Iuliia Gorshkova

Every founder I meet seems to be hunting for the same mythical creature: a "full-stack" machine learning engineer who can build state-of-the-art models, deploy them to production, manage cloud infrastructure, and somehow also handle data annotation. They are looking for a unicorn, and frankly, unicorns are rare, expensive, and often allergic to the mundane realities [...]

When people talk about building an AI company, the conversation almost immediately gravitates toward the "hard" technical roles: the machine learning engineers, the research scientists, the backend architects. It’s a natural bias; we tend to view AI through the lens of code and math because those are the tangible levers of capability. But anyone who [...]

It’s a strange thing, watching a brilliant engineering team celebrate a successful model deployment, only to have the entire project jeopardized a week later by a cease-and-desist letter regarding a dataset they scraped two years prior. In the world of artificial intelligence, speed is often mistaken for progress, and the legal landscape is treated as [...]

Most AI teams I know treat legal review like a fire extinguisher: essential, but only considered when something is already burning. They bring in a lawyer when a term sheet is being negotiated, when a user sues, or when a major enterprise client demands a custom data processing agreement that no one on the engineering [...]

We need to talk about the elephant in the server room. For the last two years, the prevailing wisdom in the startup world was simple: move fast, break things, and figure out the ethics later. That approach works when you’re disrupting the photo-sharing market. It works significantly less well when your "disruption" involves a neural [...]

It's a strange paradox we're navigating right now. On one hand, the "move fast and break things" ethos that birthed Silicon Valley is colliding with a global demand for accountability. On the other, the very nature of Artificial Intelligence—its probabilistic, non-deterministic behavior—seems fundamentally incompatible with the rigid, check-box compliance frameworks that govern industries like finance [...]

When regulators talk about "risk-based approaches" to artificial intelligence, they're not just using corporate jargon to sound sophisticated. They're grappling with a fundamental tension: how do you create rules for a technology that can be a medical diagnostic tool in the morning and a video game character in the evening? The answer lies in classification [...]

When we talk about regulating artificial intelligence, the conversation often drifts into abstract philosophy or dystopian fiction. But for the engineers and architects building these systems, regulation is a concrete engineering problem. It’s about compliance matrices, risk assessment protocols, and system boundaries. The European Union’s AI Act, along with emerging frameworks in the US and [...]

Most engineers I know react to the EU AI Act with a specific kind of fatigue. It feels like another layer of compliance bureaucracy, a set of vague legal constraints imposed on systems that are already complex enough. But if we look closely at the text of the regulation—specifically the risk categories outlined in Articles [...]

Most AI systems in production today are built for performance, speed, or cost reduction. They are rarely built for compliance by default. With the EU AI Act now in force, this gap is no longer a minor oversight; it is a structural risk. The Act does not merely regulate data privacy or model bias; it [...]

There's a persistent myth in the startup world, particularly in the AI space, that regulation and speed are mortal enemies. The narrative goes that you build the thing first, get it to market, and then, once you have traction and funding, you deal with the messy business of compliance. It’s treated as a tax on [...]

There’s a peculiar myth that persists in engineering circles, particularly among those building the next generation of intelligent systems: the idea that compliance is a tax on innovation. It’s viewed as a bureaucratic hurdle, a set of guardrails installed after the real work is done, or a necessary evil to appease legal teams before a [...]

It’s a strange feeling to watch a promising project slowly suffocate under the weight of paperwork and legal ambiguity. I’ve seen it happen in server rooms and co-working spaces where brilliant engineers were building things that genuinely excited me—algorithms that could diagnose rare diseases, systems that could optimize energy grids, tools that could help writers [...]

When founders talk about building artificial intelligence, the conversation almost always orbits around compute, data, and talent. Regulatory risk often enters the room late, treated as a compliance checkbox rather than a foundational design constraint. That’s a mistake. In practice, the jurisdictions where AI startups face the earliest and most forceful shutdowns aren’t necessarily the [...]

Building intelligent systems today feels a bit like sailing uncharted waters. You can architect a beautiful vessel, rig the sails perfectly, and harness the wind's power, but you never quite know when you'll hit a regulatory reef or a compliance squall. The landscape of AI legislation is shifting beneath our feet, not as a singular [...]

Every engineer who has ever shipped a model across borders knows the sinking feeling when a legal memo lands in the inbox with the subject line “Compliance Review.” It’s rarely about a missing comma or a forgotten log entry. It’s about a jurisdiction you’ve barely considered suddenly dictating the architecture of your pipeline. As we [...]

Australia and New Zealand are often grouped together in discussions about technology policy, largely due to their close cultural and economic ties. However, when it comes to the governance of Artificial Intelligence, they represent two distinct philosophical approaches that reflect their broader regulatory traditions. While both nations are deeply invested in the potential of AI [...]

When you start digging into the regulatory landscape for artificial intelligence, the immediate instinct is to look for a single, monolithic law—a "GDPR for AI," if you will. But in the antipodes, specifically in Australia and New Zealand, that search comes up empty. Instead, you find something far more intricate: a patchwork of existing legal [...]

Canada’s approach to regulating artificial intelligence has emerged as a distinct middle path, navigating the chasm between the European Union’s comprehensive, risk-based legislation and the United States’ fragmented, enforcement-driven landscape. The Artificial Intelligence and Data Act, or AIDA, represents Ottawa’s attempt to future-proof governance without stifling the rapid innovation occurring in hubs like Toronto-Waterloo and [...]

When I first started digging into the regulatory frameworks governing artificial intelligence, I found myself constantly mapping the landscape back to my own experiences writing code. You know the feeling: you’re staring at a complex system, trying to understand its architecture, its dependencies, and its failure modes. Regulatory frameworks are no different. They are systems [...]

It's a peculiar paradox we find ourselves grappling with in the northern reaches of Europe. On one hand, the Nordic region is often hailed as a cradle of technological innovation—home to tech giants like Spotify and a vibrant ecosystem of startups tackling everything from fintech to green energy. Yet, when the conversation turns to the [...]

When discussing the trajectory of artificial intelligence, the conversation often orbits around the colossal regulatory frameworks of the European Union, the aggressive commercial expansion of Silicon Valley, or the state-driven strategies of China. Yet, tucked into the northern reaches of Europe, the Nordic bloc—Sweden, Finland, Denmark, and Norway—presents a fascinating, somewhat paradoxical case study. On [...]

When founders in Madrid or Barcelona pitch their latest AI-driven solution, they often rehearse their technical architecture, market fit, and burn rate with religious precision. Yet, when the conversation drifts to the regulatory landscape, a palpable vagueness settles in. It’s a curious blind spot, particularly given that the European Union’s Artificial Intelligence Act (AI Act) [...]

If you’re building an AI company in Madrid, Barcelona, Milan, or Lisbon, the regulatory landscape feels different than it does in Berlin or Amsterdam. It’s not just about the text of the European Union’s AI Act—it’s about how local bureaucracies interpret compliance, how labor courts treat algorithmic management, and how regional grants subtly shape your [...]

There’s a certain kind of shift that happens in the developer experience that isn’t immediately obvious from a changelog. It’s not about a new feature or a faster compiler; it’s about where the center of gravity lies when you’re building software. For decades, that gravity was anchored firmly to the text editor, the file system, [...]

The discourse surrounding prompt engineering has, for the last couple of years, taken on the proportions of a gold rush. You have seen the headlines, the boot camps promising six-figure salaries in weeks, and the LinkedIn profiles suddenly blooming with "Certified Prompt Engineers." It feels like a new frontier, a specialized discipline emerging from the [...]

There’s a specific moment in every engineering career when the toolchain shifts beneath your feet. Maybe it was the transition from manual memory management to garbage collection, or from on-prem servers to the cloud. For many of us in the field right now, that tectonic shift is happening again, but this time it’s not just [...]