Google just announced Gemini 3 and described it as a step toward “more autonomous, agentic AI.” This follows OpenAI calling their latest features “agentic.” And Salesforce. And Microsoft. And approximately every other company that ships software in 2025.
I need to get something off my chest: the word “agentic” has become completely meaningless.
A chatbot that calls one API is not an agent. A workflow that runs a for-loop over prompts is not an agent. A model that can browse the web is not an agent. Slapping “agentic” on your product because it does more than one thing is marketing, not engineering.
What an Agent Actually Is
An agent is a system that can do four things in a continuous loop:
Sense. It perceives its environment. Not the user’s prompt alone, but the broader context: what tools are available, what state the world is in, what has changed since the last interaction.
Think. It reasons about what to do next given its goal and its understanding of the current state. Planning, evaluating options, considering consequences. A next-token predictor with a system prompt doesn’t qualify.
Act. It takes action in the world. Calling tools, modifying data, triggering workflows, producing observable effects.
Remember. It retains information across interactions and uses that information to improve future behavior. Across sessions and tasks, not within a single conversation.
Sense. Think. Act. Remember. That’s the agentic loop. If your system does all four, it’s an agent. If it does two or three, it might be a useful tool, but calling it an agent sets expectations it can’t meet.
Why the Distinction Matters
This isn’t pedantry. The conflation of “does AI stuff” with “is agentic” is actively harmful to AI adoption.
When a CTO tells their board they’re deploying “agentic AI” and what they’ve actually deployed is a chatbot with a few API integrations, they’ve set expectations that the technology will behave autonomously, learn from interactions, and improve over time. When it doesn’t (because it’s a chatbot with API integrations), the board loses confidence. The team loses credibility. The next real AI initiative faces an uphill battle for funding.
I’ve seen this exact cycle play out with every buzzword in technology. “Cloud-native” got slapped on VMs with a Kubernetes wrapper. “Machine learning” got slapped on hand-coded rules with a model.fit() somewhere in the pipeline. “IoT” got slapped on anything with a WiFi chip. Each time, the dilution of the term made it harder for the people doing the real work to get taken seriously.
“Agentic” is going through the same dilution right now.
The Framework in Practice
At Vestmark, we built a product called Vestmark Pulse around the Sense-Think-Act-Remember framework explicitly, because we wanted to build something that actually earns the label.
Sense: Pulse continuously monitors data streams. It doesn’t wait for a user to ask a question. It proactively identifies situations that require attention.
Think: When Pulse finds something interesting, it reasons about what action would be appropriate given the full context. Multiple factors, competing priorities, domain-specific constraints.
Act: Pulse drafts communications, prepares recommendations, generates reports, and surfaces insights. These actions have real effects in the user’s workflow.
Remember: Pulse learns from each interaction. When a user consistently modifies its recommendations in a particular way, the system adapts. It gets better over time because it retains and applies what it learns.
But here’s the thing: I could apply this framework at any company in any industry. The Sense-Think-Act-Remember loop is a universal architecture for autonomous systems. I used a version of it when thinking about IoT automation at Xively. I saw it in how Alexa’s skill platform evolved at Amazon. The industry matters less than the pattern.
A Challenge
If you’re building AI products, run your feature set through the Sense-Think-Act-Remember framework. Be honest about which loops are complete and which ones have gaps.
If your system only acts when prompted by a user, the Sense loop is incomplete. That’s fine. Build a great reactive tool. Call it what it is.
If your system doesn’t retain information across sessions, the Remember loop is incomplete. Also fine. Build a great stateless assistant. Call it what it is.
There’s nothing wrong with building tools that aren’t agents. The vast majority of useful AI products are not agents. The problem is calling them agents anyway because it sounds better in a pitch deck.
Words matter. Call your product what it is, build it well, and let the results speak for themselves.