The agentic revolution introduces objective auditing into political action and redefines state efficiency
Agents as Allies of Public Governance
The technological tool that enhances effectiveness and efficiency
By Dr. Nelson Jorge Mosco Castellano
Friedrich Hayek in “The Fatal Conceit: The Errors of Socialism” argues that socialism fails because it attempts to centrally plan a complex society that functions better as a “spontaneous order.”
The “arrogance” we endure in governance is the belief that human reason can design the economy and society better than the market, ignoring that knowledge is dispersed among individuals.
In essence, Hayek tells us that society is formed by free individuals whose myriad daily interactions shape the society in which they want to live, except in totalitarian systems.
When a politician believes their creative version is superior, we are left subject to the consequences that fall upon the governed without mitigation.
And even to the justification of errors, omissions, corporate interests, and corruption.
It is precisely free human ingenuity that is exponentially multiplying creative actions to audit governance with intelligent machines, effectively seeking to improve the living conditions of individuals and society.
The Agentic Revolution is the tool created by human beings that defines the current transition from an artificial intelligence that merely answers questions (like traditional chatbots) to one that executes actions autonomously.
The shift toward systems free from egocentric and selfish political influence, incorporating into public policy planning human, sensitive, ethical, and reasonable criteria, along with the review of results without constant human supervision.
They eliminate the excuse of political interest in the outcomes of such policies, producing an objective audit of governance, which, when made public in economic, moral, ethical, and social terms, becomes subject to voter scrutiny.
What was once veiled by subjectivity, political or electoral interest, or outright state corruption is made transparent in its successes, failures, and non-conformities, generating more appropriate alternatives.
It is no longer a biased critique of circumstance. From a classical liberal perspective, it reduces the costs of inefficiency, ineffectiveness, and the limits of political knowledge, which, beyond fatal arrogance, often conceal ego or malice.
To understand this revolution, one must observe the three pillars that distinguish an agent from a simple chat:
They do not merely process information; they break down a general objective (e.g., “Organize an event”) into logical steps, prioritize actions, and correct their own course if something goes wrong.
They have the ability to interact with the digital world. They can use browsers, execute code, send emails, perform transactions on a blockchain, or manage databases.
They maintain a record of what they have done and learned over time, allowing them to improve their performance in recurring tasks.
The impact on social and economic structure
This paradigm shift offers a profound transformation at multiple levels:
We stop using AI as an “advanced search engine” and begin treating it as a “digital employee” or a strategic partner.
It enables a single individual to manage processes that previously required entire departments, strengthening individual sovereignty, decentralization, and efficiency against heavy bureaucratic structures.
A future is envisioned where agents negotiate with each other. Your personal agent could negotiate with an insurance agent to find the best policy according to your ethical and economic criteria, executing the contract automatically.
Why now?
Although the idea of agents has existed since the early days of computing, it is only now that language models have reached the necessary “critical mass” of reasoning to understand complex instructions and handle real-world ambiguity without failing.
In the Agentic Revolution, it is not about machines speaking better, but about machines acting for us, allowing human beings to move toward roles of design, supervision, and critical thinking.
LLMs (Large Language Models) are a type of artificial intelligence trained to understand, generate, and apply human language in a coherent and contextual manner.
If the Agentic Revolution is the engine that enables “action,” LLMs are the linguistic brain that enables communication with the agent and reasoning with it.
The term “Large” refers to two fundamental aspects:
They have been trained on entire libraries, scientific articles, programming code, and conversations, enabling them to know virtually any topic developed by human intelligence.
They consist of internal variables that the model adjusts during its learning and development.
Current models have billions of these parameters, allowing them to capture subtleties, irony, ethical concepts, and complex logical structures.
Unlike traditional rule-based software (if A happens, do B), an LLM operates through statistical probabilities:
Its basic task is to predict the most likely next word (or “token”) in a given sequence.
They use a mechanism called “attention,” which allows them to weigh different words in a sentence to understand the overall context.
LLMs have demonstrated abilities once considered exclusively human:
They translate concepts rather than words.
They can analyze summaries and synthesize key ideas from long texts.
They are programmed to write and correct code in multiple programming languages.
With logical reasoning, they can solve mathematical problems or break down complex philosophical arguments.
The limit: From model to agent
An LLM alone is static; it is like an encyclopedia that only speaks when consulted.
It becomes part of the “Agentic Revolution” when that language model connects to external tools, enabling it not only to explain what a contract is, but to analyze terms, draft it, and send it.
To deepen the use of LLMs within an intellectual and strategic framework, these tools can act as a Socratic interlocutor to break down complex ideas.
LLMs allow for “cross-reading.” You can ask the model to analyze a current problem through the lens of specific authors:
“How would Hayek evaluate the implementation of a state digital currency versus a decentralized one in terms of individual freedom?”
The model traces principles from “The Road to Serfdom” and applies them to modern technical variables, helping to identify risks of authoritarianism or bureaucracy that might otherwise go unnoticed.
Synthesis of Liberal Arts and Critical Thinking
In an era of information overload, the synthesis capability of an LLM helps recover the value of the Liberal Arts (Trivium and Quadrivium).
They can be used to structure logical arguments (Dialectic) and improve clarity of expression (Rhetoric).
Here, the human role acts as the “teacher” who validates the ethical and moral coherence of what the AI proposes, ensuring that knowledge is not only technical but humanistic.
“The true safety net of the 21st century is not a state subsidy, but a sovereign digital identity that the government cannot confiscate.”