Why 'knowing the domain' beats 'knowing the syntax' in the age of AI

For decades, knowing how to code was the ultimate filter — the border between those who could build the future and those who could only imagine it. Programming was an exclusive language, and mastering it was the passport to innovation.

But something fundamental is changing. With the rise of large language models, the ability to “speak code” is no longer the bottleneck. Anyone who can articulate a problem clearly — in natural language — can now build, automate, and experiment with software. The new literacy is context and intent, not syntax.

The Rise of Vibe Coding

Figure 1. Vibe coding: the engineering of managing coding agents

A recent paper, A Survey of Vibe Coding with Large Language Models (arXiv:2510.12399), formalizes this shift. The authors describe “vibe coding” as a new software engineering paradigm where developers — or domain experts — express what they want in natural language, and AI agents translate that intention into functioning code.

As the paper puts it:

"Vibe Coding democratizes development by lowering technical barriers. Traditional development required extensive programming knowledge before implementing ideas. Natural language becomes the primary creation interface [4, 5, 1]. Domain experts—medical practitioners, educators, designers—articulate needs without computer science education [35]. This diversifies innovation sources, materializing underrepresented perspectives [276, 90]. Economic impact manifests through creator economy expansion: domain experts monetize specialized tools without technical co-founders. This parallels previous democratization waves, representing software literacy’s evolution from specialized skill to broadly accessible capability [277]."

That’s a polite academic way of saying: you don’t need to be a coder anymore to create technology.

From Coders to Context Designers

In the era of vibe coding, the most valuable skill is no longer the ability to implement an algorithm — it’s the ability to frame a problem precisely enough for an AI to solve it. The engineer’s role shifts from writing code to curating context.

Large language models are increasingly capable of handling the heavy lifting: writing boilerplate, integrating APIs, generating tests, and refactoring entire modules in seconds. The human task becomes more abstract — defining goals, understanding users, validating outcomes, and, most importantly, knowing why something should be built in the first place.

Technically, vibe coding relies on prompt-to-code translation, feedback loops, and memory contexts that allow AI agents to act as continuous collaborators rather than static tools. But the real transformation is cultural: programming is no longer a private language — it’s a shared conversation.

The Democratization of Software Creation

This is the next wave of software literacy. Just as spreadsheets let non-programmers do analytics and early web builders allowed anyone to publish online, vibe coding opens the door for domain experts to innovate directly — without waiting for a technical co-founder.

Educators can build adaptive learning tools. Doctors can prototype decision-support systems. Investigative journalists can automate parts of their analysis. All without touching a compiler.

This isn’t just productivity — it’s diversity. When the power to automate and create software extends beyond professional programmers, we get new voices, new biases (yes), but also new perspectives that never made it through the technical gate before.

The End of Algorithmic Gatekeeping

Many hiring processes still test humans through exercises designed for another era — whiteboard coding, algorithm puzzles, sorting challenges. Ironically, the systems used to test “problem-solving skills” are now solved instantly by the very AI tools candidates are supposed to use at work.

It’s time to rethink what we value. Being a good engineer in 2025 isn’t about knowing every edge case of a data structure. It’s about integrating knowledge, building safely with AI, and understanding the broader environment — legal, ethical, and human — in which your system operates.

Humans Still Matter — Just Not the Same Way

In my own work building desenmascara.me, I see this transition daily. The technical core — the AI model, the database, the interface, the analysis pipeline — is important. But the real breakthroughs happen when domain expertise meets automation: understanding how scammers operate, how users think, and how to translate that into patterns an AI can detect.

Figure 2. Example of domain expertise for edge cases on scam websites

That’s not programming — that’s reasoning, modeling, and empathy. It’s the essence of what vibe coding elevates: humans defining intent, AI handling execution.

The Bottom Line

Vibe coding doesn’t make programmers obsolete — it redefines them.
It moves software creation from a narrow technical discipline to a broader human capability. The best developers of the future won’t be those who type the fastest, but those who think the clearest.

The next generation of engineers, designers, and researchers will all share one thing: They don’t just code. They vibe.

The article itself is AIL 3

Migration to post-quantum cryptography

"One threat to the security of today’s digital systems is closely tied to the anticipated arrival of large-scale quantum computers. It is often called the Harvest Now, Decrypt Later (HNDL) attack."

Must read paper published by Mastercard - below the introduction:

Quantum computing is no longer a distant dream — it’s a rapidly advancing reality that promises to revolutionize industries, including finance. Around the world, governments and private enterprises are investing billions in this transformative technology, betting on its potential to solve problems that are currently beyond the reach of even the most powerful classical computers. But with this promise comes a profound risk: quantum computers threaten to undermine the cryptographic foundations that keep our financial systems secure.

Today’s digital trust relies on public-key cryptography, with algorithms like RSA and Elliptic Curve Cryptography forming the backbone of secure transactions and data protection. These systems, however, are vulnerable to the immense computational power of quantum machines. Once quantum computers reach a certain threshold, they could render current encryption methods obsolete, exposing financial institutions to risks of data breaches, financial loss and reputational harm.

The urgency to act is clear. A reactive approach to cybersecurity is no longer sufficient in the face of quantum threats. Financial organizations must proactively plan for a future where quantum-safe practices are the norm. This means exploring and adopting quantum-safe technologies, such as Post-Quantum Cryptography and Quantum Key Distribution, and preparing for a migration away from classical cryptographic systems. Early adopters will be best positioned to protect their assets and maintain resilience as the quantum era approaches.

This white paper aims to cut through the hype and provide a clear-eyed, evidence-based assessment of the quantum threat landscape, with practical guidance for financial institutions on how to navigate the technological, operational and regulatory complexities of quantum migration. By acting now, organizations can ensure the integrity of encrypted communications, secure payment systems and safeguard sensitive customer data — laying the groundwork for a secure financial future in a quantum world. 

The same day this news broke:

“A truly remarkable breakthrough — Google’s new quantum chip achieves an unprecedented accuracy milestone.”. Nature

If quantum computing is reaching this level of precision, it’s not science fiction anymore.

Better be prepared.

Unmasking the Scam Crisis: Europe’s Next Cyber Challenge

The scam threat:

This is just one of the several resources launched as part of the National Strategy in US to prevent scams. An ambitious effort bringing together corporate leaders, policymakers, and society as a whole to face what is no longer a marginal problem.

The full 70-page report includes strong calls for cross-sector cooperation, and the accompanying video is especially powerful. 

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A victim shares her story with remarkable honesty — a reminder that only around 15% of scams are ever reported. Also worth noting: the Global Head of Policy at TRM Labs explains how complex networks operate behind these scams, from fake investments to crypto fraud.

As the Aspen Institute puts it clearly:

“This is a national security crisis — and the problem is only getting worse.”

In Europe, we can’t look away. The same patterns are emerging here, rapidly crossing borders and exploiting the trust of millions.

That’s exactly why I built desenmascara.me — an AI-powered European platform designed to detect and expose fraudulent and impersonation websites, helping citizens, brands, and regulators see what’s really behind the digital façade.

I already shared some reflections on this in my recent LinkedIn article: How desenmascara.me can help tackle Europe’s scam epidemic.

The US has moved. Now it’s time for Europe to act — together, across public and private sectors.
Let’s raise awareness. Let’s cooperate.
Let’s unmask the web.