Subscribe • Previous Issues The AI Visibility Playbook: Surviving the Shift from Search to Synthesis More people are turning to AI chatbots instead of traditional search engines to find information online. Even Google now displays an AI Overview at the top of many search results to summarize answers directly. When search engines ruled the internet, search engineContinue reading “AI is describing your competitors better than you. Here’s why.”
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Why the heaviest AI users actually produce worse results 🤯
Subscribe • Previous Issues How to Stay Employable When AI Is Coming for Your Job Over the past few weeks, I have had a lot of conversations with people who are genuinely worried about what AI means for their careers. Not just developers, but marketers, analysts, lawyers, and others who are starting to wonder how much ofContinue reading “Why the heaviest AI users actually produce worse results 🤯”
Why smarter agent architecture does not always improve results
Subscribe • Previous Issues Why Your AI Agents Need Engineering Instead of Best Practices I remain optimistic about the impact agents will have on knowledge work. As I noted in an earlier article, fields shaped by clear rules and mature systems, including accounting and contract management, already look well suited to this kind of automation. But evenContinue reading “Why smarter agent architecture does not always improve results”
When AI does the junior work, how do we train seniors?
Subscribe • Previous Issues The Agentic Sweet Spot: Where AI Moves Fast and Humans Stay in the Loop A recent Anthropic study on agent autonomy offers a clear preview of where knowledge work is headed. Anthropic analyzed millions of real interactions across their public API and Claude Code to see how people actually deploy autonomous systems. TheContinue reading “When AI does the junior work, how do we train seniors?”
8 domains where AI agents are actually working
Subscribe • Previous Issues How Teams Actually Use RL to Make Agents Reliable I have had a longstanding fascination with reinforcement learning (RL) and have monitored its slow diffusion from research labs into enterprise production. Much of the recent activity remains concentrated among foundation model builders and teams with dedicated post-training capacity. They use RL after pre-trainingContinue reading “8 domains where AI agents are actually working”
The warning signs your AI vendor is becoming your cage
Subscribe • Previous Issues The Honeymoon Phase Won’t Last: Preparing for AI’s Platform Shift I am old enough to remember the early days of the internet. It was a time when blogs were everywhere and information felt decentralized. Before the giant platforms and their algorithms, the web felt like a collection of independent voices. We had chronologicalContinue reading “The warning signs your AI vendor is becoming your cage”
AI agents just made your data pipeline obsolete
Subscribe • Previous Issues The Industrialization of Synthetic Data Synthetic data used to be a fairly narrow idea: pad a small dataset, test a model without touching production data, maybe stress a system for bias. The rise of generative AI and autonomous agents has changed the landscape. Teams use synthetic data to train and evaluate agentic systems,Continue reading “AI agents just made your data pipeline obsolete”
The margin paradox threatening every AI company
Subscribe • Previous Issues The AI Bubble Is Real. Enterprise Usage Is Even More Telling. The existence of an AI bubble is beyond dispute. What remains unclear is when or how it deflates. As investors know all too well, the most costly mistake in business is often being correct prematurely. The infrastructure layer has already booked revenues.Continue reading “The margin paradox threatening every AI company”
Your agents need runbooks, not bigger context windows
Subscribe • Previous Issues Why Your AI Agents Need Operational Memory, Not Just Conversational Memory Now that AI agents are moving out of the lab and into the real world, we’re realizing that “memory” isn’t one-size-fits-all. Most people think of agent memory like a personal assistant. It remembers your preferences, your travel plans, and the email youContinue reading “Your agents need runbooks, not bigger context windows”
The “Data Center Rebellion” is here
Subscribe • Previous Issues Beyond the Chips: The Local Politics of AI Infrastructure Even the most ardent cheerleaders for artificial intelligence now quietly concede we are navigating a massive AI bubble. The numbers are stark: hyperscalers are deploying roughly $400 billion annually into data centers and specialized chips while AI-related revenue hovers around $20 billion — aContinue reading “The “Data Center Rebellion” is here”