Now Entering: The Era Of Bleh

Aaron Horwath is the director of AI operations at a creative technology company where he is focused on implementing AI in a way that supports both humans and business. To start his week, Lukas Weber, a 28-year-old copywriter for a mid-sized SaaS company, first checks on the small army of AI agents he has built and now manages. It’s been part of his daily routine since his company’s “AI-first” mandate at the start of the year.

His agents have been busy. One agent has pulled in all the industry news from the past week and combined it with customer calls to identify potential newsletter topics. That agent has since handed off its findings to a copywriting agent that has written drafts for Weber to review and send out.

Another has identified prospective clients visiting the company website and, based on their activity, sent each a custom proposal. Another agent has analyzed the data from a recent campaign and, noticing some concerning trends, reached out to Weber to take a look. Yet another has responded to unread emails, and the drafts sit ready to review in Weber’s inbox.

Our team has downsized this year, so I’ve become responsible for a wider range of our marketing activity, and the agents help me keep up.” Weber is not unique. From HR to Sales to Customer Success to Engineering, his colleagues across the company start their days the same way: checking in on agents, reviewing their work, following up on their insights gathered and analyzed from across the organization. An increasingly large portion of the cognitive load employees were paid to execute just a year ago is now outsourced to AI.

This is what every AI-bullish tech executive describes as what great looks like when it comes to AI adoption: everyone using AI for everything; human knowledge workers sitting above teams of agents all built on the same small ecosystem of LLMs. And it’s not just Weber’s company. It’s also their competitors, who are checking on their AI agents built to execute similar tasks.

And those agents are all built on the same small ecosystem of LLMs as Weber’s. It’s a funny predicament: all day, humans across the same industry — ostensibly hired for their unique critical thinking and experience — collectively pump every thought, business challenge, idea and solution through the same set of AI tools. Almost as if all these companies have simultaneously hired the same single employee: Mr.