AI agents are getting a lot of buzz lately. From planning vacations to writing code, it feels like they can do just about everything—right? Well, not quite.
AI agents can do some impressive things. But they also have limitations that are easy to overlook. If you’re thinking about using or building with AI agents, it’s worth knowing both sides of the story.
Let’s dive into what these agents are genuinely capable of—and where they still fall short.
1. What Exactly Is an AI Agent?
At the simplest level, an AI agent is a system that can perceive its environment, make decisions, and act on those decisions—often with minimal human guidance. Think of it like a digital intern that can follow instructions, learn over time, and sometimes even solve problems on its own.
They’re often powered by large language models (LLMs) like GPT-4 or Claude, and connected to tools like web browsers, APIs, databases, and more.
2. What AI Agents Can Do (Really Well)
Execute Tasks Without Hand-Holding
Once you give an AI agent a goal—like “research top SaaS competitors”—it can independently break it down, search the web, summarize data, and even organize it into a report.
Handle Repetitive Processes
From categorizing emails to generating weekly reports, AI agents are consistent, fast, and tireless.
Use Multiple Systems
Agents can pull from CRMs, spreadsheets, and alert tools like Slack—all while keeping track of the task at hand.
Plan and Adjust
They’re capable of breaking tasks into subtasks and adjusting strategies mid-process if something doesn’t work.
Scale Tasks with Consistency
Deploy one or one hundred—the output stays consistent. That’s a huge win for operational efficiency.
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