Iuliia Gorshkova

The business-to-business (B2B) landscape is undergoing rapid transformation as artificial intelligence (AI) technologies mature and proliferate. For organizations developing AI products, selling to large enterprises presents both enticing opportunities and unique challenges. Navigating the complexities of procurement, establishing credibility, and addressing concerns about trust, security, and measurable benefit require a thoughtful, strategic approach rooted in [...]

There's a peculiar kind of madness that has taken hold of the startup ecosystem lately. It’s a gold rush mentality, but instead of pickaxes and shovels, the tools are transformers and diffusion models. Every pitch deck now seems to have a slide with the word "AI" in a font size slightly larger than the rest, [...]

There’s a particular kind of fever that grips engineering teams when a new paradigm emerges. It’s the urge to refactor, to rewrite, to shoehorn the new tool into every possible workflow simply because it exists. We saw it with microservices, with blockchain, and now we are seeing it with Artificial Intelligence. The Large Language Model [...]

The prevailing narrative in popular media often paints Artificial Intelligence as a monolith—a singular, sentient entity poised to either solve all human problems or bring about our doom. This anthropomorphic framing is seductive, but for those of us who spend our days in the trenches of code and computation, it’s a profound misrepresentation of reality. [...]

For years, the dominant narrative surrounding Artificial Intelligence has been one of monolithic ambition. We have been conditioned to think of AI as a singular entity—a "brain" in the machine—tasked with reasoning, remembering, and reacting as a whole. When we interact with systems like GPT-4, it is easy to anthropomorphize the output, to imagine a [...]

The most interesting systems I’ve built recently aren’t the ones where the neural network does all the heavy lifting. They’re the ones where a tiny, rigid, absolutely predictable piece of code acts as a gatekeeper for the probabilistic chaos inside. It’s a counter-intuitive shift if you’ve been marinating in the hype surrounding Large Language Models [...]

There’s a persistent misunderstanding about how artificial intelligence actually functions in the real world. We tend to anthropomorphize the technology, imagining it as a singular, monolithic intelligence capable of reasoning from first principles. When an LLM generates a coherent paragraph or a diffusion model paints a photorealistic scene, it feels like magic—like pure thought. But [...]

Artificial Intelligence (AI) has permeated nearly every facet of modern life, from healthcare diagnostics and financial forecasting to personalized recommendations and autonomous vehicles. Yet, despite remarkable technical advancements, the widespread adoption of AI-powered solutions is frequently stymied by a less tangible but equally formidable challenge: the trust, or lack thereof, that users place in algorithms. [...]

Every engineer who has spent time in the trenches of production machine learning systems knows the peculiar dread of the "silent drift." It isn’t the catastrophic failure of a server outage or a syntax error that screams for attention; it is the slow, almost imperceptible erosion of performance. The model that once sliced through data [...]

Every engineer has a favorite story about a model that seemed perfect in the lab but slowly turned into a confused, unreliable mess in production. It rarely happens all at once. Instead, it’s a quiet erosion of performance, a subtle drift that’s easy to miss until a critical error forces a panicked review of the [...]

There’s a peculiar kind of hubris baked into the early iterations of large language models. It’s the confidence of an encyclopedia that never learned to say “I’m not sure.” When you ask a model about a niche historical event that occurred yesterday, or query it on a specific line of code from a library that [...]

There's a peculiar hum in the air when an AI system admits it doesn't know something. It's not the static of a wrong answer or the confident drone of a hallucination—it's the sound of integrity. In the landscape of artificial intelligence, where we've spent decades pushing systems toward omniscience, the ability to say "I don't [...]

When we interact with large language models, we often treat the output as a monolithic block of generated text. We ask a question, we get an answer. The process feels atomic, complete. But under the hood, generative AI is a sequential process, a chain of predictions where each step is mathematically dependent on the one [...]

Imagine you're having a conversation with a brilliant colleague who has a peculiar habit. For the first ten minutes, they are sharp, insightful, and perfectly on point. But then, a subtle shift occurs. They misremember a name, and in the next sentence, they build an argument based on that incorrect name. A few exchanges later, [...]

Artificial intelligence startups face increased scrutiny as their systems play ever more critical roles in society. An audit of an AI system is a rigorous evaluation of its processes, data, fairness, security, and compliance with regulations. Whether the audit is regulatory, a requirement from partners, or part of due diligence for investment, the process can [...]

There's a particular kind of silence that settles over a server room at 3 AM when an autonomous agent you've spent months building goes spectacularly off the rails. It’s not the loud, crash-of-thunder kind of failure. It’s a quiet, creeping chaos. A few weeks ago, I watched a logistics agent I’d deployed to optimize shipping [...]

The allure of autonomous agents is undeniable. We envision systems that can independently navigate complex tasks, from booking travel to debugging code, acting as tireless digital employees. Yet, the chasm between a promising demo and a resilient production environment is vast and often littered with the wreckage of failed deployments. As someone who has spent [...]

The Persistent Ghost in the Machine When we talk about artificial intelligence, we often speak in metaphors of cognition. We say a model "understands" a prompt, that it "reasons" through a problem, or that it "remembers" a fact. But in the realm of autonomous agents—systems designed to perceive, plan, and act independently—the concept of memory [...]

Every time I boot up a local LLM or experiment with a new agentic framework, I find myself wrestling with a paradox. We are building systems that can reason, plan, and execute code with startling competence, yet they remain fundamentally amnesiac. They are brilliant strangers waking up in a new room every few seconds, armed [...]

There’s a palpable energy shift happening in the software engineering community right now. We are moving past the initial hype of Large Language Models (LLMs) as mere chat interfaces or autocomplete engines and stepping into a phase where these models are integrated into the very fabric of our systems. This integration often brings us to [...]

One of the most common misconceptions I see in the rapidly evolving landscape of AI application development is the conflation of two fundamentally distinct architectural patterns: AI Agents and AI Workflows. While often used interchangeably in marketing materials and casual conversation, understanding the difference isn't just semantic pedantry—it is the critical factor that determines whether [...]

Artificial intelligence is advancing rapidly, yet the landscape of innovation is uneven. While the giants of the tech world train ever-larger models, small AI startups and independent researchers face a series of daunting obstacles. *Developing and training sophisticated AI models is not just about having smart algorithms; it’s about access to immense resources, both computational [...]

We have all seen it: the slick keynote stage, the confident presenter, the live demonstration of an AI model that seems to defy the laws of computational physics. It answers complex questions instantly, generates photorealistic images from vague descriptions, or navigates a robot through a chaotic environment with grace. The audience gasps, the stock price [...]

The stage is dark. A single spotlight hits the presenter, who holds a smartphone. "Watch this," they say, and speak into the device: "Show me a photo of a giraffe wearing a space helmet, riding a unicorn on Mars." A few seconds of processing spinners, and then—boom. The image appears on the big screen behind [...]

For years, the conversation around integrating artificial intelligence into software products has been dominated by the language of features. Product managers and engineers ask, "Where can we add an AI button?" or "Which workflow could be automated by a model?" This mindset treats AI as a shiny add-on, a discrete module bolted onto the existing [...]

The conversation around artificial intelligence in product development has become strangely monolithic. We talk about "AI features" as if they are shiny ornaments to be added to an existing structure, like hanging a new lamp in a living room that has stood for years. This framing is seductive because it’s simple. It suggests a checklist: [...]

There’s a particular kind of dread that only hits when you watch a model you’ve spent weeks fine-tuning suddenly start hallucinating nonsense in production. It’s the digital equivalent of a bridge collapsing after you’ve already opened it to traffic. In traditional software engineering, we have a safety net: version control. We commit, we push, we [...]