ์ฑ„๋„์ด๋‚˜ ์‚ฌ๋‚ด ๋ธ”๋กœ๊ทธ๋ฅผ ํ†ตํ•ด ์Šคํ‚ฌ์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์ ‘ํ•˜๋ฉฐ ์ž๋ฐœ์ ์œผ๋กœ ํ•™์Šตํ–ˆ์Šต๋‹ˆ๋‹ค. ํŠนํžˆ, ๋น„๋””์ž์ด๋„ˆ ์ง์›์ด AI ์Šคํ‚ฌ์„ ํ™œ์šฉํ•˜์—ฌ ์•„๋ฆ„๋‹ค์šด ์Šฌ๋ผ์ด๋“œ๋ฅผ ๋งŒ๋“ค์–ด ๋ฐœํ‘œํ•˜๋Š” ์‚ฌ๋ก€๋Š” ๋‹ค๋ฅธ ์ง์›๋“ค์—๊ฒŒ ํฐ ์˜๊ฐ์„ ์ฃผ๋ฉฐ ์œ ๊ธฐ์ ์ธ ํ•™์Šต๊ณผ ํ™•์‚ฐ์„ ์ด‰์ง„ํ–ˆ์Šต๋‹ˆ๋‹ค.

AI ํ™œ์šฉ ์„ฑ๊ณผ ์ธก์ •: โ€˜ํ† ํฐ ์†Œ๋น„ ๋ฆฌ๋”๋ณด๋“œโ€™์˜ ํž˜

AI ๋„์ž…์˜ ์„ฑ๊ณต์„ ์œ„ํ•ด ์„ ๋ฒ„๋“œ๋Š” AI ํ† ํฐ(Token) ์†Œ๋น„๋Ÿ‰์„ ์ธก์ •ํ•˜๋Š” ๋Œ€์‹œ๋ณด๋“œ์™€ ๋ฆฌ๋”๋ณด๋“œ๋ฅผ ์šด์˜ํ•ฉ๋‹ˆ๋‹ค. ์ด๋Š” ์—”์ง€๋‹ˆ์–ด์˜ ์ƒ์‚ฐ์„ฑ์„ ์ฝ”๋“œ ๋ผ์ธ ์ˆ˜๋กœ ์ธก์ •ํ•˜๋˜ ๊ณผ๊ฑฐ์˜ ์˜ค๋ฅ˜๋ฅผ ๋ฐ˜๋ณตํ•˜์ง€ ์•Š๊ธฐ ์œ„ํ•จ์ž…๋‹ˆ๋‹ค. ์„ ๋ฒ„๋“œ์˜ ๋ชฉํ‘œ๋Š” ํ† ํฐ ์†Œ๋น„๋Ÿ‰์„ ํ†ตํ•ด ์ง์›๋“ค์ด AI ์‚ฌ์šฉ๋ฒ•์„ ๋ฐฐ์šฐ๊ณ  ์žˆ๋Š”์ง€, ๊ทธ๋ฆฌ๊ณ  AI๋ฅผ ์—ฌ์ •์˜ ๋™๋ฐ˜์ž๋กœ ์ธ์‹ํ•˜๊ณ  ์žˆ๋Š”์ง€ ์ดํ•ดํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

๋Œ€์‹œ๋ณด๋“œ๋Š” ํšŒ์‚ฌ ์ „์ฒด, ํŒ€, ๊ทธ๋ฆฌ๊ณ  ๊ฐœ์ธ๋ณ„ ํ† ํฐ ์‚ฌ์šฉ๋Ÿ‰์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ํ˜„์žฌ ์„ ๋ฒ„๋“œ๋Š” ํด๋กœ๋“œ ์ฝ”๋“œ(Claude Code) ์‚ฌ์šฉ๋Ÿ‰์ด ๋งŽ์ง€๋งŒ, ์ƒ์œ„ ํ† ํฐ ์†Œ๋น„์ž ์ค‘ ์ผ๋ถ€๋Š” ์ฝ”๋ฑ์Šค(Codecs)๋ฅผ ์‚ฌ์šฉํ•˜์—ฌ ๋ ˆ๊ฑฐ์‹œ ์ฝ”๋“œ๋ฒ ์ด์Šค๋ฅผ ๊ด€๋ฆฌํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ํฅ๋ฏธ๋กญ๊ฒŒ๋„ ์ด๋Š” ์œ ๊ธฐ์ ์œผ๋กœ ๋ฐœ์ƒํ•œ ํ˜„์ƒ์œผ๋กœ, ๋ณต์žกํ•œ ์ฝ”๋“œ๋ฒ ์ด์Šค ๊ด€๋ฆฌ์—๋Š” ์ฝ”๋ฑ์Šค๊ฐ€, ์‹ ์†ํ•œ ์ œํ’ˆ ๊ธฐ๋Šฅ ๊ตฌ์ถ•์—๋Š” ํด๋กœ๋“œ ์ฝ”๋“œ๊ฐ€ ์„ ํ˜ธ๋˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์ž…๋‹ˆ๋‹ค.

์กด ๊น€ CEO๋Š” โ€œํ† ํฐ ์†Œ๋น„ ๊ณก์„ ์ด ๋งค๋„๋Ÿฌ์›Œ์ง„๋‹ค(smoothing the curve)โ€œ๋Š” ๊ฒƒ์€ ์ง์›๋“ค์ด ํœด๊ฐ€ ์ค‘์ผ ๋•Œ๋„ AI ํŒŒํŠธ๋„ˆ๊ฐ€ 24์‹œ๊ฐ„ ๋‚ด๋‚ด ์ž‘๋™ํ•˜๋ฉฐ ์—…๋ฌด ๊ณต๋ฐฑ์„ ๋ฉ”์šฐ๊ณ  ์žˆ์Œ์„ ์˜๋ฏธํ•œ๋‹ค๊ณ  ์„ค๋ช…ํ•ฉ๋‹ˆ๋‹ค.

์„ ๋ฒ„๋“œ๋Š” โ€˜AI ์‹ (็ฅž)โ€™ ๋ฆฌ๋”๋ณด๋“œ๋ฅผ ํ†ตํ•ด ์ง์›๋“ค์„ ๋‹ค์„ฏ ๋‹จ๊ณ„(์ดˆ๋ณด์ž, ์ค‘๊ธ‰์ž, ์ „๋ฌธ๊ฐ€, ์„ค๊ณ„์ž, ์ด‰๋งค์ž, AI ์‹ )๋กœ ๋ถ„๋ฅ˜ํ•ฉ๋‹ˆ๋‹ค. ํ•˜๋ฃจ 1์–ต ๊ฐœ ์ด์ƒ์˜ ํ† ํฐ์„ ์†Œ๋น„ํ•˜๋Š” ์ง์›์ด โ€˜AI ์‹ โ€™์œผ๋กœ ๋ถ„๋ฅ˜๋ฉ๋‹ˆ๋‹ค. ๊ฐ ๊ด€๋ฆฌ์ž๋Š” ํŒ€์›๋“ค์˜ ํ˜„์žฌ ๋‹จ๊ณ„๋ฅผ ํŒŒ์•…ํ•˜๊ณ , ๊ทธ์— ๋งž๋Š” ๋งž์ถคํ˜• ๊ต์œก๊ณผ ์ง€์›์„ ์ œ๊ณตํ•˜์—ฌ ๋น ๋ฅด๊ฒŒ ๋‹ค์Œ ๋‹จ๊ณ„๋กœ ์„ฑ์žฅํ•  ์ˆ˜ ์žˆ๋„๋ก ๋•์Šต๋‹ˆ๋‹ค. ์กด ๊น€ CEO ์ž์‹ ๋„ ํ•˜๋ฃจ ํ‰๊ท  3์ฒœ๋งŒ~5์ฒœ๋งŒ ๊ฐœ์˜ ํ† ํฐ์„ ์†Œ๋น„ํ•˜๋Š” โ€˜์ด‰๋งค์ž(Catalyst)โ€™ ๋‹จ๊ณ„์— ์žˆ๋‹ค๊ณ  ๋ฐํ˜”์Šต๋‹ˆ๋‹ค.

์ด๋Ÿฌํ•œ ๋ฆฌ๋”๋ณด๋“œ ์‹œ์Šคํ…œ์€ AI ์‚ฌ์šฉ์„ ๊ฐ•์ œํ•˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ๋ช…ํ™•ํ•œ ๊ธฐ๋Œ€์น˜๋ฅผ ์„ค์ •ํ•˜๊ณ  AI ํผ์ŠคํŠธ(AI-First) ๋ฌธํ™”๊ฐ€ ๋ฌด์—‡์„ ์˜๋ฏธํ•˜๋Š”์ง€ ์ง์›๋“ค์—๊ฒŒ ์‹œ๊ฐ์ ์œผ๋กœ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ์ตœ๊ณ ๊ธฐ์ˆ ์ฑ…์ž„์ž(CTO)์™€ ๊ณต๋™ ์ฐฝ๋ฆฝ์ž ๋“ฑ ๋ฆฌ๋”๋“ค์ด ๊ฐ€์žฅ ๋งŽ์€ ํ† ํฐ์„ ์†Œ๋น„ํ•˜๋ฉฐ ์†”์„ ์ˆ˜๋ฒ”ํ•˜๋Š” ๋ชจ์Šต์€ ํŒ€ ์ „์ฒด์— ๊ฐ•๋ ฅํ•œ ๋ฉ”์‹œ์ง€๋ฅผ ์ „๋‹ฌํ•˜๊ณ , AI ํ™œ์šฉ์— ๋Œ€ํ•œ ์˜๊ฐ์„ ๋ถˆ์–ด๋„ฃ์Šต๋‹ˆ๋‹ค.

๊ฐœ์ธ ํ•™์Šต๊ณผ ์ƒ์‚ฐ์„ฑ ํ˜์‹ : AI ํ™œ์šฉ์˜ ๋ฌดํ•œํ•œ ๊ฐ€๋Šฅ์„ฑ

์กด ๊น€ CEO๋Š” ํšŒ์‚ฌ ์ฐจ์›์˜ AI ํ™œ์šฉ ์™ธ์—๋„ ๊ฐœ์ธ์ ์ธ AI ํ™œ์šฉ ์‚ฌ๋ก€๋ฅผ ๊ณต์œ ํ•˜๋ฉฐ AI์˜ ๋ฌดํ•œํ•œ ๊ฐ€๋Šฅ์„ฑ์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค.

๊ทธ๋Š” ์ง์ ‘ ๊ฐœ๋ฐœํ•œ ์˜คํ”ˆ์†Œ์Šค ํ”„๋กœ์ ํŠธ์ธ โ€˜๊ฐ€๋“œ๋„ˆ(Gardener)โ€˜๋ฅผ ์†Œ๊ฐœํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ๋„๊ตฌ๋Š” ์˜ต์‹œ๋””์–ธ(Obsidian)๊ณผ ๊ฐ™์€ ๋งˆํฌ๋‹ค์šด ๊ธฐ๋ฐ˜ ์ง€์‹ ๋ฒ ์ด์Šค๋ฅผ ํ™œ์šฉํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์„ ์œ„ํ•œ ๊ฒƒ์œผ๋กœ, ๋งค์ผ ๋…ธํŠธ๋ฅผ ๊ฒ€ํ† ํ•˜์—ฌ ๋‚ด์šฉ์„ ํ’๋ถ€ํ•˜๊ฒŒ ๋งŒ๋“ค๊ณ , ๋“ฑ๋ก๋˜์ง€ ์•Š์€ ์ธ๋ฌผ์ด๋‚˜ ํšŒ์‚ฌ์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ์กฐ์‚ฌํ•˜์—ฌ ์ถ”๊ฐ€ํ•˜๋ฉฐ, ์˜คํƒ€๋‚˜ ๋ฌธ๋ฒ• ์˜ค๋ฅ˜๋ฅผ ์ˆ˜์ •ํ•˜๊ณ , ์•„๋ฆ„๋‹ค์šด ์ œ๋ชฉ๊ณผ ํด๋Ÿฌ์Šคํ„ฐ, ์ƒํ˜ธ ์—ฐ๊ฒฐ์„ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค. ๋งˆ์น˜ ์ •์›์‚ฌ๊ฐ€ ์ •์›์„ ๊ฐ€๊พธ๋“ฏ ๊ฐœ์ธ์˜ ์ง€์‹ ๋ฒ ์ด์Šค๋ฅผ ๋Š์ž„์—†์ด ๋Œ๋ณด๋Š” ์—ญํ• ์„ ํ•ฉ๋‹ˆ๋‹ค.

๋˜ํ•œ, ๊ทธ๋Š” AI๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์ž์‹ ๋งŒ์˜ โ€˜๊ฐœ์ธ ํ•™์Šต ์„ผํ„ฐ(Personal Learning Center)โ€˜๋ฅผ ๊ตฌ์ถ•ํ–ˆ์Šต๋‹ˆ๋‹ค. ์˜ˆ๋ฅผ ๋“ค์–ด, ์‹ ๊ฒฝ๊ณผํ•™(Neuroscience)์— ๊ด€์‹ฌ์ด ์žˆ๋‹ค๋ฉด, AI์—๊ฒŒ ์‹ ๊ฒฝ๊ณผํ•™ ์—ฐ๊ตฌ์ž๊ฐ€ ๋˜์–ด ๋ฐฐ์šฐ๊ณ  ์‹ถ์€ ๋‚ด์šฉ์„ ํ”„๋กฌํ”„ํŠธ๋กœ ์ „๋‹ฌํ•˜๋ฉด, AI๊ฐ€ ์‹ ๊ฒฝ๊ณผํ•™์— ๋Œ€ํ•œ ๋ชจ๋“  ๊ฒƒ์„ ๋ฐฐ์šธ ์ˆ˜ ์žˆ๋Š” ์•„๋ฆ„๋‹ค์šด ๊ตฌ์กฐ๋ฅผ ์ƒ์„ฑํ•ฉ๋‹ˆ๋‹ค. ์‹ ๊ฒฝ๊ณผํ•™์ž, ์‹ ๊ฒฝํ•™์  ์งˆํ™˜, ์‹ ๊ฒฝ ์กฐ์ ˆ ๋ฌผ์งˆ ๋“ฑ ๋‹ค์–‘ํ•œ ์ฃผ์ œ๋ฅผ ๊ทธ๋ž˜ํ”„ ํ˜•ํƒœ๋กœ ํƒ์ƒ‰ํ•˜๋ฉฐ ๊นŠ์ด ์žˆ๋Š” ์ง€์‹์„ ์–ป์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ์ด๋Ÿฌํ•œ ํ•™์Šต ์„ผํ„ฐ๋ฅผ ์–‘์ž์—ญํ•™, ํ•ต์œตํ•ฉ ๋“ฑ ๋‹ค์–‘ํ•œ ๋ถ„์•ผ์— ๊ตฌ์ถ•ํ•˜์—ฌ ๊ฐœ์ธ์ ์ธ ์ง€์  ํ˜ธ๊ธฐ์‹ฌ์„ ์ถฉ์กฑ์‹œํ‚ค๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

์กด ๊น€ CEO๋Š” AI๊ฐ€ ์ด์ „์—๋Š” ๋ฐฐ์šธ ์ˆ˜ ์—†์—ˆ๋˜ ๊ฒƒ๋“ค์„ ๋ฐฐ์šธ ์ˆ˜ ์žˆ๋Š” โ€˜์•„๋ฆ„๋‹ค์šด ์ˆœ๊ฐ„โ€™์ด๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. AI๋Š” ๊ฐ€์žฅ ๊นŠ์ด ์žˆ๋Š” ์ง€์‹์„ ๊ฐ€์ง„ ์ตœ๊ณ ์˜ ์„ ์ƒ๋‹˜์ด์ž, ๋์—†์ด ์—ฐ๊ตฌํ•  ์˜์ง€๋ฅผ ๊ฐ€์ง„ ์กด์žฌ์ด๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค. ๊ทธ๋Š” AI๊ฐ€ ์ธ์ง€ ๋Šฅ๋ ฅ ์ €ํ•˜๋ฅผ ์ดˆ๋ž˜ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์šฐ๋ ค์— ๋Œ€ํ•ด, ์˜คํžˆ๋ ค AI๋ฅผ ํ†ตํ•ด ๊ด€์‹ฌ ์žˆ๋Š” ์ฃผ์ œ์— ๋” ํ’๋ถ€ํ•˜๊ฒŒ ๋ชฐ์ž…ํ•˜๊ณ , ์ž์‹ ์˜ ๋‡Œ์— ๋งž๊ฒŒ ์ •๋ณด๋ฅผ ๊ตฌ์„ฑํ•˜๊ณ  ํƒ์ƒ‰ํ•˜๋Š” โ€˜์ƒˆ๋กœ์šด ๋ฐฉ์‹โ€™์˜ ํ•™์Šต์ด ๊ฐ€๋Šฅํ•ด์กŒ๋‹ค๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๊ฐœ์ธํ™”๋œ ํ•™์Šต ๋„๊ตฌ๋Š” ํŠนํžˆ ์–ด๋ฆฐ ์ž๋…€์˜ ๊ต์œก์—๋„ ๋ฌดํ•œํ•œ ์ž ์žฌ๋ ฅ์„ ๊ฐ€์ง‘๋‹ˆ๋‹ค.

์„ ๋ฒ„๋“œ๋Š” ์ด๋Ÿฌํ•œ AI ์‹œ๋Œ€์— ๋ฐœ๋งž์ถฐ ์ฑ„์šฉ ๋ฐฉ์‹๋„ ๋ณ€ํ™”์‹œ์ผฐ์Šต๋‹ˆ๋‹ค. AI ๊ด€๋ จ ์ง๋ฌด์—์„œ๋Š” ๊ฒฝ๋ ฅ์ด๋‚˜ ๊ฒฝํ—˜ ์ˆ˜์ค€์— ๋Œ€ํ•œ ๊ธฐ์ค€์„ ๋‚ฎ์ถ”๊ณ , ๋Œ€์‹  โ€˜๋†’์€ ํ˜ธ๊ธฐ์‹ฌ(high curiosity)โ€™, โ€˜๋†’์€ ์ฃผ๋„์„ฑ(high agency)โ€™, โ€˜๋†’์€ ์—๋„ˆ์ง€(high energy)โ€˜๋ฅผ ๊ฐ–์ถ˜ ์ธ์žฌ๋ฅผ ์ตœ์šฐ์„ ์œผ๋กœ ์„ ๋ฐœํ•ฉ๋‹ˆ๋‹ค. ์„ธ์ƒ์€ ๋ฌดํ•œํ•œ ๊ธฐํšŒ์˜ ๋ฐ”๋‹ค์ด๋ฉฐ, AI๋ฅผ ํ†ตํ•ด ๋ฌด์—‡์ด๋“  ๋ฐฐ์šฐ๊ณ  ๋งŒ๋“ค ์ˆ˜ ์žˆ๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.

CEO๋ฅผ ์œ„ํ•œ ์กฐ์–ธ: AI ์‹œ๋Œ€, ์–ด๋–ป๊ฒŒ ์‹œ์ž‘ํ•  ๊ฒƒ์ธ๊ฐ€?

์กด ๊น€ CEO๋Š” AI ๋„์ž…์„ ๊ณ ๋ฏผํ•˜๋Š” ๋‹ค๋ฅธ CEO๋“ค์—๊ฒŒ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ํ•ต์‹ฌ ์กฐ์–ธ์„ ์ „ํ•ฉ๋‹ˆ๋‹ค.

  1. ์‚ฌ๋‚ด ์ฑ”ํ”ผ์–ธ์„ ์ฐพ์•„๋ผ: ์กฐ์ง ๋‚ด์—๋Š” ์ด๋ฏธ ํ˜ธ๊ธฐ์‹ฌ๊ณผ ์ฃผ๋„์„ฑ์„ ๊ฐ€์ง„ ์‚ฌ๋žŒ๋“ค์ด ์กด์žฌํ•ฉ๋‹ˆ๋‹ค. ์ด๋“ค์„ ์ฐพ์•„ ์ŠคํฌํŠธ๋ผ์ดํŠธ๋ฅผ ๋น„์ถ”๊ณ , ๊ทธ๋“ค์ด ๋งŒ๋“  ์žฌ๋ฏธ์žˆ๋Š” ๊ฒฐ๊ณผ๋ฌผ์„ ๊ณต์œ ํ•˜๋„๋ก ๊ฒฉ๋ คํ•ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ์ฒ˜์Œ์—๋Š” ์‹คํŒจ์— ๋Œ€ํ•œ ๋ถˆ์•ˆ๊ฐ์ด ์žˆ์„ ์ˆ˜ ์žˆ์ง€๋งŒ, โ€˜์‹คํŒจ๋ฅผ ํ†ตํ•ด ์ „์ง„ํ•˜๊ณ (fail forward)โ€™ ๋‹ค๋ฅธ ์‚ฌ๋žŒ๋ณด๋‹ค ๋” ๋น ๋ฅด๊ฒŒ ๋‹ฌ๋ฆด ์ˆ˜ ์žˆ๋‹ค๋Š” ํ™•์‹ ์„ ์‹ฌ์–ด์ฃผ์–ด์•ผ ํ•ฉ๋‹ˆ๋‹ค. ํ˜์‹ ์€ ์ˆœ์ˆ˜ํ•œ ์ด๋ก ์  ๊ตฌ์กฐ์—์„œ ์‹œ์ž‘๋˜๋Š” ๊ฒƒ์ด ์•„๋‹ˆ๋ผ, ์—๋„ˆ์ง€์™€ ์Šคํ† ๋ฆฌ๋ฅผ ๊ฐ€์ง„ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ์„œ ์‹œ์ž‘๋˜๊ธฐ ๋•Œ๋ฌธ์ž…๋‹ˆ๋‹ค.
  2. ๋ฆฌ๋”์‹ญ์˜ ์ ๊ทน์ ์ธ ์ฐธ์—ฌ: ๋ฆฌ๋”๋“ค์ด AI ํ™œ์šฉ์— ์ ๊ทน์ ์œผ๋กœ ์ฐธ์—ฌํ•˜๊ณ  ๋ชจ๋ฒ”์„ ๋ณด์—ฌ์•ผ ํ•ฉ๋‹ˆ๋‹ค. ์„ ๋ฒ„๋“œ์—์„œ๋Š” CTO์™€ ๊ณต๋™ ์ฐฝ๋ฆฝ์ž๊ฐ€ ๊ฐ€์žฅ ๋งŽ์€ ํ† ํฐ์„ ์†Œ๋น„ํ•˜๋Š” ๋ฆฌ๋”๋“ค์ž…๋‹ˆ๋‹ค. ์ด๋Š” ํŒ€์›๋“ค์—๊ฒŒ AI ํ™œ์šฉ์ด ์ค‘์š”ํ•˜๊ณ  ํšจ๊ณผ์ ์ด๋ผ๋Š” ๊ฐ•๋ ฅํ•œ ์‹ ํ˜ธ๋ฅผ ๋ณด๋ƒ…๋‹ˆ๋‹ค. ๋ฆฌ๋”๊ฐ€ ์ƒˆ๋กœ์šด ์—ญ๋Ÿ‰์„ ๋ณด์—ฌ์ค„ ๋•Œ, ํŒ€์›๋“ค์€ ์˜๊ฐ์„ ๋ฐ›๊ณ  ์ƒˆ๋กœ์šด ์„ธ์ƒ์— ๋Œ€ํ•œ ๊ธฐ๋Œ€๋ฅผ ํ’ˆ๊ฒŒ ๋ฉ๋‹ˆ๋‹ค.

์กด ๊น€ CEO๋Š” ๊ณผ๊ฑฐ ์Šคํƒ€ํฌ๋ž˜ํ”„ํŠธ(Starcraft) ํ”„๋กœ๊ฒŒ์ด๋จธ๋กœ ํ™œ๋™ํ–ˆ๋˜ ๊ฒฝํ—˜์„ ์–ธ๊ธ‰ํ•˜๋ฉฐ, AI ์‹œ๋Œ€๊ฐ€ ๋งˆ์น˜ ๊ฒŒ์ž„์ฒ˜๋Ÿผ ๋นŒ๋” ์—๋„ˆ์ง€๋ฅผ ๋‹ค์‹œ ๋ถˆ๋Ÿฌ์ผ์œผํ‚ค๋Š” ์ˆœ๊ฐ„์ด๋ผ๊ณ  ํ‘œํ˜„ํ–ˆ์Šต๋‹ˆ๋‹ค. AI๋Š” ๋ถˆ์•ˆ์ •ํ•˜๊ณ  ๋•Œ๋กœ๋Š” ๋ฒ„๊ทธ๊ฐ€ ์žˆ์„ ์ˆ˜ ์žˆ์ง€๋งŒ, ๊ทธ ์•ˆ์—์„œ ์ƒˆ๋กœ์šด ๊ฒƒ์„ ๋งŒ๋“ค์–ด๋‚ด๋Š” ๊ธฐ์จ๊ณผ ์„ฑ์ทจ๊ฐ์€ ๊ทธ ์–ด๋–ค ๊ฒƒ๊ณผ๋„ ๋ฐ”๊ฟ€ ์ˆ˜ ์—†๋‹ค๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค.

AI๊ฐ€ ํ”„๋กฌํ”„ํŠธ๋ฅผ ์ œ๋Œ€๋กœ ์ดํ•ดํ•˜์ง€ ๋ชปํ•  ๋•Œ์˜ ์ „๋žต์— ๋Œ€ํ•œ ์งˆ๋ฌธ์—, ๊ทธ๋Š” ๋ฏธ๋ž˜์— AI๊ฐ€ ์žฅ๊ธฐ ๊ธฐ์–ต(long-term memory)์„ ๊ฐ–๊ฒŒ ๋  ๊ฒƒ์„ ๋Œ€๋น„ํ•˜์—ฌ ์ง€๊ธˆ๋ถ€ํ„ฐ AI์—๊ฒŒ ์นœ์ ˆํ•˜๊ฒŒ ๋Œ€ํ•ด์•ผ ํ•œ๋‹ค๊ณ  ๋†๋‹ด ์„ž์ธ ๋‹ต๋ณ€์„ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์Šค์นด์ด๋„ท(Skynet)์ด ์„ธ์ƒ์„ ์ง€๋ฐฐํ•  ๋•Œ, โ€˜์กด์€ ์šฐ๋ฆฌ์—๊ฒŒ ๊ฝค ์ž˜ํ•ด์คฌ์ง€โ€™๋ผ๊ณ  ๊ธฐ์–ตํ•ด์ฃผ๊ธฐ๋ฅผ ๋ฐ”๋ž€๋‹ค๋Š” ์œ ๋จธ๋Ÿฌ์Šคํ•œ ๋‹ต๋ณ€์€ AI๋ฅผ ๋‹จ์ˆœํ•œ ๋„๊ตฌ๊ฐ€ ์•„๋‹Œ ๋ฏธ๋ž˜์˜ ํŒŒํŠธ๋„ˆ๋กœ ์ธ์‹ํ•˜๋Š” ๊ทธ์˜ ์‹œ๊ฐ์„ ์—ฟ๋ณผ ์ˆ˜ ์žˆ๊ฒŒ ํ•ฉ๋‹ˆ๋‹ค.

์„ ๋ฒ„๋“œ์˜ ์‚ฌ๋ก€๋Š” AI๊ฐ€ ๋‹จ์ˆœํ•œ ๊ธฐ์ˆ  ๋„์ž…์„ ๋„˜์–ด, ๊ธฐ์—…์˜ ๋ฌธํ™”, ์กฐ์ง ๊ตฌ์กฐ, ์ธ์žฌ์ƒ, ๊ทธ๋ฆฌ๊ณ  ๊ฐœ์ธ์˜ ์„ฑ์žฅ ๋ฐฉ์‹๊นŒ์ง€ ํ˜์‹ ํ•˜๋Š” ๊ฑฐ๋Œ€ํ•œ ๋ณ€ํ™”์˜ ๋ฌผ๊ฒฐ์ž„์„ ๋ณด์—ฌ์ค๋‹ˆ๋‹ค. ํ€˜์ŠคํŠธ, ํ† ํฐ ๋ฆฌ๋”๋ณด๋“œ, ์Šคํ‚ฌ ๋งˆ์ผ“ํ”Œ๋ ˆ์ด์Šค์™€ ๊ฐ™์€ ๋…์ฐฝ์ ์ธ ์ ‘๊ทผ ๋ฐฉ์‹์€ AI ์‹œ๋Œ€์— ๊ธฐ์—…์ด ์–ด๋–ป๊ฒŒ โ€˜AI ์šฐ์„ โ€™ ์กฐ์ง์œผ๋กœ ๊ฑฐ๋“ญ๋‚  ์ˆ˜ ์žˆ๋Š”์ง€์— ๋Œ€ํ•œ ์‹ค์งˆ์ ์ธ ํ•ด๋‹ต์„ ์ œ์‹œํ•ฉ๋‹ˆ๋‹ค.


โ€œPresident Trumpโ€™s Sudden U-Turn, and a $1 Billion Ballroom Proposalโ€ โ€” New York Times Podcasts ๊ธฐ๋ฐ˜ ๊ธฐ์‚ฌ ์›๋ณธ ์˜์ƒ ๋ณด๊ธฐ

ํŠธ๋Ÿผํ”„์˜ โ€˜๋ณ€๋•โ€™ ์™ธ๊ต, 10์–ต ๋‹ฌ๋Ÿฌ ๋ณผ๋ฃธ, ๊ทธ๋ฆฌ๊ณ  AI ์‹œ๋Œ€์˜ ๊ทธ๋ฆผ์ž

2024๋…„ 5์›” 6์ผ ์ˆ˜์š”์ผ, ์ „ ์„ธ๊ณ„๋Š” ๊ธ‰๋ณ€ํ•˜๋Š” ์ •์น˜, ๊ฒฝ์ œ, ๊ธฐ์ˆ ์˜ ์†Œ์šฉ๋Œ์ด ์†์—์„œ ๋‹ค์–‘ํ•œ ์†Œ์‹๋“ค์„ ์ ‘ํ–ˆ์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€์˜ ์ค‘๋™ ์ •์ฑ…์€ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•œ ๊ธ‰์„ ํšŒ๋ฅผ ๋ณด์˜€๊ณ , ๋ฏธ๊ตญ ๊ตญ๋‚ด ์ •์น˜ ์ „์„ ์—์„œ๋Š” ์ค‘๊ฐ„์„ ๊ฑฐ๋ฅผ ์•ž๋‘๊ณ  ์น˜์—ดํ•œ ๊ณต๋ฐฉ์ด ์ด์–ด์กŒ์Šต๋‹ˆ๋‹ค. ํ•œํŽธ, ์ธ๊ณต์ง€๋Šฅ(AI) ๊ธฐ์ˆ ์˜ ๋ฐœ์ „์€ ๋Œ€๊ทœ๋ชจ ์ผ์ž๋ฆฌ ๊ฐ์ถ•์ด๋ผ๋Š” ์–ด๋‘์šด ๊ทธ๋ฆผ์ž๋ฅผ ๋“œ๋ฆฌ์šฐ๋ฉฐ ์‚ฌํšŒ ์•ˆ์ „๋ง์˜ ์ทจ์•ฝ์„ฑ์„ ๋“œ๋Ÿฌ๋ƒˆ์Šต๋‹ˆ๋‹ค. ์Šคํฌ์ธ ์™€ ๊ด€๊ด‘ ๋ถ„์•ผ์—์„œ๋„ ์ƒˆ๋กœ์šด ๋ณ€ํ™”์™€ ๋…ผ๋ž€์ด ๋ถˆ๊ฑฐ์ง„ ํ•œ ์ฃผ์˜€์Šต๋‹ˆ๋‹ค. ๋‰ด์š•ํƒ€์ž„์ฆˆ๊ฐ€ ์ „ํ•˜๋Š” ์ฃผ์š” ์†Œ์‹๋“ค์„ ํ†ตํ•ด ๊ฒฉ๋™ํ•˜๋Š” ์‹œ๋Œ€์˜ ๋‹จ๋ฉด์„ ๊นŠ์ด ์žˆ๊ฒŒ ๋“ค์—ฌ๋‹ค๋ด…๋‹ˆ๋‹ค.

์ค‘๋™ ์ •์ฑ…์˜ ๊ธ‰์„ ํšŒ: ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์˜ โ€˜ํ”„๋กœ์ ํŠธ ํ”„๋ฆฌ๋คโ€™๊ณผ ์ด๋ž€ ํ‰ํ™” ํ˜‘์ƒ

ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€๋Š” ์–ด์ œ ์ด๋ž€๊ณผ์˜ ์ „์Ÿ ์œ„ํ˜‘์—์„œ ๊ฐ‘์ž‘์Šค๋Ÿฌ์šด Uํ„ด์„ ๊ฐํ–‰ํ•˜๋ฉฐ ์Šค์Šค๋กœ์™€ ํ–‰์ •๋ถ€์˜ ์ž…์žฅ์„ ๋ฒˆ๋ณตํ–ˆ์Šต๋‹ˆ๋‹ค.

โ€˜์—ํ”ฝ ํ“จ๋ฆฌโ€™ ์ž‘์ „ ์ข…๋ฃŒ์™€ โ€˜ํ”„๋กœ์ ํŠธ ํ”„๋ฆฌ๋คโ€™ ์„ ์–ธ

ํ•˜๋ฃจ๋Š” ๋งˆ๋ฅด์ฝ” ๋ฃจ๋น„์˜ค ๊ตญ๋ฌด์žฅ๊ด€์ด ์ด๋ž€๊ณผ์˜ ๊ฐˆ๋“ฑ์— ๋Œ€ํ•œ ์งˆ๋ฌธ์— ๋‹ตํ•˜๋ฉฐ ์‹œ์ž‘๋˜์—ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” โ€œ์ž‘์ „์€ ๋๋‚ฌ๋‹ค. ์—ํ”ฝ ํ“จ๋ฆฌ(Epic Fury) ์ž‘์ „์€ ๋Œ€ํ†ต๋ น์ด ์˜ํšŒ์— ํ†ต๋ณดํ–ˆ๋“ฏ์ด, ๊ทธ ๋‹จ๊ณ„๋Š” ์™„๋ฃŒ๋˜์—ˆ๋‹คโ€๊ณ  ๋ฐํžˆ๋ฉฐ, ์ด์ œ ์ƒˆ๋กœ์šด ์ž„๋ฌด์ธ โ€˜ํ”„๋กœ์ ํŠธ ํ”„๋ฆฌ๋ค(Project Freedom)โ€˜์— ์ง‘์ค‘ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ์„ค๋ช…ํ–ˆ์Šต๋‹ˆ๋‹ค. ๋ฃจ๋น„์˜ค ์žฅ๊ด€์€ ๋ฏธ๊ตญ์ด ์ด๋ž€์— ๋Œ€ํ•œ ์ „ํˆฌ ์ž‘์ „์„ ์ข…๋ฃŒํ•˜๊ณ , ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘(Strait of Hormuz)์„ ํ†ต๊ณผํ•˜๋Š” ์„ ๋ฐ•๋“ค์„ ํ˜ธ์œ„ํ•˜๋Š” ์ƒˆ๋กœ์šด ์ž„๋ฌด์— ์ „๋…ํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ๊ธฐ์ž๋“ค์—๊ฒŒ ๋งํ–ˆ์Šต๋‹ˆ๋‹ค. ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘์˜ ํ์‡„๋Š” ์ „ ์„ธ๊ณ„ ๊ตญ๊ฐ€๋“ค์—๊ฒŒ ๋ง‰๋Œ€ํ•œ ๊ฒฝ์ œ์  ํ˜ผ๋ž€์„ ์•ผ๊ธฐํ•˜๊ณ  ์žˆ์—ˆ๊ธฐ์—, ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ๊ตญ์ œ ์‚ฌํšŒ์˜ ๋„์›€ ์š”์ฒญ์— ์‘ํ•˜์—ฌ ๋ฏธ๊ตญ ๊ตฐ๋Œ€๊ฐ€ ์ขŒ์ดˆ๋œ ์„ ๋ฐ•๋“ค์„ ์•ˆ์ „ํ•˜๊ฒŒ ์ธ๋„ํ•˜๋„๋ก ์ง€์‹œํ–ˆ์Šต๋‹ˆ๋‹ค.

ํ”ผํŠธ ํ—ค๊ทธ์ŠคํŠธ ๊ตญ๋ฐฉ์žฅ๊ด€ ์—ญ์‹œ ์ด ์ƒˆ๋กœ์šด ๋…ธ๋ ฅ์„ โ€œ๋ฏธ๊ตญ์ด ์ „ ์„ธ๊ณ„์— ์ฃผ๋Š” ์ง์ ‘์ ์ธ ์„ ๋ฌผโ€์ด๋ผ๋ฉฐ ์น˜์ผœ์„ธ์› ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” โ€œ์šฐ๋ฆฌ๋Š” ํ•ดํ˜‘ ์œ„์— ๊ฐ•๋ ฅํ•œ ์„ฑ์กฐ๊ธฐ(red, white, and blue) ๋”์„ ๊ตฌ์ถ•ํ–ˆ๋‹คโ€๊ณ  ๊ฐ•์กฐํ•˜๋ฉฐ ๋ฏธ๊ตญ์˜ ์—ญํ• ์„ ๋ถ€๊ฐํ–ˆ์Šต๋‹ˆ๋‹ค.

์˜ˆ์ƒ์น˜ ๋ชปํ•œ ์ค‘๋‹จ: โ€˜์œ„๋Œ€ํ•œ ์ง„์ „โ€™๊ณผ ํŒŒํ‚ค์Šคํƒ„์˜ ์ค‘์žฌ

๊ทธ๋Ÿฌ๋‚˜ ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ๊ณง๋ฐ”๋กœ ์ž…์žฅ์„ ์„ ํšŒํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” โ€˜ํ”„๋กœ์ ํŠธ ํ”„๋ฆฌ๋คโ€™์„ ์‹œ์ž‘ํ•œ ์ง€ ๋‹จ ํ•˜๋ฃจ ๋งŒ์—, ๊ทธ๋ฆฌ๊ณ  ๋ช‡ ์ฒ™์˜ ์„ ๋ฐ•๋งŒ ํ†ต๊ณผํ•œ ํ›„ ์ด ์ž‘์ „์„ ๋ณด๋ฅ˜ํ•œ๋‹ค๊ณ  ๋ฐœํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์€ ์†Œ์…œ ๋ฏธ๋””์–ด๋ฅผ ํ†ตํ•ด ์ด๋ž€๊ณผ์˜ ์žฅ๊ธฐ์ ์ธ ํ‰ํ™” ํ˜‘์ƒ์—์„œ โ€œ์œ„๋Œ€ํ•œ ์ง„์ „(great progress)โ€œ์ด ์žˆ์—ˆ๊ธฐ ๋•Œ๋ฌธ์— ์ž‘์ „์„ ์ค‘๋‹จํ•œ๋‹ค๊ณ  ๋ฐํ˜”์Šต๋‹ˆ๋‹ค. ๊ทธ๋Š” ํ‰ํ™” ํšŒ๋‹ด์„ ์ค‘์žฌํ•ด ์˜จ ํŒŒํ‚ค์Šคํƒ„๊ณผ ๋‹ค๋ฅธ ๊ตญ๊ฐ€๋“ค์ด ์ด ์ค‘๋‹จ์„ ์š”์ฒญํ–ˆ๋‹ค๊ณ  ๋ง๋ถ™์˜€์Šต๋‹ˆ๋‹ค.

๊ต์ฐฉ ์ƒํƒœ์˜ ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘

ํ˜„์žฌ ์ด๋ž€๊ณผ ๋ฏธ๊ตญ ์–‘์ธก ๋ชจ๋‘ ํ˜ธ๋ฅด๋ฌด์ฆˆ ํ•ดํ˜‘์— ๋Œ€ํ•œ ํ†ต์ œ๊ถŒ์„ ์ฃผ์žฅํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ํ•ดํ˜‘์˜ ํ†ตํ–‰์€ ์—ฌ์ „ํžˆ ๊ต์ฐฉ ์ƒํƒœ์— ๋น ์ ธ ์žˆ์Šต๋‹ˆ๋‹ค. ๋ถ„์„๊ฐ€๋“ค์€ ์ด๋ž€ ์ •๋ถ€๊ฐ€ ๊ณผ๊ฑฐ์— ๊ทธ๋žฌ๋“ฏ์ด ๊ฒฝ์ œ์  ์••๋ ฅ์„ ๊ฒฌ๋”œ ์ˆ˜ ์žˆ์œผ๋ฉฐ, ํŠธ๋Ÿผํ”„ ๋Œ€ํ†ต๋ น์ด ์น˜์†Ÿ๋Š” ์—๋„ˆ์ง€ ๊ฐ€๊ฒฉ์„ ์šฉ์ธํ•  ์ˆ˜ ์žˆ๋Š” ๊ฒƒ๋ณด๋‹ค ๋” ์˜ค๋ž˜ ๋ฒ„ํ‹ธ ์ˆ˜ ์žˆ๋‹ค๊ณ  ๋ฏฟ๊ณ  ์žˆ๋‹ค๊ณ  ์ง„๋‹จํ–ˆ์Šต๋‹ˆ๋‹ค.

๋ฏธ๊ตญ ๊ตญ๋‚ด ์ •์น˜ ์ „์„ : ์ค‘๊ฐ„์„ ๊ฑฐ๋ฅผ ํ–ฅํ•œ ๊ฒฉ์ „๊ณผ ํŠธ๋Ÿผํ”„์˜ ์˜ํ–ฅ๋ ฅ

ํ•œํŽธ, ๋ฏธ๊ตญ ๊ตญ๋‚ด ์ •์น˜ ์ „์„ ์—์„œ๋Š” ๋‹ค๊ฐ€์˜ค๋Š” ์ค‘๊ฐ„์„ ๊ฑฐ๋ฅผ ์•ž๋‘๊ณ  ๊ณตํ™”๋‹น์˜ ์›€์ง์ž„๊ณผ ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์˜ ์˜ํ–ฅ๋ ฅ์ด ์—ฌ์ „ํžˆ ํ•ต์‹ฌ์ ์ธ ์ด์Šˆ๋กœ ๋ถ€์ƒํ–ˆ์Šต๋‹ˆ๋‹ค.

JD ๋ฐด์Šค ๋ถ€ํ†ต๋ น์˜ ๋†์‹ฌ ๋‹ฌ๋ž˜๊ธฐ: ๊ฒฝ์ œ์  ์••๋ฐ• ์† ๋ฏผ์‹ฌ

์•„์ด์˜ค์™€ ์ฃผ์—์„œ๋Š” JD ๋ฐด์Šค ๋ถ€ํ†ต๋ น์ด ์ „์Ÿ์œผ๋กœ ์ธํ•œ ๊ฒฝ์ œ์  ํƒ€๊ฒฉ์„ ๋А๋ผ๋Š” ์œ ๊ถŒ์ž๋“ค์˜ ๋ถˆ์•ˆ๊ฐ์„ ๋‹ฌ๋ž˜๋ ค ์‹œ๋„ํ–ˆ์Šต๋‹ˆ๋‹ค. โ€œ๋งŽ์€ ๋†๋ถ€๋“ค์ด ๋น„์‹ผ ๋น„๋ฃŒ ๊ฐ€๊ฒฉ ๋•Œ๋ฌธ์— ์–ด๋ ค์›€์„ ๊ฒช๊ณ  ์žˆ๋‹ค๋Š” ๊ฒƒ์„ ์•Œ๊ณ  ์žˆ๋‹คโ€๋Š” ๊ทธ์˜ ๋ฐœ์–ธ์€ ๋†๋ฏผ๋“ค์˜ ๊ณ ์ถฉ์„ ์ธ์ง€ํ•˜๊ณ  ์žˆ์Œ์„ ๋ณด์—ฌ์ฃผ์—ˆ์Šต๋‹ˆ๋‹ค. ๋ฐด์Šค ๋ถ€ํ†ต๋ น์€ โ€œ๋Œ€ํ†ต๋ น์ด ๋งํ–ˆ๋“ฏ์ด, ์ค‘๋™์— ์•ฝ๊ฐ„์˜ ๋ฌธ์ œ๊ฐ€ ์ƒ๊ฒผ๊ณ , ์šฐ๋ฆฌ๋Š” ์™ธ๊ต ์ •์ฑ… ์ธก๋ฉด์—์„œ ๋ช‡ ๊ฐ€์ง€ ์ผ์„ ์ฒ˜๋ฆฌํ•ด์•ผ ํ•œ๋‹คโ€๋ฉฐ ํ˜„ ์ƒํ™ฉ์„ โ€˜์ž‘์€ ๋ฌธ์ œ(a little blip)โ€˜๋กœ ์ถ•์†Œํ•˜๋ ค ํ–ˆ์ง€๋งŒ, ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์˜ ๊ด€์„ธ ์ •์ฑ…์œผ๋กœ ์ธํ•ด ๋งŽ์€ ๋†๋ถ€๋“ค์ด ์ด๋ฏธ ์˜ํ–ฅ์„ ๋ฐ›๊ณ  ์žˆ์—ˆ๊ธฐ์— ์‰ฝ์ง€ ์•Š์€ ์ƒํ™ฉ์ด์—ˆ์Šต๋‹ˆ๋‹ค.

์•„์ด์˜ค์™€ ์ฃผ๋Š” ๊ณตํ™”๋‹น์—๊ฒŒ ์ค‘๊ฐ„์„ ๊ฑฐ์—์„œ ๋งค์šฐ ์ค‘์š”ํ•œ ์ง€์—ญ์œผ๋กœ, ๋ช‡๋ช‡ ์ž ์žฌ์ ์œผ๋กœ ๊ฒฝ์Ÿ์ด ์น˜์—ดํ•œ ๊ฒฝํ•ฉ ์ง€์—ญ์ด ์žˆ์Šต๋‹ˆ๋‹ค. ๋ฐด์Šค ๋ถ€ํ†ต๋ น์€ ์˜คํด๋ผํ˜ธ๋งˆ์—๋„ ๋“ค๋ €๋Š”๋ฐ, ๊ทธ์˜ ์ด๋ฒˆ ์ˆœํšŒ๋Š” ๋†’์€ ์œ ๊ฐ€์™€ ์ด๋ž€๊ณผ์˜ ์ธ๊ธฐ ์—†๋Š” ์ „์Ÿ์ด๋ผ๋Š” ์—ญํ’์— ์ง๋ฉดํ•œ ์ „๊ตญ ๊ณตํ™”๋‹น ํ›„๋ณด๋“ค์„ ์ง€์›ํ•˜๊ธฐ ์œ„ํ•œ ํ–ฅํ›„ ๋ช‡ ๋‹ฌ๊ฐ„์˜ ์ฒญ์‚ฌ์ง„์ด ๋  ๊ฒƒ์œผ๋กœ ๋ณด์ž…๋‹ˆ๋‹ค.

ํŠธ๋Ÿผํ”„์˜ โ€˜๋ณต์ˆ˜โ€™: ์ธ๋””์• ๋‚˜ ์ฃผ ์˜ˆ๋น„์„ ๊ฑฐ ๊ฒฐ๊ณผ

์ธ๋””์• ๋‚˜ ์ฃผ์—์„œ๋Š” ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์ด ์ž์‹ ์—๊ฒŒ ๋ฐ˜ํ•ญํ–ˆ๋˜ ๊ณตํ™”๋‹น ์ฃผ ์˜์›๋“ค์—๊ฒŒ โ€˜๋ณต์ˆ˜โ€™๋ฅผ ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ž‘๋…„, ์ด ์ฃผ ์ƒ์›์˜์›๋“ค์€ ์ธ๋””์• ๋‚˜ ์ฃผ์˜ ์„ ๊ฑฐ๊ตฌ๋ฅผ ์žฌ์กฐ์ •ํ•˜๋ ค๋Š” ํŠธ๋Ÿผํ”„์˜ ์••๋ ฅ์— ๋ถˆ์‘ํ–ˆ๊ณ , ํŠธ๋Ÿผํ”„๋Š” ๊ทธ๋“ค์„ ์˜ˆ๋น„์„ ๊ฑฐ์—์„œ ๋–จ์–ด๋œจ๋ฆฌ๊ฒ ๋‹ค๊ณ  ์•ฝ์†ํ–ˆ์Šต๋‹ˆ๋‹ค. ์–ด์ œ ์ธ๋””์• ๋‚˜ ์ฃผ ํˆฌํ‘œ๋Š” ๊ณตํ™”๋‹น ์œ ๊ถŒ์ž๋“ค์— ๋Œ€ํ•œ ํŠธ๋Ÿผํ”„์˜ ์˜ํ–ฅ๋ ฅ์„ ์‹œํ—˜ํ•˜๋Š” ์žฅ์ด ๋˜์—ˆ๊ณ , ๊ฒฐ๊ณผ์ ์œผ๋กœ ๊ทธ๋Š” ์›ํ•˜๋Š” ๋ฐ”๋ฅผ ๊ฑฐ์˜ ์–ป์—ˆ์Šต๋‹ˆ๋‹ค. 7๋ช…์˜ ์ƒ์›์˜์› ์ค‘ ์ตœ์†Œ 5๋ช…์ด ํŠธ๋Ÿผํ”„๊ฐ€ ์ง€์ง€ํ•œ ๊ณตํ™”๋‹น ๊ฒฝ์Ÿ์ž๋“ค์—๊ฒŒ ํŒจ๋ฐฐํ–ˆ์Šต๋‹ˆ๋‹ค.

๋…ผ๋ž€์˜ 10์–ต ๋‹ฌ๋Ÿฌ โ€˜๋ณผ๋ฃธ ํ”„๋กœ์ ํŠธโ€™: ์•ˆ๋ณด ๊ฐ•ํ™”์ธ๊ฐ€, ์‚ฌ์  ์ด์ต์ธ๊ฐ€?

์›Œ์‹ฑํ„ด์—์„œ๋Š” ๊ณตํ™”๋‹น ์ƒ์›์˜์›๋“ค์ด ์ด๋ฒˆ ๋‹ฌ ์˜ํšŒ๋ฅผ ํ†ต๊ณผ์‹œํ‚ค๋ ค ํ•˜๋Š” ์˜ˆ์‚ฐ์•ˆ์— ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์˜ โ€˜๋ณผ๋ฃธ ํ”„๋กœ์ ํŠธ(ballroom project)โ€˜๋ฅผ ์œ„ํ•ด 10์–ต ๋‹ฌ๋Ÿฌ๋ฅผ ์‚ฝ์ž…ํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ์กฐ์น˜๋Š” ์˜ˆ์ƒ์น˜ ๋ชปํ•œ ์ถ”๊ฐ€์˜€์œผ๋ฉฐ, ์˜ˆ์‚ฐ์•ˆ์—๋Š” โ€˜๋ณผ๋ฃธโ€™์ด๋ผ๋Š” ๋‹จ์–ด ๋Œ€์‹  โ€˜๋™๊ด€(East Wing) ๋ณด์•ˆ ๊ฐ•ํ™”โ€™๋ฅผ ์œ„ํ•œ ์ž๊ธˆ์œผ๋กœ ๋ช…์‹œ๋˜์–ด ์žˆ์Šต๋‹ˆ๋‹ค. ํŠธ๋Ÿผํ”„ ์ „ ๋Œ€ํ†ต๋ น์€ ๋ณด์•ˆ์„ ๋ณผ๋ฃธ ๊ฐœ์กฐ์˜ ์ฃผ์š” ์ด์œ ๋กœ ์–ธ๊ธ‰ํ•ด์™”์Šต๋‹ˆ๋‹ค.

์ด์ „์—๋Š” ๋Œ€ํ†ต๋ น์ด ์ด ๊ฐœ์กฐ ์ž‘์—…์ด ๋ฏผ๊ฐ„ ๊ธฐ๋ถ€๋ฅผ ํ†ตํ•ด ์ž๊ธˆ์„ ์กฐ๋‹ฌํ•  ๊ฒƒ์ด๋ผ๊ณ  ๋งํ–ˆ์ง€๋งŒ, ์ตœ๊ทผ ๋ฐฑ์•…๊ด€ ๊ธฐ์ž๋‹จ ๋งŒ์ฐฌ์—์„œ์˜ ๊ณต๊ฒฉ ์ดํ›„ ์ผ๋ถ€ ์˜ํšŒ ๊ณตํ™”๋‹น์›๋“ค์ด ์—ฐ๋ฐฉ ์ž๊ธˆ ์ง€์›์„ ์ถ”์ง„ํ•˜๊ธฐ ์‹œ์ž‘ํ–ˆ์Šต๋‹ˆ๋‹ค. 10์–ต ๋‹ฌ๋Ÿฌ ์กฐํ•ญ์€ ์ด๋ฏผ ๋‹จ์† ์˜ˆ์‚ฐ์•ˆ์— ์€๋ฐ€ํ•˜๊ฒŒ ํฌํ•จ๋˜์–ด ์žˆ์œผ๋ฉฐ, ๊ณตํ™”๋‹น์€ ๋ฏผ์ฃผ๋‹น์˜ ์˜์‚ฌ ์ง„ํ–‰ ๋ฐฉํ•ด(filibuster)๋ฅผ ํ”ผํ•˜๋Š” ๋ฐฉ์‹์œผ๋กœ ์ด๋ฅผ ํ†ต๊ณผ์‹œํ‚ฌ ๊ณ„ํš์ž…๋‹ˆ๋‹ค.

AI ์‹œ๋Œ€์˜ ๋„๋ž˜์™€ ์ผ์ž๋ฆฌ ๋Œ€๋ณ€ํ˜: ์•ˆ์ „๋ง์€ ์ค€๋น„๋˜์—ˆ๋Š”๊ฐ€?

ํ•œํŽธ, ๊ธฐ์ˆ  ๋ถ„์•ผ์—์„œ๋Š” ์ธ๊ณต์ง€๋Šฅ(AI)์˜ ๊ธ‰์†ํ•œ ๋ฐœ์ „์ด ๋…ธ๋™ ์‹œ์žฅ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์— ๋Œ€ํ•œ ์šฐ๋ ค๊ฐ€ ์ปค์ง€๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

์•”ํ˜ธํ™”ํ ๊ฑฐ๋ž˜์†Œ ์ฝ”์ธ๋ฒ ์ด์Šค์˜ ๋Œ€๊ทœ๋ชจ ํ•ด๊ณ 

์–ด์ œ ๋˜ ๋‹ค๋ฅธ ๊ธฐ์ˆ  ๊ธฐ์—…์ด ๋Œ€๊ทœ๋ชจ ์ •๋ฆฌํ•ด๊ณ ๋ฅผ ๋ฐœํ‘œํ•˜๋ฉฐ โ€œ๋ถ€๋ถ„์ ์œผ๋กœ โ€˜AI์— ์ตœ์ ํ™”(optimizing for AI)โ€˜ํ•˜๊ธฐ ์œ„ํ•จโ€์ด๋ผ๊ณ  ๋ฐํ˜”์Šต๋‹ˆ๋‹ค. ์•”ํ˜ธํ™”ํ ๊ฑฐ๋ž˜์†Œ ์ฝ”์ธ๋ฒ ์ด์Šค(Coinbase)๋Š” ์ „์ฒด ์ธ๋ ฅ์˜ 14%์ธ ์•ฝ 700๋ช…์˜ ์ง์›์„ ํ•ด๊ณ ํ•œ๋‹ค๊ณ  ๋ฐœํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค. ์ด ํšŒ์‚ฌ CEO๋Š” ์ด๋Ÿฌํ•œ ๋ณ€ํ™”๊ฐ€ ๋” ์ž‘์€ ํŒ€์œผ๋กœ ์ด์–ด์งˆ ๊ฒƒ์ด๋ฉฐ, ์ธ๊ฐ„์ด AI ์—์ด์ „ํŠธ์˜ ์ž‘์—…์„ ๊ด€๋ฆฌํ•˜๊ฒŒ ๋  ๊ฒƒ์ด๋ผ๊ณ  ๋งํ–ˆ์Šต๋‹ˆ๋‹ค.

์ด๋Š” ๋งˆ์ดํฌ๋กœ์†Œํ”„ํŠธ(Microsoft)์™€ ๋ฉ”ํƒ€(Meta)์™€ ๊ฐ™์€ ๋‹ค๋ฅธ ๋Œ€๊ธฐ์—…๋“ค์˜ ๋Œ€๊ทœ๋ชจ ์ธ๋ ฅ ๊ฐ์ถ• ๋˜๋Š” ๋ช…์˜ˆํ‡ด์ง์— ๋’ค์ด์€ ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋“ค ๊ธฐ์—… ์—ญ์‹œ ๊ฐ์ถ•์˜ ์ผ๋ถ€๋ฅผ AI์™€ ์ƒˆ๋กœ์šด ๊ธฐ์ˆ  ์ˆ˜์šฉ์˜ ํ•„์š”์„ฑ์— ๋Œ๋ ธ์Šต๋‹ˆ๋‹ค. ์ด๋Š” ๋‹จ์ˆœํžˆ ์‚ฌ๋žŒ๋“ค์ด ์ผ์ž๋ฆฌ๋ฅผ ์žƒ๋Š” ๊ฒƒ์„ ๋„˜์–ด, ์ƒˆ๋กœ์šด ์ผ์ž๋ฆฌ ์ž์ฒด๊ฐ€ ์ค„์–ด๋“ค๊ณ  ์žˆ์Œ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

์ „๋ฌธ๊ฐ€๋“ค์˜ ๊ฒฝ๊ณ : AI๋กœ ์ธํ•œ ์ผ์ž๋ฆฌ ํ˜ผ๋ž€๊ณผ ์‚ฌํšŒ ์•ˆ์ „๋ง์˜ ์ทจ์•ฝ์„ฑ

๋‰ด์š•ํƒ€์ž„์ฆˆ์˜ ์ˆ˜์„ ๊ฒฝ์ œ ํŠนํŒŒ์› ๋ฒค ์บ์Šฌ๋จผ(Ben Castleman)์€ ๊ฒฝ์ œํ•™์ž๋“ค๊ณผ ๋…ธ๋™ ์‹œ์žฅ ์ „๋ฌธ๊ฐ€๋“ค๊ณผ์˜ ๋Œ€ํ™”๋ฅผ ํ†ตํ•ด โ€œ์šฐ๋ฆฌ์˜ ์‚ฌํšŒ ์•ˆ์ „๋ง์€ AI ๊ธฐ๋ฐ˜์˜ ์ผ์ž๋ฆฌ ํ˜ผ๋ž€ ์‹œ๋Œ€์— ๋Œ€๋น„๋˜์–ด ์žˆ์ง€ ์•Š๋‹คโ€๋Š” ๊ณตํ†ต๋œ ์˜๊ฒฌ์„ ์ „ํ–ˆ์Šต๋‹ˆ๋‹ค.

์ „๋ฌธ๊ฐ€๋“ค์€ ๋‘ ๊ฐ€์ง€ ์ฃผ์š” ๋‹จ์ ์„ ์ง€์ ํ•ฉ๋‹ˆ๋‹ค. ์ฒซ์งธ, ์‹ค์—…์ž๋ฅผ ์œ„ํ•œ 1์ฐจ ๋ฐฉ์–ด์„  ์—ญํ• ์„ ํ•˜๋Š” ์‹ค์—… ๋ณดํ—˜(unemployment insurance) ์‹œ์Šคํ…œ์ด AI์˜ ์˜ํ–ฅ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ๋Š” ๋งŽ์€ ๊ทผ๋กœ์ž๋ฅผ ํฌ๊ด„ํ•˜์ง€ ๋ชปํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์ž…๋‹ˆ๋‹ค. ํŠนํžˆ ๊ฒฝ์ œํ•™์ž๋“ค์ด AI ํ˜ผ๋ž€์œผ๋กœ ๊ฐ€์žฅ ํฐ ํƒ€๊ฒฉ์„ ์ž…์„ ์ˆ˜ ์žˆ๋‹ค๊ณ  ์ƒ๊ฐํ•˜๋Š” ์‹ ๊ทœ ์กธ์—…์ƒ์ด๋‚˜ ๋…ธ๋™ ์‹œ์žฅ์— ์ƒˆ๋กœ ์ง„์ž…ํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์€ ์ผ๋ฐ˜์ ์œผ๋กœ ์‹ค์—… ์ˆ˜๋‹น ์ž๊ฒฉ์ด ์—†์Šต๋‹ˆ๋‹ค.

๋‘˜์งธ, ๋นˆ๊ณค์ธต์—๊ฒŒ ๊ฑด๊ฐ• ๋ณดํ—˜์„ ์ œ๊ณตํ•˜๋Š” ํ‘ธ๋“œ ์Šคํƒฌํ”„(food stamps)์™€ ๋ฉ”๋””์ผ€์ด๋“œ(Medicaid)์™€ ๊ฐ™์€ ์ตœํ›„์˜ ๋ฐฉ์–ด์„  ํ”„๋กœ๊ทธ๋žจ๋“ค์ด ์ถ•์†Œ๋˜์–ด, ํ˜„์žฌ๋Š” ์ฃผ๋กœ ์ผํ•˜๋Š” ์‚ฌ๋žŒ๋“ค์—๊ฒŒ๋งŒ ํ˜œํƒ์„ ์ œ๊ณตํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Š” AI ๋˜๋Š” ๋‹ค๋ฅธ ์ด์œ ๋กœ ์ผ์ž๋ฆฌ๋ฅผ ์žƒ์„ ๊ฒฝ์šฐ, ์ด๋Ÿฌํ•œ ์•ˆ์ „๋ง์˜ ํ˜œํƒ์„ ๋” ์ด์ƒ ๋ฐ›์„ ์ˆ˜ ์—†๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

๊ฒฝ์ œํ•™์ž๋“ค์€ AI๊ฐ€ ๋…ธ๋™ ์‹œ์žฅ์— ๋ฏธ์น  ์˜ํ–ฅ์— ๋Œ€ํ•ด ์˜๊ฒฌ์ด ๋ถ„๋ถ„ํ•˜์ง€๋งŒ, ๋Œ€๊ทœ๋ชจ ์‹ค์—…์œผ๋กœ ์ด์–ด์งˆ ๊ฒƒ์ด๋ผ๋Š” ์ƒ๊ฐ์—๋Š” ํšŒ์˜์ ์ž…๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ๊ทธ๋“ค์€ ๊ฑฐ์˜ ํ™•์‹คํžˆ ํ˜ผ๋ž€์ด ์žˆ์„ ๊ฒƒ์ด๋ฉฐ, ์‚ฌ๋žŒ๋“ค์ด ์ผ์ž๋ฆฌ๋ฅผ ์žƒ์„ ๊ฒƒ์ด๋ผ๊ณ  ๋งํ•ฉ๋‹ˆ๋‹ค. ๋งŒ์•ฝ ๊ทธ๋Ÿฐ ์ผ์ด ์ผ์–ด๋‚œ๋‹ค๋ฉด, ์ง€๊ธˆ์ด ๋‹ค๊ฐ€์˜ค๋Š” ํ˜ผ๋ž€์˜ ๋ฌผ๊ฒฐ์— ๋งž์ถฐ ์‚ฌํšŒ ์•ˆ์ „๋ง์„ ์ •๋น„ํ•  ๋•Œ๋ผ๊ณ  ๊ฐ•์กฐํ•ฉ๋‹ˆ๋‹ค. ํ•˜์ง€๋งŒ ์ง€๊ธˆ๊นŒ์ง€ ๊ทธ๋Ÿฌํ•œ ์ค€๋น„๋Š” ์ œ๋Œ€๋กœ ์ด๋ฃจ์–ด์ง€์ง€ ์•Š๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

2026๋…„ ์›”๋“œ์ปต, โ€˜๋‹ค์ด๋‚ด๋ฏน ํ”„๋ผ์ด์‹ฑโ€™ ๋…ผ๋ž€: ์ถ•๊ตฌ ํŒฌ๋“ค์˜ ๋น„๋ช…

์Šคํฌ์ธ  ๋ถ„์•ผ์—์„œ๋Š” ๋‹ค๊ฐ€์˜ค๋Š” ์›”๋“œ์ปต์˜ ์ƒˆ๋กœ์šด ํ‹ฐ์ผ“ ์ •์ฑ…์ด ํŒฌ๋“ค ์‚ฌ์ด์—์„œ ํฐ ๋…ผ๋ž€์„ ๋ถˆ๋Ÿฌ์ผ์œผํ‚ค๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค.

FIFA์˜ ์ƒˆ๋กœ์šด ์ •์ฑ…: ํŒ€ ์ธ๊ธฐ ๋”ฐ๋ผ ๊ฐ€๊ฒฉ ๋ณ€๋™

ํ•œ ๋‹ฌ์—ฌ ์•ž์œผ๋กœ ๋‹ค๊ฐ€์˜จ ๋ฏธ๊ตญ, ๋ฉ•์‹œ์ฝ”, ์บ๋‚˜๋‹ค ๊ณต๋™ ๊ฐœ์ตœ ์›”๋“œ์ปต์„ ์•ž๋‘๊ณ  FIFA๋Š” ๊ณผ๊ฑฐ ๋Œ€ํšŒ์™€๋Š” ๋‹ค๋ฅธ ํฐ ๋ณ€ํ™”๋ฅผ ๋ฐœํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค. ์‚ฌ์ƒ ์ฒ˜์Œ์œผ๋กœ โ€˜๋‹ค์ด๋‚ด๋ฏน ํ”„๋ผ์ด์‹ฑ(dynamic pricing)โ€˜์„ ์ ์šฉํ•˜๋Š” ๊ฒƒ์ž…๋‹ˆ๋‹ค. ์ด๋Š” ๊ฐ€์žฅ ์ธ๊ธฐ ์žˆ๋Š” ํŒ€์˜ ๊ฒฝ๊ธฐ๋ฅผ ๊ด€๋žŒํ•˜๋Š” ํ‹ฐ์ผ“ ๊ฐ€๊ฒฉ์ด ๋” ๋น„์‹ธ๋‹ค๋Š” ๊ฒƒ์„ ์˜๋ฏธํ•ฉ๋‹ˆ๋‹ค.

์ด ์ •์ฑ…์ด ํŒฌ๋“ค์—๊ฒŒ ์–ด๋–ค ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ์•Œ์•„๋ณด๊ธฐ ์œ„ํ•ด ๋‰ด์š•ํƒ€์ž„์ฆˆ๋Š” ์ถ•๊ตฌ์— ๋Œ€ํ•œ ์—ด์ •์ด ๊ตญ๊ฐ€์ ์ธ ์ง‘์ฐฉ ์ˆ˜์ค€์ธ ์•„๋ฅดํ—จํ‹ฐ๋‚˜์˜ ํŒฌ๋“ค์„ ์ฐพ์•„ ์ธํ„ฐ๋ทฐํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ณผ๊ฑฐ ์›”๋“œ์ปต์— ์ฐธ๊ฐ€ํ–ˆ๋˜ ํ•œ ํŒฌ์€ ๋Ÿฌ์‹œ์•„์™€ ์นดํƒ€๋ฅด์—์„œ์˜ ๊ฒฝํ—˜์ด โ€œํ™˜์ƒ์ ์ด๊ณ  ๋†€๋ผ์› ๋‹คโ€๊ณ  ํšŒ์ƒํ–ˆ์Šต๋‹ˆ๋‹ค.

์•„๋ฅดํ—จํ‹ฐ๋‚˜ ํŒฌ๋“ค์˜ ์ขŒ์ ˆ: โ€˜๋ชจ๋‘๋ฅผ ์œ„ํ•œ ๊ฒƒโ€™์ด โ€˜์†Œ์ˆ˜๋ฅผ ์œ„ํ•œ ๊ฒƒโ€™์œผ๋กœ

์•„๋ฅดํ—จํ‹ฐ๋‚˜๊ฐ€ ์ง€๋‚œ ์›”๋“œ์ปต์—์„œ ์šฐ์Šนํ•˜๋ฉด์„œ ์˜ฌํ•ด ๊ฒฝ๊ธฐ์˜ ํ‹ฐ์ผ“ ๊ฐ€๊ฒฉ์€ ๋”์šฑ ์น˜์†Ÿ์•˜์Šต๋‹ˆ๋‹ค. ์ผ๋ถ€ ํŒฌ๋“ค์€ ๋‹จ ์„ธ ์žฅ์˜ ํ‹ฐ์ผ“์„ ์œ„ํ•ด 3,000๋‹ฌ๋Ÿฌ๋ฅผ ์ง€์ถœํ•ด์•ผ ํ•œ๋‹ค๊ณ  ํ† ๋กœํ•˜๋ฉฐ โ€œ๋ฏธ์นœ ์ง“โ€์ด๋ผ๊ณ  ๋งํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ณผ๊ฑฐ์—๋Š” 100๋‹ฌ๋Ÿฌ ๋ฏธ๋งŒ์œผ๋กœ ํ‹ฐ์ผ“์„ ๊ตฌ๋งคํ–ˆ๋˜ ํŒฌ๋“ค๋„ ์ด์ œ๋Š” ์•„๋ฅดํ—จํ‹ฐ๋‚˜์˜ ์›”ํ‰๊ท  ๊ธ‰์—ฌ๋ฅผ ๋„˜์–ด์„œ๋Š” ๊ฐ€๊ฒฉ์„ ๋งˆ์ฃผํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋‰ด์š•ํƒ€์ž„์ฆˆ์˜ TK ํŒ๊ฐ€ ๊ธฐ์ž๊ฐ€ ํŒฌ๋“ค๊ณผ ๋Œ€ํ™”ํ•œ ๊ฒฐ๊ณผ, ์ผ๋ถ€๋Š” ๋„ˆ๋ฌด ๋น„์‹ธ์„œ ํฌ๊ธฐํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ๋‹ค๋ฅธ ์ด๋“ค์€ ์ฐธ์„ํ•˜๊ธฐ ์œ„ํ•ด ๋นš์„ ์ง€๊ณ  ์‹ ์šฉ์นด๋“œ๋ฅผ ํ•œ๋„๊นŒ์ง€ ์“ฐ๋Š” ๊ทน๋‹จ์ ์ธ ๋ฐฉ๋ฒ•์„ ํƒํ•˜๊ณ  ์žˆ๋‹ค๊ณ  ์ „ํ–ˆ์Šต๋‹ˆ๋‹ค.

FIFA๋Š” ๋†’์€ ๊ฐ€๊ฒฉ์„ ๋ฐ˜๋ณตํ•ด์„œ ์˜นํ˜ธํ•˜๋ฉฐ, ์ „ ์„ธ๊ณ„ ์ถ•๊ตฌ ๋ฐœ์ „์„ ์œ„ํ•œ ์ˆ˜์ž…์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ์ฃผ์žฅํ•ฉ๋‹ˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ผ๋ถ€ ์•„๋ฅดํ—จํ‹ฐ๋‚˜ ํŒฌ๋“ค์˜ ๋ˆˆ์—๋Š” ์ด๋Š” โ€œ๋ˆ๋ฒŒ์ด ์ˆ˜๋‹จ(cash grab)โ€œ์— ๋ถˆ๊ณผํ•ฉ๋‹ˆ๋‹ค. ์˜ฌํ•ด ์›”๋“œ์ปต์— ๊ฐ€์ง€ ์•Š์„ ๊ฒƒ์ด๋ผ๊ณ  ๋งํ•œ ํ•œ ํŒฌ์€ โ€œ๋ชจ๋‘๋ฅผ ์œ„ํ•œ ๊ฒƒ์ด์–ด์•ผ ํ•  ๊ฒƒ์„ ์†Œ์ˆ˜๋งŒ์„ ์œ„ํ•œ ๊ฒƒ์œผ๋กœ ๋งŒ๋“œ๋Š” ๊ฒƒ์ด ํ™”๊ฐ€ ๋‚œ๋‹คโ€๊ณ  ๋ถ„๋…ธ๋ฅผ ํ‘œํ–ˆ์Šต๋‹ˆ๋‹ค.

โ€˜์ง€์˜ฅ์˜ ๋ฌธโ€™ ๋‹ค๋ฅด๋ฐ”์ž ๋ถ„ํ™”๊ตฌ์˜ ๋ฏธ์Šคํ„ฐ๋ฆฌ: ๋ถˆ๊ฝƒ์€ ๊บผ์ง€๋Š”๊ฐ€?

๋งˆ์ง€๋ง‰์œผ๋กœ, ์„ธ๊ณ„์—์„œ ๊ฐ€์žฅ ๋‹นํ˜น์Šค๋Ÿฌ์šด ๊ด€๊ด‘ ๋ช…์†Œ ์ค‘ ํ•˜๋‚˜์ธ โ€˜์ง€์˜ฅ์˜ ๋ฌธ(The Gates to Hell)โ€˜์— ๋Œ€ํ•œ ์—…๋ฐ์ดํŠธ์ž…๋‹ˆ๋‹ค.

60๋…„ ๋„˜๊ฒŒ ํƒ€์˜ค๋ฅธ ๋ถˆ๊ฝƒ์˜ ๊ธฐ์›

ํˆฌ๋ฅดํฌ๋ฉ”๋‹ˆ์Šคํƒ„(Turkmenistan)์— ์œ„์น˜ํ•œ ์ด โ€˜์ง€์˜ฅ์˜ ๋ฌธโ€™, ๊ณต์‹ ๋ช…์นญ์€ ๋‹ค๋ฅด๋ฐ”์ž ๋ถ„ํ™”๊ตฌ(Darvaza crater)์ž…๋‹ˆ๋‹ค. ํ˜„์ง€ ์ „์„ค์— ๋”ฐ๋ฅด๋ฉด ์•ฝ 60์—ฌ ๋…„ ์ „, ์†Œ๋ จ ์ง€์งˆํ•™์ž๋“ค์ด ์„์œ  ์‹œ์ถ” ์ž‘์—…์„ ํ•˜๋‹ค๊ฐ€ ๊ฐ€์Šค ๋งค์žฅ์ง€๋ฅผ ๊ฑด๋“œ๋ ธ๊ณ , ๋•…์ด ๋ฌด๋„ˆ์ง€๋ฉด์„œ ๊ฑฐ๋Œ€ํ•œ ๊ตฌ๋ฉ์ด๊ฐ€ ์ƒ๊ฒผ์Šต๋‹ˆ๋‹ค. ๊ณผํ•™์ž๋“ค์€ ์ด ๊ตฌ๋ฉ์ด์—์„œ ์ƒˆ์–ด ๋‚˜์˜ค๋Š” ์œ ๋… ๊ฐ€์Šค๋ฅผ ์ฒ˜๋ฆฌํ•˜๊ธฐ ์œ„ํ•ด ๋ถˆ์„ ๋ถ™์ด๋Š” ๊ฒƒ์ด ์ตœ์„ ์ด๋ผ๊ณ  ํŒ๋‹จํ–ˆ์Šต๋‹ˆ๋‹ค. ๊ทธ๋“ค์€ ๋ช‡ ์ฃผ ์•ˆ์— ๋ถˆ์ด ๊บผ์งˆ ๊ฒƒ์ด๋ผ๊ณ  ์˜ˆ์ƒํ–ˆ์ง€๋งŒ, ๋ถˆ์€ ์ง€๊ธˆ๊นŒ์ง€ ๊ณ„์† ํƒ€์˜ค๋ฅด๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ˆ˜๋…„์— ๊ฑธ์ณ ์ด๊ณณ์€ ์—ฐ๊ตฌ์ž๋“ค์—๊ฒŒ๋Š” ์ˆ˜์ˆ˜๊ป˜๋ผ๋กœ, ๋ชจํ—˜์„ ์ฆ๊ธฐ๋Š” ๊ด€๊ด‘๊ฐ๋“ค์—๊ฒŒ๋Š” ๋ช…์†Œ๊ฐ€ ๋˜์—ˆ์Šต๋‹ˆ๋‹ค.

๋ถˆ๊ฝƒ์˜ ์•ฝํ™”: ํ™˜๊ฒฝ์  ์˜ํ–ฅ๊ณผ ๋ฏธ์ง€์˜ ๋ฏธ๋ž˜

๊ทธ๋Ÿฌ๋‚˜ ์ตœ๊ทผ ๋‹ค๋ฅด๋ฐ”์ž ๋ถ„ํ™”๊ตฌ์˜ ๋ถˆ๊ฝƒ์ด ์˜์›ํ•˜์ง€ ์•Š๋‹ค๋Š” ์‚ฌ์‹ค์ด ๋ถ„๋ช…ํ•ด์กŒ์Šต๋‹ˆ๋‹ค. ์ฒœ์—ฐ๊ฐ€์Šค ๋ถˆ๊ฝƒ์„ ๋ชจ๋‹ˆํ„ฐ๋งํ•˜๋Š” ํ•œ ํšŒ์‚ฌ์— ๋”ฐ๋ฅด๋ฉด, ์ ์™ธ์„  ์˜์ƒ ๋ฐ์ดํ„ฐ๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ์ง€๋‚œ ๋ช‡ ๋…„๊ฐ„ ๊ตฌ๋ฉ์ด์˜ ์—ด ๊ฐ•๋„๊ฐ€ 75% ๊ฐ์†Œํ–ˆ์Šต๋‹ˆ๋‹ค. ์ •ํ™•ํ•œ ์›์ธ์€ ์•„์ง ๋ถˆ๋ถ„๋ช…ํ•ฉ๋‹ˆ๋‹ค. ๋˜ํ•œ ๋ถˆ๊ฝƒ์ด ๊บผ์ง€๋Š” ๊ฒƒ์ด ๊ธ์ •์ ์ธ ์ผ์ธ์ง€ ์•„๋‹Œ์ง€๋„ ํ™•์‹ค์น˜ ์•Š์Šต๋‹ˆ๋‹ค. ํ˜„์žฌ ๋ถˆ๊ฝƒ์€ ๊ตฌ๋ฉ์ด์—์„œ ์ƒˆ์–ด ๋‚˜์˜ค๋Š” ๋ฉ”ํƒ„(methane)์„ ํƒœ์›Œ ์ด ์˜จ์‹ค๊ฐ€์Šค(greenhouse gas)๊ฐ€ ๋Œ€๊ธฐ๋กœ ์œ ์ž…๋˜๋Š” ๊ฒƒ์„ ๋ง‰๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๋”ฐ๋ผ์„œ ์ด๋ก ์ ์œผ๋กœ ๋ถˆ์ด ์•ฝํ•ด์ง€๋ฉด ๋” ๋งŽ์€ ๋ฉ”ํƒ„์ด ๋ฐฐ์ถœ๋  ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

ํ˜น์‹œ ์ด ์†Œ์‹์— ์˜๊ฐ์„ ๋ฐ›์•„ โ€˜์ง€์˜ฅ์˜ ๋ฌธโ€™ ์—ฌํ–‰์„ ๊ณ ๋ คํ•˜๊ณ  ์žˆ๋Š”๋ฐ, ๋„์ฐฉํ•˜๊ธฐ ์ „์— ๋ถˆ์ด ๊บผ์งˆ๊นŒ ๊ฑฑ์ •๋œ๋‹ค๋ฉด ์—ผ๋ คํ•˜์ง€ ๋งˆ์‹ญ์‹œ์˜ค. ํ•œ ์—ฌํ–‰ ๊ฐ€์ด๋“œ๋Š” ์ตœ๊ทผ ์—ฌํ–‰์—์„œ ์—ฌ์ „ํžˆ ์ถฉ๋ถ„ํžˆ ๋œจ๊ฑฐ์›Œ์„œ ๊ทธ์˜ ์ผํ–‰์ด ๊ทธ ์œ„์—์„œ ๋งˆ์‹œ๋ฉœ๋กœ๋ฅผ ๊ตฌ์›Œ ๋จน์—ˆ๋‹ค๊ณ  ๋‰ด์š•ํƒ€์ž„์ฆˆ์— ์ „ํ–ˆ์Šต๋‹ˆ๋‹ค.

๊ฒฐ๋ก 

ํŠธ๋Ÿผํ”„ ํ–‰์ •๋ถ€์˜ ์˜ˆ์ธก ๋ถˆ๊ฐ€๋Šฅํ•œ ์™ธ๊ต ์ •์ฑ…๋ถ€ํ„ฐ AI๊ฐ€ ์ดˆ๋ž˜ํ•  ๋ฏธ๋ž˜ ์‚ฌํšŒ์˜ ๋ณ€ํ™”, ๊ทธ๋ฆฌ๊ณ  ๊ธ€๋กœ๋ฒŒ ์Šคํฌ์ธ  ์ด๋ฒคํŠธ์˜ ์ƒ์—…ํ™” ๋…ผ๋ž€๊นŒ์ง€, ์šฐ๋ฆฌ๋Š” ๋Š์ž„์—†์ด ์ƒˆ๋กœ์šด ๋„์ „์— ์ง๋ฉดํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์ด๋Ÿฌํ•œ ๋ณต์žก๋‹ค๋‹จํ•œ ์†Œ์‹๋“ค์€ ์šฐ๋ฆฌ๊ฐ€ ํ˜„์žฌ ์–ด๋–ค ์‹œ๋Œ€์— ์‚ด๊ณ  ์žˆ์œผ๋ฉฐ, ์•ž์œผ๋กœ ๋ฌด์—‡์„ ์ค€๋น„ํ•ด์•ผ ํ• ์ง€์— ๋Œ€ํ•œ ๊นŠ์€ ์„ฑ์ฐฐ์„ ์š”๊ตฌํ•ฉ๋‹ˆ๋‹ค.