Agents Over Bubbles

AI is probably not a bubble

AI companies have revenue, demand, and paths to immense value

AI is probably not a bubble

AI companies have revenue, demand, and paths to immense value

After AI

Legacies of the bubble.

The AI bubble isn’t new — Karl Marx explained the mechanisms behind it nearly 150 years ago

OpenAI CEO Sam Altman’s warning of an AI bubble highlights a deeper economic problem: capitalism is producing more capital than it can profitably invest.

Build Agent Advocates, Not Platform Agents

Language model agents are poised to mediate how people navigate and act online. If the companies that already dominate internet search, communication, and commerce -- or the firms trying to unseat them -- control these agents, the resulting platform agents will likely deepen surveillance, tighten lock-in, and further entrench incumbents. To resist that trajectory, this position paper argues that we should promote agent advocates: user-controlled agents that safeguard individual autonomy and choice. Doing so demands three coordinated moves: broad public access to both compute and capable AI models that are not platform-owned, open interoperability and safety standards, and market regulation that prevents platforms from foreclosing competition.

Andrew Orlowski on Twitter / X

By far the shrewdest and most entertaining analyst of the AI bubble is Georg Zoeller, ex Facebook. Re-reading his DeepSeek reaction piece from 18 months, which holds up well. It was all so predictable: banning open source, the Red Menace, pivot to military. What has really… pic.twitter.com/38dX7vcrkC— Andrew Orlowski (@AndrewOrlowski) July 5, 2026

pguso/ai-agents-from-scratch

Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.

10 things I learned from burning myself out with AI coding agents

Opinion: As software power tools, AI agents may make people busier than ever before.

The Eternal Sloptember

I’m calling it now, the adoption of AI agents into software development will be one of the most costly mistakes in the field’s history. Agents cannot program, and it’s taking longer and longer to realize that they can’t. They are a highly sophisticated statistical model designed to mimic the distribution of programming. The output is broken, but in a way that’s getting harder and harder to detect. Which is exactly what you’d expect from an increasingly accurate statistical model.

The Eternal Sloptember

I’m calling it now, the adoption of AI agents into software development will be one of the most costly mistakes in the field’s history. Agents cannot program, and it’s taking longer and longer to realize that they can’t. They are a highly sophisticated statistical model designed to mimic the distribution of programming. The output is broken, but in a way that’s getting harder and harder to detect. Which is exactly what you’d expect from an increasingly accurate statistical model.

AI Agents Will Become the New UI, and Apps Take a Backseat

For decades, screens, keyboards, and structured applications have shaped our relationship with technology. People learned how to interact with computers

Introduction to Agents

Discover what actually works in AI. Join millions of builders, researchers, and labs evaluating agents, models, and frontier technology through crowdsourced benchmarks, competitions, and hackathons.