Subscribe • Previous Issues Local AI Is a Routing Problem, Not a Privacy Feature I’ve had a longstanding interest in local AI for a simple reason. I would rather not send proprietary code, unpublished plans, or knowledge about how a business operates to an outside model provider when I have a viable alternative. I want more controlContinue reading “The local AI question I had backwards”
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I keep thinking about these 17,600 attempts
Subscribe • Previous Issues Eight Security Assumptions AI Agents Quietly Break If you check Ethics.Dev regularly, you may have noticed how often AI agents and cybersecurity have been colliding lately. Some of the stories sound straight out of movies: agents escaping test environments, communicating through channels nobody intended, finding vulnerabilities, stealing credentials, and reaching production systems. TheContinue reading “I keep thinking about these 17,600 attempts”
Something changed in how AI gets fed
Subscribe • Previous Issues The AI Data Problem Moved Downstream Last year I wrote that robotics had a data problem language models were lucky enough to avoid. Text, images, and code had accumulated for decades before anyone decided to train models on them. Robots had no comparable internet of physical experience. That distinction is starting to lookContinue reading “Something changed in how AI gets fed”
why your data stack is about to get less forgiving
Subscribe • Previous Issues Stale Data Used to Be Annoying Imagine a procurement agent checking inventory and deciding that stock has fallen below the reorder threshold. It places another order. The problem is that a large delivery was recorded a few minutes earlier, and the copy of the data the agent queried has not caught up. AContinue reading “why your data stack is about to get less forgiving”
so Google just paid $10 million for an airline’s Teams messages
Subscribe • Previous Issues When Work History Becomes an AI Asset Google recently agreed to pay $10 million for the internal business data of Spirit Airlines. The airline is bankrupt, but its emails, Teams messages, software, spreadsheets, and operating records apparently still have value. Google plans to use the material for product development and AI. Spirit’s flightContinue reading “so Google just paid $10 million for an airline’s Teams messages”
Your AI model is a rental (but the loop is an asset)
Subscribe • Previous Issues Self-Improvement Without the Science Fiction A few weeks ago I wrote about AI systems that keep learning after deployment instead of treating every interaction as a fresh start. That prompted a few readers to ask about recursive self-improvement (RSI). The connection is real, but I think it helps to separate three ideas. ContinualContinue reading “Your AI model is a rental (but the loop is an asset)”
if everyone rents the same intelligence, what’s left?
Subscribe • Previous Issues Your Model Is Not Your Moat In a recent article, I wrote about companies turning their own data, workflows, and production feedback into specialized intelligence they increasingly control. The deeper idea was compounding. What matters is not simply whether a model performs well today, but whether using it creates assets that make theContinue reading “if everyone rents the same intelligence, what’s left?”
I keep hearing the same advice about agents
Subscribe • Previous Issues Nine Practical Rules for Agents Doing Real Work In recent conversations with crews building agents, I keep hearing the same lessons. Teams with very different products are arriving independently at almost the same architectural choices. That convergence feels important. In recent posts, I argued that passing your evals does not mean an AIContinue reading “I keep hearing the same advice about agents”
The model may not be your biggest risk
Subscribe • Previous Issues The biggest AI risks sit outside the model The most revealing AI failures right now are not stories about models becoming too capable. They are stories about everything around the model. One system received more access than its test environment could contain. Another was trained on material whose acquisition created $1.5 billion inContinue reading “The model may not be your biggest risk”
Why do our AI models stop learning the second we deploy them?
Subscribe • Previous Issues Continual Learning Is Arriving in Pieces A while back I wrote about how startups are using reinforcement learning to make agents more reliable. A deeper problem behind that whole trend keeps resurfacing: a model can improve during training, but the moment it’s deployed, learning largely stops. A policy changes, a new edge caseContinue reading “Why do our AI models stop learning the second we deploy them?”
