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When AI systems were just a single model behind an API, life felt simpler. You trained, deployed, and maybe fine-tuned a few hyperparameters. But that world’s gone. Today, AI feels less like a single engine and more like a busy city—a network of small, specialized agents constantly talking to each other, calling APIs, automating workflows, […]
The debate about open source AI has largely featured open weight models. But that’s a bit like arguing that in the PC era, the most important goal would have been to have Intel open source its chip designs. That might have been useful to some people, but it wouldn’t have created Linux, Apache, or the
What MCP and Claude Skills Teach Us About Open Source for AI Read More »
The debate about open source AI has largely featured open weight models. But that’s a bit like arguing that in the PC era, the most important goal would have been to have Intel open source its chip designs. That might have been useful to some people, but it wouldn’t have created Linux, Apache, or the
What MCP and Claude Skills Teach Us About Open Source for AI Read More »
The conversation around artificial intelligence is shifting dramatically.We’ve evolved beyond the binary narrative of humans versus machines. The new paradigm is human–AI orchestration, led by a new generation of Agentic AI systems — autonomous, reasoning, goal-driven agents that collaborate with humans instead of replacing them. Welcome to the era of Human-in-the-Loop 2.0 — a world
The Future of Work: How Agentic AI Is Powering the Human-in-the-Loop 2.0 Revolution Read More »
The following article originally appeared on Medium and is being republished here with the author’s permission. Don’t get me wrong, I’m up all night using these tools. But I also sense we’re heading for an expensive hangover. The other day, a colleague told me about a new proposal to route a million documents a day
Job for 2027: Senior Director of Million-Dollar Regexes Read More »
One of the principles in our upcoming book Architecture as Code is the ability for architects to design automated governance checks for important architectural concerns, creating fast feedback loops when things go awry. This idea isn’t new—Neal and his coauthors Rebecca Parsons and Patrick Kua espoused this idea back in 2017 in the first edition
The following originally appeared on Asimov’s Addendum and is being republished here with the author’s permission. The other day, I was looking for parking information at Dulles International Airport, and was delighted with the conciseness and accuracy of Google’s AI overview. It was much more convenient than being told that the information could be found
Headlines surfaced by a simple “job market” search describe it as “a humiliation ritual” or “hell” and “an emerging crisis for entry-level workers.” The unemployment rate in the US for recent graduates is at an “unusually high” 5.8%—even Harvard Business School graduates have been taking months to find work. Inextricable from this conversation is the
Picture this: You’re a data analyst on day one at a midsize SaaS company. You’ve got the beginnings of a data warehouse—some structured, usable data and plenty of raw data you’re not quite sure what to do with yet. But that’s not the real problem. The real problem is that different teams are doing their
The following originally appears on fast.ai and is reposted here with the author’s permission. I’ve spent decades teaching people to code, building tools that help developers work more effectively, and championing the idea that programming should be accessible to everyone. Through fast.ai, I’ve helped millions learn not just to use AI but to understand it
