WHAT IS AN
AI AGENT?
A no-nonsense guide to one of AI’s buzziest – but most misunderstood – concepts.
Introduction: Navigating the Buzz Around AI Agents
If you’ve been paying attention to AI lately, you’ve likely noticed one term rising above the rest: AI agents. But despite all the buzz, the definition is still fuzzy – even for the experts:
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“Even A16Z VCs Say No One Really Knows What an AI Agent Is” – TechCrunch (May 2025)
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“No One Knows What the Hell an AI Agent Is” – TechCrunch (March 2025)
This page is here to change that. We’ll explain exactly what AI agents are, how they work – especially in cybersecurity – and what separates them from the chatbots, copilots, and automation tools you already know.
Understanding AI Agents Through Everyday Analogies
Think about driving to a new destination.
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Using GPS is like having a co-pilot. It gives you directions, but you’re still the one doing the driving.
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Using a self-driving car is like using an AI agent. It perceives the environment, makes decisions, and gets you where you need to go –autonomously.
That’s the difference. Where copilots assist, agents act.
Core Characteristics of AI Agents
To be considered a true AI agent, a system must do more than run tasks. It must:
Have a goal
Examples include: “Determine if this user is allowed to use a VPN", "Is this URL malicious?".
Perceive its environment
Understand the context of data, the infrastructure, and the relationship between entities.
Use tools
AI Agents have access to tools based on their mission to perform investigations.
Make decisions
Based on responses, agents then form conclusions.
Adapt over time
Agents are able to improve based on new information and past outcomes.
Operate autonomously
AI Agents must be able to perform their mission without human prompts.
Real-World Applications in Cybersecurity
At 7AI, we build and deploy AI agents specifically for cybersecurity. Here’s how they work in practice:
Mission Agents
Handle alert ingestion. They determine what type of alert it is (EDR, DLP, phishing, etc.), enrich the data, and deploy specialist agents for investigation.
Specialist Agents
Have narrow goals and deep focus. For example:
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A URL Reputation Agent submits suspicious links to tools like VirusTotal, reasons through the results, and decides whether they are malicious.
- A File Inspection Agent detonates a file in a sandbox to determine whether it is malicious.
- Third Example Agent - Let's pick one and describe what it does.
Dynamic Pivoting
Once a malicious threat is identified, agents:
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Query systems like your SIEM to identify blast radius
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Investigate other users, endpoints, or files potentially affected
Determination and Recommendations
Agents collaborate to form a conclusion and deliver a remediation recommendation. While 7AI uses read-only APIs today, remediation capabilities are coming soon.
Common Misconceptions About AI Agents
Myth |
Reality |
|---|---|
| Just automation | Agents reason, adapt, and act |
| Like SOAR playbooks | SOAR is rule-based; agents are autonomous |
| Just chatbots | Agents don’t need prompts—they work independently |
| Untrustworthy | Task-specific agents + tools = no hallucinations |
| Future tech | 7AI agents are working in production today |
FAQs: Clarifying AI Agents in Cybersecurity
Q: How is this different from automation or SOAR?
A: SOAR uses rigid logic and workflows. AI agents reason dynamically and learn from outcomes, making them more flexible and effective.
Q: Don’t LLMs hallucinate?
Q: What about prompt injection attacks?
Q: Is this just a co-pilot?
Q: Do AI agents actually work today?
Q: What types of tasks are best suited for AI agents in cybersecurity?
Q: DO 7AI AGENTS TRAIN ON MY DATA?
THE AGENTIC SECURITY REVOLUTION IS HERE.
Find out how 7AI can transform your security operations with swarming AI agents.