Tag: AI
The AI Paradox at Work: Why LLMs Don’t Just Automate Tasks — They Undermine the Job Map
In early 2024, McDonald's made a quiet announcement: after three years of testing AI-powered drive-through ordering across more than 100 U.S. restaurants, the company was pulling the plug on its partnership with IBM. The technology would be removed by July 26. The official explanation was polished corporate-speak about "exploring voice ordering solutions more broadly."...
The Probabilistic Revolution: How AI is Making Software Engineering More Like “Real” Engineering
For decades, software engineers have endured a peculiar form of professional imposter syndrome. While their colleagues in mechanical, civil, and chemical engineering designed bridges that probably wouldn't collapse and factories that mostly wouldn't explode, software engineers worked in a deterministic paradise where 2+2 always equaled 4, functions returned predictable outputs, and bugs were logical puzzles...
The Web’s Old Guard Isn’t Chasing AGI—They’re Building the New Infrastructure
Christina Wodtke, veteran product designer and Stanford lecturer, captured something profound recently: "The old timers who built the early web are coding with AI like it's 1995. They gave blockchain the sniff test and walked away. Ignored crypto. NFTs got a collective eye roll. But AI? Different story. The same folks who hand-coded HTML while...
Microsoft’s TinyTroupe Gets Major Update: Digital Humans for Business Insights
The Secret Life of AI Learning: How Transformers Adapt Without Really Changing
Large language models like GPT-4 and Claude have a seemingly magical ability: show them a few examples of a new pattern, and they can immediately apply that pattern to solve similar problems—all without any traditional "learning" or weight updates. It's as if you could teach someone to play chess by showing them three games, and...
Software 3.0 Revolution: The AI-Driven Programming Paradigm Shift
The software development landscape has undergone a seismic transformation, with AI coding assistants reaching 76% developer adoption and $45 billion in generative AI funding in 2024 alone. Andrej Karpathy's prophetic Software 1.0/2.0 framework now extends to Software 3.0, where natural language programming has become reality and "vibe coding" is democratizing software creation for millions. This...
When AI Hits a Wall: Limits of Reasoning Models Revealed
The latest generation of AI models from OpenAI, Anthropic, and others promise something revolutionary: machines that can "think" before they answer. These Large Reasoning Models (LRMs) generate detailed chains of thought, self-reflect on their reasoning, and supposedly tackle complex problems better than their predecessors. But new research from Apple throws cold water on these claims,...
The AI Job Apocalypse Is Already Here—But It’s Not What You Think
Simon Willison has a problem. As co-creator of Django and a veteran software engineer with 25 years of experience, he's watching his own profession get disrupted by the very technology he's helping to advance. However, in his recent conversation with journalist Natasha Zubes, what emerges isn't the typical doom-and-gloom narrative about AI replacing everyone. Instead,...
Coding for AI Agents vs. Coding for Human Developers
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...