I am always on the lookout for new AI agents and applications that operate outside the coding world. By agent, I mean a system that can take a goal, use tools, keep context, and work through several steps rather than simply answer a prompt. Looking through my notes from the recent AI Agent Conference, IContinue reading “Beyond the Demo: What Real AI Agents Actually Do at Work”
Author Archives: Ben Lorica
What Upwork, DoorDash, Meta, EY, and Fundrise reveal about agents
Subscribe • Previous Issues Beyond the Demo: What Real AI Agents Actually Do at Work I am always on the lookout for new AI agents and applications that operate outside the coding world. By agent, I mean a system that can take a goal, use tools, keep context, and work through several steps rather than simply answerContinue reading “What Upwork, DoorDash, Meta, EY, and Fundrise reveal about agents”
The Vatican’s AI Principles: What You Need to Know
The Vatican’s recent encyclical, Magnifica Humanitas, introduces a moral framework that challenges how technology leaders evaluate artificial intelligence. It treats AI as a test of human priorities. Its central question is not whether AI can make institutions faster, cheaper, or more scalable. The question is whether it helps people live with more dignity, freedom, responsibility,Continue reading “The Vatican’s AI Principles: What You Need to Know”
An AI Math Breakthrough and the New Division of Labor
In a piece I wrote a few months ago, I argued that research mathematics had become an unexpectedly useful test case for AI, precisely because mathematical claims are either right or wrong, which makes AI outputs verifiable in a way that many business applications are not. That argument just got a very concrete test case.Continue reading “An AI Math Breakthrough and the New Division of Labor”
Integration Is the New Moat: Moving Beyond the LLM
The AI Agent Conference in New York was one of the better events I’ve attended to get a read on what’s actually happening with enterprise AI. The formal sessions were great, but the hallway conversations was where I got the inside scoop. The consistent message: deploying AI agents is much harder than most organizations expect,Continue reading “Integration Is the New Moat: Moving Beyond the LLM”
Google I/O 2026: The Agent Layer Takes Shape
The announcements at Google I/O 2026 landed today. I’ve gone through everything and pulled out what I think actually matters for people building products, running technical teams, or making bets on where AI is heading. The short version: Google used this I/O to stake a claim on the agentic layer, and the ambition is widerContinue reading “Google I/O 2026: The Agent Layer Takes Shape”
Stop upgrading your LLM. Start fixing your data.
Subscribe • Previous Issues Integration Is the New Moat: Moving Beyond the LLM The AI Agent Conference in New York was one of the better events I’ve attended to get a read on what’s actually happening with enterprise AI. The formal sessions were great, but the hallway conversations was where I got the inside scoop. The consistentContinue reading “Stop upgrading your LLM. Start fixing your data.”
The End of the AI Experiment: Surviving the CFO’s New ROI Demands
Why This Has Become an Executive Issue Why is AI spend no longer just an IT budget problem? AI has crossed a threshold where aggregate spend across every department requires capital allocation discipline, not just software procurement review. Every function now has a case for AI investment, and someone has to decide which requests deserveContinue reading “The End of the AI Experiment: Surviving the CFO’s New ROI Demands”
Why your AI bills are going up (even as tokens get cheaper) 📉💸
Subscribe • Previous Issues The End of the AI Experiment: Surviving the CFO’s New ROI Demands Why This Has Become an Executive Issue Why is AI spend no longer just an IT budget problem? AI has crossed a threshold where aggregate spend across every department requires capital allocation discipline, not just software procurement review. Every function nowContinue reading “Why your AI bills are going up (even as tokens get cheaper) 📉💸”
Why Your AI Agents Fail in Production (And How to Actually Test Them)
In a previous post, I argued that deploying autonomous AI agents reliably is not primarily a model problem. It is an environment problem. The gap between a capable foundation model and a production-ready system is bridged by harness engineering: the discipline of building structured workflows, validation loops, and governance mechanisms around the model rather thanContinue reading “Why Your AI Agents Fail in Production (And How to Actually Test Them)”