As AI coding assistants and autonomous agents (often powered by large language models) become more involved in software development, best practices in coding must account for a new “audience.” Traditionally, code is written by and for human developers, emphasizing readability and maintainability for people. In contrast, code intended to be generated or maintained by AI...
Tag: AI
The Great Rewiring: Nadella and Zuckerberg on How AI is Reshaping Tech’s Foundation
AI isn’t just upgrading our tools—it’s redefining the tech foundation. In a compelling fireside chat, Satya Nadella and Mark Zuckerberg reveal how artificial intelligence is reshaping the very foundations of software development. From multi-model orchestration to AI-powered coding agents, they paint a future where the boundaries between documents, applications, and human input dissolve into a...
Integrating AI Agents into Teams—How to Succeed Without Tech Overload
AI agents are more than just smart chatbots—they're becoming genuine team members. With the right approach, AI agents like Roman from support function as part of your team, not as foreign entities. These AI agents don't hide behind interfaces or in the cloud. They have email addresses. They respond. They coordinate. And when implemented correctly,...
A2A vs MCP: Comparing AI Standards for Agent Interoperability
As AI agents increasingly automate and enhance complex workflows, the technology landscape is seeing the rise of crucial interoperability standards. Google's Agent2Agent (A2A) protocol and Anthropic's Model Context Protocol (MCP) stand out as prominent initiatives that, while complementary, target distinct aspects of AI integration. Here we take a deeper look at both, examining their designs,...
AI is automating our jobs – but values need to change if we are to be liberated by it
Artificial intelligence may be the most significant disruptor in the history of mankind. Google’s CEO Sundar Pichai famously described AI as “more profound than the invention of fire or electricity”. OpenAI’s CEO Sam Altman claims it has the power to cure most diseases, solve climate change, provide personalized education to the world, and lead...
Vibe Coding in Software Engineering
Vibe coding is a programming approach where developers rely on intuition and an organic “flow” state rather than formal planning or strict methodologies. In practice, this often means jumping straight into coding with minimal upfront design or documentation. Advocates argue that this free-form style can boost creativity and speed, but it also raises concerns in...
Vibe Coding: Embracing the AI Revolution in Software Development
Throughout the evolution of coding styles—from procedural and object-oriented programming to agile and DevOps methodologies—developers have continually refined their approaches. Now, a new coding paradigm is emerging—vibe coding. Coined by OpenAI cofounder Andrej Karpathy, vibe coding represents a radical shift from traditional software development. Rather than painstakingly writing every line of code, developers now harness the...
Breaking Down Data Silos with Email-Based AI Agents
Picture your organization's data ecosystem as an ancient city. In one quarter, sales records are meticulously kept in towering databases. Across town, customer stories echo through spreadsheets and feedback forms. And in yet another district, market insights are sealed away in countless reports and presentations. Between these quarters stand invisible walls – not of stone...
Training Data: The Source Code of the AI Era
In software development, we've long understood the distinction between source code and compiled binaries. Source code is what programmers write - the human-readable instructions that define a program's behavior. When we compile this code, we transform it into machine code that computers can execute efficiently. This compilation process necessarily obscures the original logic, making the...
How close is the superintelligence?
The pursuit of superintelligence—the development of artificial intelligence (AI) systems that significantly surpass human cognitive abilities—has become a focal point of research and debate within the AI community. As advancements in machine learning, particularly through large language models (LLMs) and deep learning techniques, have accelerated, experts increasingly ponder the implications of systems that could autonomously...
