When the Algorithm Is the Interface
Some years ago, a designer assigned to my team and I became interested in a central question about recommendations. We were working on shopping experiences, and it seemed obvious that people approached shopping with very different intentions. Sometimes you know more or less what you want. You are trying to solve a problem, find the…
Subagents: From Agentic Systems to Agentic Organizations
In earlier posts in this series, I proposed agentics as a way to study artificial agents and agent systems more systematically [1]. I offered a broad working definition: An agent is an entity capable of selecting and performing actions in pursuit of objectives, within an environment, under constraints [2]. I subsequently suggested that agentic capabilities…
New Insights into Agent-mediated Retail Discovery
For the past several months, I have been writing about agent-mediated retail discovery: a future in which the consumer’s AI agent — not the retailer’s website — becomes the primary place where intent is understood, alternatives are evaluated and purchasing decisions are shaped. Accenture’s new Consumer Pulse Research 2026 provides new consumer-side signals about how…
Toward a More Mature Culture of Experimentation
A/B testing is one of the most valuable tools in modern digital product development. Used well, it gives teams something rare and precious: causal evidence. Instead of relying on hierarchy, opinion, intuition, or the most persuasive person in the room, teams can expose different users to different experiences and measure what actually happens. The advance…
Agency, Autonomy, and Intelligence: What Makes an Agent Agentic?
In the first two posts in this series, I explored why it may be useful to think of agentics as a way of studying AI agents more systematically. The first post asked why we might need a science of agents at all. The second looked across disciplines to ask what different fields mean by “agent,”…
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