Ilana Gershon: What insights into coding and Silicon Valley emerge when you begin with hackers in Mexico?
Héctor Beltrán: Starting from Mexico reveals how Silicon Valley’s celebrated flexibility is actually quite rigid about who gets to be flexible and where. During my fieldwork, the mainstream narrative was that tech is open, meritocratic, and borderless. But when Mexican hacker-entrepreneurs register their startups as Delaware C Corporations or name their apps in English instead of Spanish just to be taken seriously, they’re not simply “entering the global tech economy.” They’re exposing how that economy is structured around very specific forms of presence and legitimacy. One research participant told me his team realized “if they think we’re a Mexican startup, nobody will pay attention to us.” This isn’t paranoia. It’s pattern recognition.
What I found most striking was how hackers used coding concepts to analyze these dynamics. They’d talk about their relationships with investors using the language of “loose coupling”—a software design principle where components interact without needing to know each other’s internal workings. For them, loose coupling became a way to maintain autonomy while navigating institutions that simultaneously fetishized and devalued their labor. They were loosely coupled to tech companies, to government programs, to the promises of the Aztec Tiger economy—the promise that Mexico would become a tech powerhouse (like the Asian Tigers of South Korea, Taiwan, and so on).
But here’s where it gets interesting: loose coupling is celebrated in code design precisely because it creates modularity and replaceability. Mexican hackers recognized they were being positioned as replaceable talent, present when needed, disposable when not. So they turned the metaphor back on the system, using it to think critically about the political economy they were embedded in. This is what I call “code work”: the labor of using coding logics not just to build software, but to analyze and navigate social and political relations.
Ilana Gershon: I am quite struck by your argument that coding strongly shapes the ways in which hackers understand how to create social change. Could you talk a little bit about how coding practices around loose coupling and looping shape how Mexican hackers try to create larger political changes?
Héctor Beltrán: The hacker school in Mexico City offers a perfect example. The founders loved hackathons so much they wanted to “live the hackathon every day”: to extend what’s typically a weekend event into an ongoing way of life. But instead of creating a permanent space, they made their bootcamp nomadic, moving through different locations in twelve-week cycles. Each cycle was a batch of students, and when a batch finished training, they’d work within tech companies or government offices where they were being recruited for their coding skills. If there was no good match—if the organization might compromise the hacker ethic they’d carefully cultivated—the hacker would return to the next batch and try again. They called this “catching an exception.”
These aren’t just cute metaphors. In programming, exception handling is how you plan for things going wrong. A defensive programmer anticipates failures and writes special cases to handle them. The hacker school was doing exactly this with employment relationships. Instead of responding desperately to job postings, they systematically analyzed workplace dynamics, interviewed workers about retention and nepotism, and treated each placement as an iteration: a loop with a conditional. If conditions weren’t met, loop again.
This iterative, looping approach to social change differs fundamentally from both revolutionary rupture and liberal incrementalism. It’s more like what performance artist David Morison Portillo does with “border looping” in his collaboration with anthropologist Rihan Yeh, Border Vueltas / Looping Fronterizo—crossing the San Ysidro port of entry repeatedly to expose the system’s rituals and constraints. The repetition isn’t failure; it’s methodology. Each iteration reveals more about how power operates.
But I want to be clear: this isn’t some techno-utopian fantasy where coding logic solves political problems. Many of my research participants got caught reproducing the same flexibility that exploited them. The code work can be a tool for critique, but it can also reinforce the neoliberal logics that ask young people to endlessly optimize themselves. The question I kept returning to was: when does thinking with the code help you see the system differently, and when does it just make you better at surviving within it?
Ilana Gershon: Your interlocutors encounter quite a few stigmatizing stereotypes in the course of being entrepreneurs/hackers. What aspects of coding logic do they use when responding to contexts rift with stereotypes?
Héctor Beltrán: The concept that came up most was “pivoting,” that Silicon Valley buzzword about rapidly adapting your product to align with the market. But my research participants also pivoted their identities, their language practices, their entire presentation of self. Javo, whose story anchors the final chapter, pivoted his startup from an anti-corruption voting fraud app to a pizza delivery system when that’s what investors wanted to hear. But more revealingly, he pivoted between being recognizably Mexican in some spaces and invisible as Mexican in others.
At a tech festival in Mexico, he wore the sombrero, waved the flag, performed enthusiastic Mexicanness for the live feedback to Silicon Valley headquarters. But when pitching to US investors, he emphasized his US presence—his San Francisco address, his “perfect English” inherited from his El Paso-born grandmother. He learned exactly when to leverage being “a hungry Mexican who knows the market” and when to render that identity invisible.
What’s fascinating is that Javo explicitly theorized this. He told me investors had asked whether his entire team was Mexican, implying they’d run things the Mexican way. So he learned to code-switch not just linguistically but ontologically: to pivot his presence across what I call the techno-Borderlands. The term pivot gave him a framework to understand and strategically navigate the racialized politics of tech work.
But this individual maneuvering has limits. The stereotypes Javo encountered (that Mexicans lack entrepreneurial culture, that they’re backward, that they need their “chip” changed—literally a government slogan: “todos con el mismo chip”) aren’t bugs in the system. They’re features. They justify paying Mexican programmers two to five times less than their US counterparts while celebrating Mexico as a source of raw talent.
Ilana Gershon: You studied a Latina hackathon, what did you discover about the gendered divisions of labor in computing?
Héctor Beltrán: The women’s hackathon was advertised as “the first for women by women in Latin America,” focused on designing “intelligent homes.” On the surface, this looks like classic gendered segregation: women designing domestic technologies, reinforcing their association with home and family. And yes, those dynamics were present. But something more interesting happened.
The organizers strategically used Arduino kits to place participants at a higher level of the computing stack; they could manipulate sensors and data without needing to master lower-level programming. This allowed women with different technical backgrounds to participate as peers. More importantly, it created space for a surprise intervention that’s become readers’ favorite ethnographic moment: the arrival of the abuelitas.
At the end of the hackathon, grandmothers showed up to cheer for their granddaughters. Their presence completely shifted the event’s meaning. In computing cultures, “grandmother” is typically deployed as the figure of technological incompetence—”make it simple enough for your grandmother to use/understand.” But here, the abuelitas weren’t passive recipients of explanation. Their presence asserted something fundamental: they were the infrastructure that made the hackathon possible. The domestic labor, the childcare, the intergenerational support; this was the actual “bottom layer of the stack” that enabled everything else.
One participant told me her abuelita “es la que ayuda en todo del día a día. Ella es la que se encarga de todo” (she’s the one that helps with everything in the day to day. She is the one that is in charge of everything). The abuelitas displaced the male tech mentors standing along the walls in their Google shirts—mentors who functioned as both reminders of the gendered hierarchy of expertise and a form of male surveillance over the women’s work. The abuelitas effectively reminded everyone that before you can code, someone has to make it possible for you to sit down and code.
Ilana Gershon: At the end of your book, you talk about how some of your interlocutors gradually transformed their initial ideas into an imminently fundable startup that could assist activists and NGOs in the global South. What lessons do you draw from this example?
Héctor Beltrán: Javo’s trajectory—from politics to pizzas and back to politics—is one of the book’s answers to whether code work can enable meaningful social change. His team’s app, “Pingafy,” used mesh networking to let phones communicate without internet or cellular service. They initially developed it thinking about earthquake response in Mexico City. But the app escaped their control in productive ways. Protesters in Hong Kong, Myanmar, and Ukraine started using it to organize away from government surveillance.
The surprise was that Javo accomplished this by doing what Silicon Valley ideology claims to value: focusing on the product, staying apolitical, working on the technology itself. He explicitly would say “we don’t support or not support anyone; we are just a tool.” This seemingly depoliticized stance actually enabled a deeply political outcome because he focused on the root layers of the computing stack: the underlying protocols that enable communication, not just the surface-level features.
There’s an important lesson here about where to aim your intervention. A lot of hackathons produce apps that are really just technological fixes, solutions that avoid addressing systemic issues. Javo’s original anti-corruption app, designed to report voting fraud in Mexico, fell into this trap. But by working on fundamental communication infrastructure, his team created something protesters could appropriate for their own purposes.
That said, I don’t want to romanticize this as a simple success story. Javo’s team received millions in venture capital because investors saw what they understood as disruptive technology, not because they cared about protesters. The app works for social movements, but it also works within capitalist logics of value extraction. And Javo’s path required forms of privilege (mobility, linguistic capital, elite university connections) that most Mexican hacker-entrepreneurs don’t have.
The real lesson is about connecting what I call code work to border work. Javo’s transnational experience—shuttling between Mexico and Silicon Valley, navigating shifting markers of race and nation, learning when to perform Mexicanness and when to render it invisible—gave him the analytical tools to understand how different systems operate. He learned to think with the code not just about software architecture, but about political economy, about how structures of innovation repeatedly reassemble into structures of inequality, iteration after iteration.
That’s what I mean by border-code-workers: people who can connect technical logics with critical consciousness about power. It’s one of the final keywords I offer readers in the book’s glossary, structured like the documentation or manuals programmers would appreciate, another bridge I’m trying to build with this work. The book ends with this provocation: if we want technology to serve liberatory ends, we can’t just teach more people to code. We need to cultivate hackers who understand that the code work can never stand alone. It has to be tightly coupled with the harder work of dismantling the borders (geographic, racial, gendered, economic) that determine whose hacking gets celebrated and whose gets criminalized.
CaMP Anthropology 