Blog · Review Essay · Last reviewed June 14, 2026

A Hacker Manifesto and the Vectoralist Class

McKenzie Wark's A Hacker Manifesto is a compact theory of information-age class power. It matters now because AI platforms have made the book's central conflict newly concrete: people and machines produce abstractions, but the owners of the vectors decide which abstractions can circulate, be priced, be trained on, be queried, and be turned into institutional authority.

The Book

A Hacker Manifesto was published by Harvard University Press in 2004. Google Books lists the edition at 208 pages, published October 4, 2004, with subjects including computers, internet, intellectual property, and political philosophy. The same record describes the book as a restatement of Marxist thought for cyberspace and globalization, drawing on Guy Debord and Gilles Deleuze, and centered on the conflict around commodified information.

Wark's own institutional location matters. The New School profile lists A Hacker Manifesto among Wark's publications and names media theory, new media, and critical theory as research interests. This is not a manual about intrusion or security technique. It is media theory written as political economy: a manifesto about who produces new abstractions and who owns the channels through which those abstractions become valuable.

The book belongs beside Hackers, Coding Freedom, Protocol, The People's Platform, Data Cartels, and The Stack. Those books trace hacker culture, open-source institutions, network control, platform dependency, information monopoly, and planetary computation. Wark supplies the class vocabulary: hackers make the new; vectoralists own the vectors.

The Hacker Is Not Just a Programmer

The first useful move in A Hacker Manifesto is widening the word "hacker." Wark does not limit the hacker class to computer programmers. A hacker is anyone whose labor produces new information, new relations, new concepts, new expressions, new forms, or new abstractions from raw material. That includes software developers, scientists, artists, writers, designers, musicians, theorists, biologists, and other makers of information-bearing novelty.

This broad definition can irritate readers expecting a narrower history of computer hacking. A First Monday review from 2005 notes that Wark's hacker includes writers and singers alongside programmers, which is exactly where some readers may feel the book leaving conventional hacker culture. Brent Jesiek's 2006 New Media & Society review makes a similar point from a more sympathetic angle: the book is not a conventional account of hackers, but an information-age Marxism about a new productive class and the class that controls informational conduits.

The broadness is the point. Wark is not trying to describe a subculture. Wark is trying to name a mode of production in which valuable work increasingly appears as abstraction. Code is an abstraction. A model architecture is an abstraction. A dataset schema is an abstraction. A design pattern, scientific paper, video format, patent claim, playlist genre, legal database, prompt template, benchmark, and synthetic voice are all abstractions that can be copied, priced, enclosed, ranked, and routed.

That makes the hacker class vulnerable in a specific way. If the output of labor is information, then the central fight is not only wages. It is ownership, licensing, distribution, access, credit, versioning, search visibility, API permission, and the right to keep building without asking permission from whoever owns the channel.

The Vectoralist Class

Wark's strongest term is "vectoralist." The vectoralist class owns and controls the vectors through which information moves: networks, platforms, databases, distribution channels, legal rights, telecommunications systems, search systems, archives, standards, payment rails, identity layers, and other conduits that turn abstraction into power.

The term has aged well because it does not depend on one company, device, or business model. In 2004, the immediate setting was file sharing, software, intellectual property, digital culture, and globalization. In 2013, Melissa Gregg's Los Angeles Review of Books interview with Wark framed the book's ten-year legacy around the shift from factory-centered class analysis to a knowledge economy in which hackers produce innovation, knowledge, and abstraction while vectoralists appropriate and commoditize those goods. The interview also captured Wark's later judgment that social creation had won some affordances while vectoral power regrouped around metadata and more abstract control.

That later comment is crucial. The vector is not only the visible file, post, song, model, article, or app. It is also the metadata, the identity graph, the query log, the ranking signal, the dependency map, the training corpus, the access token, the permission scope, the benchmark result, the provenance field, the container image, the distribution agreement, and the payment event. The owner of the vector can make openness feel generous while keeping control over the layer that makes openness operational.

This is why the book remains sharper than generic "information wants to be free" rhetoric. Wark is not saying that copying alone defeats property. Wark is saying that information creates a distinct class struggle because it can be nonrival at the level of the artifact and still scarce at the level of access, attention, legality, computation, discoverability, and institutional adoption.

The AI Reading

Read in 2026, A Hacker Manifesto looks like a prehistory of AI platform politics. Foundation models are machines for producing and manipulating abstraction, but they sit on vectors owned by firms and institutions: training data pipelines, cloud compute, GPU supply chains, model weights, API gateways, app stores, eval suites, safety classifiers, enterprise connectors, identity systems, payment rails, and default interfaces.

The hacker class now includes more than people writing code or text. It includes open-source maintainers whose repositories become training material, artists whose styles become latent coordinates, scientists whose papers become retrieval inputs, forum users whose answers become model behavior, moderators whose judgment becomes safety data, labelers whose decisions become alignment examples, and users whose prompts become telemetry. The work of abstraction is distributed. The ownership of the vector is concentrated.

That is not a simple anti-AI argument. Models can help hackers make more abstractions: code, images, interfaces, simulations, theories, diagrams, datasets, tests, and tools. But Wark's class lens asks who captures the surplus when abstraction becomes cheap to produce. If every worker gains a copilot while every platform gains the telemetry, distribution channel, billing relationship, and model improvement loop, the balance of power may still move upward.

The same issue appears in open models. A model weight release can expand technical agency, but openness at one layer does not settle vectoral control at other layers. Who has compute to train or fine-tune? Who hosts the endpoint? Who controls the package registry, container, model hub, benchmark leaderboard, safety certification, deployment policy, and enterprise procurement path? The vector can absorb the gift.

Wark's vocabulary is useful because it avoids treating "open" and "closed" as moral absolutes. The real question is what practical powers move with the artifact. Can affected people inspect it, run it, repair it, fork it, contest it, exit it, and use it without feeding a dependency loop they cannot govern?

Recursive Reality

The book also helps explain recursive reality: representations become infrastructure, then infrastructure changes the world being represented.

A search index ranks documents, so publishers write for the index. A recommender ranks videos, so creators make videos for the recommender. A benchmark ranks models, so labs train toward the benchmark. A coding assistant suggests patterns, so codebases absorb the assistant's defaults. A legal research platform organizes precedent, so lawyers learn the platform's map of relevance. A model marketplace ranks downloads, so builders shape releases around distribution signals. The vector does not merely transmit abstraction. It trains the next abstraction.

This is where A Hacker Manifesto becomes more than a property argument. It is a theory of world-making through information channels. Once the vectoral class owns the path by which abstractions reach users, it can shape not only prices but imagination. Some tools become visible. Some problems become profitable. Some forms of knowledge become easier to cite, retrieve, train, and operationalize. Others become noise.

AI systems intensify the loop because they can act on the abstractions they inherit. A model trained on platform-shaped culture produces new platform-shaped culture. A procurement benchmark produces products optimized for procurement benchmarks. A data broker's schema becomes the memory through which agencies see people. A school dashboard produces student records that train future dashboards. The vector observes the world, routes the world, and then treats the routed world as evidence.

Where the Book Needs Friction

A Hacker Manifesto is brilliant as a conceptual machine, but it is not a careful empirical map of every labor relation in the information economy. Its manifesto form is compressed, polemical, and aphoristic. That makes the book memorable. It also makes it easy to overextend.

The biggest risk is class flattening. Wark's hacker class includes artists, scientists, programmers, writers, and other abstraction workers, but those groups do not share one stable interest. Some are precarious. Some are employees of vectoralist firms. Some become founders, investors, managers, or owners. Some depend on copyright or patents for survival. Some produce public knowledge; some produce surveillance systems. Some want openness; some want monopoly if they can get it.

Jesiek's New Media & Society review is useful here because it praises the ambition while noting concerns about the likely unification of productive classes and about making class primary over other relations of oppression. That caution has only become more important. AI extraction, data labor, biometric surveillance, platform moderation, algorithmic ranking, and intellectual-property fights are also shaped by race, gender, disability, migration status, geography, language, caste, credentialing, and the uneven capacity to refuse.

The book also has an ambivalent relationship to institutions. A politics of the commons cannot live on circulation alone. Public-interest infrastructure needs libraries, universities, standards bodies, unions, maintainers, courts, archives, regulators, public compute, cooperative platforms, durable funding, and maintenance cultures. Without institutions, the vectoralist class often wins by being the only actor willing to keep the channel running.

Those limits do not weaken the book's relevance. They make its best use clearer. Read it as a diagnostic for information power, not as a complete program. It names a conflict that has become more visible in the AI era: abstraction is socially produced, but the route from abstraction to reality is owned.

What This Changes

The practical lesson is to audit the vector, not only the artifact.

When evaluating an AI model, platform, agent, dataset, creative tool, search product, or open-source release, ask who owns the route. Who controls discovery, hosting, identity, billing, logging, metadata, evaluation, compliance, and defaults? Who gets to change the terms after people depend on the system? Who receives the improvement data? Who can fork in practice, not just in license theory? Who can appeal when the vector misclassifies, buries, prices, blocks, or extracts from them?

For labor, ask whether AI expands the hacker's agency or merely accelerates abstraction for someone else's channel. A coding assistant can improve craft if it leaves workers with understanding, authorship, bargaining power, and repair capacity. It can also turn craft into prompt throughput while centralizing knowledge in a vendor's model and logs.

For culture, ask whether new creative abundance is paired with durable rights for creators, maintainers, labelers, communities, and publics. A platform that celebrates remix while owning ranking, monetization, training access, and moderation has not abolished property. It has moved property into the vector.

A Hacker Manifesto matters because it gives a hard name to a soft interface. The friendly surface says create, share, prompt, remix, build, publish, and connect. The vector decides what can be found, paid, trained, trusted, and remembered. In the AI era, that is where much of the politics lives.

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