“Agentic” is one of the most overused terms in AI right now.
Some people call a chatbot agentic.
Others say it’s only agentic if it can take actions.
Some teams label any workflow automation as an “agent.”
In many real-world projects, this leads to a familiar challenge: long debates on whether a solution is truly agentic — and if it is, what level of autonomy or intelligence it can realistically claim.
A helpful way to cut through the noise is to think of agentic systems as a progression of capabilities, rather than a binary label.
Below is a simple breakdown of agentic maturity levels, based on logic and capability. This framing is adapted from Google’s agent learning materials shared as part of the “5-Day Agents” guide at https://www.kaggle.com/learn-guide/5-day-agents
Agentic Levels: From Simple to Advanced
| Agent Level | Name | Progression Logic | Capability |
|---|---|---|---|
| 0 | Core Reasoning System (“Brain”) | Operates in isolation using only pre-trained knowledge. No tools (“hands”) and no memory, so it can’t react to new real-world information. | Explains concepts, answers questions, and creates theoretical plans based on what it already knows. |
| 1 | Connected Problem-Solver | Adds tools/APIs so it can Act and Observe, overcoming real-time blindness. | Checks live information (e.g., sports scores), queries internal systems, uses RAG to fetch enterprise knowledge. |
| 2 | Strategic Problem-Solver | Uses context engineering to manage multi-step goals by selecting the right information for each stage of execution. | Solves multi-part tasks like calculating a midpoint and using it to trigger focused follow-up searches or actions. |
| 3 | Collaborative Multi-Agent System | Scales through delegation: a “manager” agent assigns sub-tasks to specialist agents (treated like tools). | Automates full workflows by dividing work across agents (research, coding, marketing, etc.) and combining outputs. |
| 4 | Self-Evolving System | Uses meta-reasoning to detect capability gaps and autonomously create new tools or sub-agents to fill them. | Expands its own skillset on the fly (e.g., creates a sentiment-analysis specialist, tests it, and adds it to the team). |
So the next time the conversation shifts to “agentic or not,” this table can help teams align quickly — and focus on the real question:
What level of agentic capability are we building, and what level do we actually need?
Team Cennest!