đ What Actually Makes an Agent... an Agent?
The term "agent" gets thrown around a lot these daysâoften used to describe any API interaction with a large language model (LLM).
But letâs be real: asking OpenAI to summarize a text isnât an agentâitâs just a fancy API call.
Often, we call elaborated AI + Automation systems "agents", when we should rather call them "copilots" or simply "automation systems".
So, whatâs a true agent?
An agent is more than a simple input-output pipeline. It must:
1ď¸âŁ Intelligently decide its next action:
â Should it execute a task, delegate to another agent, or transition to a new workflow?
2ď¸âŁ Adapt dynamically to context:
â Make context-based decisions and adjust its actions to align with evolving inputs and goals.
I really like how OpenAI frames it:
"An agent packages a set of instructions with various functions (and additional settings) and can transfer execution to another agent."
But hereâs the catch...
Sometimes, you donât want full autonomy.â ď¸
For example:
âĄď¸ A refund-processing agent may require human oversight (human-in-the-loop) to ensure accuracy.
âĄď¸ Outreach agents often include HITL steps, so SDRs can review or tweak messages before theyâre sent.
This intersection of agency + control is exactly what tools like LangChain, 11x, and Relevance AI aim to address.
True agents are adaptive systems, not just glorified scripts. They:
âď¸ Decide and adapt intelligently
âď¸ Combine dynamic decision-making with pre-set workflows
âď¸ Seamlessly transition tasks or delegate to other agents
Automation is about following a predetermined path.
Agency is thinking and deciding.
Just as a co-pilot makes you twice as productive, but an autonomous agent lets you hand over the work entirely.
Whatâs your take? Are we too loose with the term âagentâ?
PS: Gotta admit, Iâve made this mistake myself.