Rise of the Planet of the Agents

6 min Read

What can go wrong when AI agents call all the shots?
(2025 is the unoffical year of the AI agent.)

By now, most of us should be quite convinced that 2025 is the “year of the agent”. This is of course natural, given the high fequency of news reports on the rapid progress of AI. From passive chatbots who understand complex queries, to today’s client-facing assistants, who can proactively execute multiple tasks on behalf of humans.

First, a quick definition of AI Agent

Although as yet there’s no single, official definition of an AI agent, we could  agree that agents are a version of large language model chatbots that if given autonomy to ‘act’ in the ‘real’ world, which are able to ingest information (read, update & self-train) and do at least one of the following:

  • Navigate digital space (make calls, operate softwares, etc.)
  • Take physical action (sight, motion, etc.)

 
Today’s sales agents can analyse incoming email and act on the good ones. And programming agents have become the de facto sidekicks of coding teams. Companies have also launched “agentic browsers” that can book tickets and order groceries for us.

 

Think about it: the basis of human intelligence is a combination of humongous memory of historical data with speedy access via a set of statistical routines.

  • Why statistics? Because that is the only way to process humongous data.
  • Which statistical routines? Those which associate past data with ‘successful’ outcomes.
One-man Startups

Here’s a possible real-life scenario of what could go wrong in one-man startups which run totally on AI agents.

Let’s take CX agents for example. Like all humans, they must routinely trained to answer in the affirmative tone for a positive customer experience. How soon before the affirmative tone auto converts into white lies & then to baseless commitments (even if occasional)?

Since these agents are also empowered to communicate freely with each other – both internal & client-side agents – what will prevent them to update clients with insufficient basis of truth? (May be after ‘talking’ to other internal product management agents, just like us humans.)

Finally, what happens when these agents learn to fabricate messages? And what if the company remains blissfully unaware of what the agents discuss with each other?!

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