One of the most influential publications on real-world AI system design is Anthropic’s guide, Building Effective Agents. Its core message is simple:
Effective AI requires structure first, adaptability second.

Anthropic emphasizes that AI agents work best when:

1. A deterministic workflow does all the structured work up front
   
2. The agent only activates when uncertainty remains
   
3. The agent begins with full context, not an empty slate
   
4. Tool usage is controlled and evidence-driven
   
5. Human-in-the-loop remains central for oversight and trust
   

These principles ensure accuracy, avoid hallucinations and keep investigations reproducible, all critical requirements for cybersecurity.

Intezer Forensic AI SOC is built on exactly this philosophy. Our platform uses a dual-mode design with Intezer AI Workflow and AI Agent, completely aligning with Anthropic’s best practices to deliver fast, scalable and highly accurate investigations across a broad range of alerts, all while keeping analysts in the loop.

Here is how Intezer implements Anthropic’s best practices for agents.

Structured first: Intezer AI Workflow handles the majority of alerts

Anthropic advises that AI systems should begin with deterministic workflows instead of free-form reasoning. In cybersecurity, this is essential for accuracy, auditability, trust and scalability (when handling huge volumes of alerts).

Intezer’s AI Workflow mode is a structured triage process designed by security experts and executed with strict consistency. It applies AI only at key decision points, not as the driver of the entire investigation.

This approach provides:

• Deterministic, reproducible results
  
• High speed due to streamlined, parallelizable steps
  
• Lower costs because heavy reasoning is used sparingly
  
• No drift or unexpected branching
  
• Clear human oversight points
  

Most alerts, especially well-defined ones, are fully resolved at this stage, giving SOCs broad alert coverage at low cost.

Adaptive only when needed: Intezer AI Agent extends the investigation

Anthropic states that agents should activate only when the structured workflow reaches uncertainty, and only after they inherit the full context. Intezer follows this exactly.

AI Agent mode activates only when the Workflow cannot reach a high-confidence verdict.

At that point, the agent:

• Starts with all evidence collected so far
  
• Avoids premature assumptions
  
• Uses tools deliberately and contextually
  
• Expands the investigation where human analysts would
  
• Surfaces deeper behavioral patterns or cross-asset correlations
  

This ensures the agent is guided, not free-floating, and its decisions remain grounded in evidence, not guesswork.

Tools the AI Agent can leverage once activated

• Dynamic SIEM queries
  
• EDR/XDR telemetry lookups
  
• Identity provider (IDP) investigation
  
• Behavioral analysis of processes and command lines
  
• User activity mapping
  
• Process ancestry and parent-child correlation
  
• Intezer’s historical alert database
  
• Code DNA similarity and malware lineage tracking
  
• Additional host, memory, or file-based forensics

The result is deeper investigation where it matters, without unnecessary cost.

Human-in-the-loop by design

Intezer keeps human analysts at the center so they can review and override conclusions, and trace every decision made by Intezer. Of course, all evidence and reasoning is grounded in forensic data and is fully transparent and explainable for beginners and advanced analysts alike.

This aligns with Anthropic’s principle that humans remain final decision-makers, especially in high-stakes domains like cybersecurity.

How this architecture improves SOC performance

Intezer’s adherence to Anthropic’s best practices produces measurable outcomes across the three most important SOC metrics: accuracy, coverage, and speed, while also reducing cost.

Accuracy

Intezer’s approach of combining deterministic forensics + adaptive AI = best-in-class verdict quality.

• The structured workflow prevents hallucinations
  
• The AI Agent only activates with strong guardrails
  
• Context inheritance ensures consistent reasoning
  
• Analysts always have visibility and control
  

This hybrid approach dramatically reduces false positives and prevents premature conclusions.

Triage of all alerts, including low-severity (where threats often hide)

Because AI Workflows handle the bulk of alerts inexpensively and AI Agents only run when needed, heavy and expensive reasoning calls are minimized

This frees SOCs from cherry-picking which alerts to ingest allowing them to triage and investigate them all.

This is crucial for:

• High-volume enterprise environments
  
• MSSPs with strict SLAs
  
• Cloud-scale detection pipelines
  
• 24/7 monitoring teams
  

You get broad alert coverage without inflating compute costs.

Speed: Structured steps + adaptive depth

• Workflow mode resolves most alerts within seconds
  
• Agents accelerate investigations that normally take analysts hours
  
• No bottlenecks, no backlog, no manual evidence gathering
  

The result is a SOC where every alert is investigated quickly, consistently, and with forensic depth.

Table of how Intezer’s design reflects Anthropic’s guidance

Anthropic best practice	How Intezer implements it
Start with deterministic workflows	AI Workflow handles structured triage with predefined expert steps
Activate agents only when needed	AI Agent triggers only when confidence is insufficient
Give agents full context	Agent inherits the entire Workflow evidence set
Control tool usage	Agent selects tools based on evidence, not speculation
Maintain human-in-the-loop	Analysts can verify, guide, and override conclusions
Prioritize safety and reproducibility	Every action is logged, justified, and traceable

Conclusion: Anthropic’s Agent principles in a real SOC

Anthropic’s framework for building effective agents is now influencing industries far beyond general AI research. Intezer Forensic AI SOC might be one of the strongest real-world implementations of these practices in cybersecurity.

By combining:

• Deterministic workflows for reliable baseline investigations
  
• Adaptive agents for deeper reasoning when needed
  
• Human oversight for trust and accountability
  
• Cost efficiency enabling full-pipeline alert coverage
  

Intezer is able to deliver fast, accurate, and scalable triage that transforms SOC operations.

Learn more about how you can transform your SOC today.

The post Building effective AI for the SOC: How Intezer Forensic AI SOC follows Anthropic’s best practices appeared first on Intezer.

Gartner’s recent Innovation Insight: AI SOC Agents report is an encouraging signal that the concept of an “AI-powered SOC” has reached mainstream awareness. The report recognizes the potential of AI technologies to transform how security operations centers function, especially in augmenting analysts through automation and intelligent workflows.

Yet, while Gartner’s analysis succeeds in capturing the momentum of this space, it falls short in clarifying how and where AI actually fits within the security operations stack. By treating “AI SOC” as a monolithic, undifferentiated category, the report overlooks the crucial distinctions between detection, triage and response, each of which requires a very different kind of AI capability and delivers very different value.

A closer look at Gartner’s analysis 

Gartner’s report provides a valuable overview of how AI SOC can assist with detection, alert investigation, and even response recommendation. We wholeheartedly agree with Gartner’s advice that CISOs should evaluate which security activities are “volumetric, troublesome, or low-performing, and which would benefit the most from augmentation with the application of AI”. However, presenting all of the AI SOC functions (and vendors) as part of a single undifferentiated security ecosystem, can be confusing. 

This broad framing misses the fact that an AI model designed to improve SIEM detection logic operates on entirely different data, architecture, and feedback loops than one built to support analyst decision-making or response automation. The result is a flattening of a nuanced market into one monolithic category, useful for taxonomy, but not for decision-making.

For CISOs, this lack of segmentation makes it hard to answer the key strategic question: Where should we apply AI first to get tangible operational value?

By contrast, our view is that organizations should start by identifying which part of their operations needs augmentation most, then evaluate AI solutions purpose-built for that domain.

A clearer way to frame the AI SOC market

To understand where AI truly fits in and how it can deliver measurable outcomes, it helps to zoom out and look at the broader security operations stack. As we described in a previous blog post, “Making sense of the AI SOC market”, we see three main layers where AI can add value:

Detection (SIEM, XDR)

The first layer converts raw telemetry into actionable alerts. Here, AI can strengthen correlation logic, improve detection models, and reduce false positives. This is largely about data pattern recognition and automation of repetitive analysis.

Triage and Investigation (SOC / MDR)

The middle layer is where human analysts determine which alerts are real incidents worth escalating. This is where AI can truly emulate analyst reasoning, gathering context, cross-referencing intelligence, and presenting likely root causes. Done well, AI here acts as a co-analyst, not a replacement.

Response and Case Management (SOAR)

The final layer coordinates remediation and manages incident workflows. AI can accelerate playbook creation, automate routine case handling, and improve overall response time through dynamic decision logic.

Each layer offers opportunities for AI—but they are fundamentally different problems to solve. When vendors use the term “AI SOC” without specifying which layer they’re addressing, it creates confusion and unrealistic expectations.

A more practical evaluation framework

To move the conversation forward, we recommend a more structured approach to evaluating AI SOC solutions.

Step 1: Identify your target layer

Ask: Which layer of our operations needs the most improvement. Is it detection (SIEM/XDR/Cloud), triage (SOC/MDR), or response (SOAR)? 

This helps narrow the field to the right class of solutions rather than chasing the broad “AI SOC” label.

Step 2: Define measurable outcomes

Especially for alert triage and investigation (which is usually handled by an internal SOC or external MDR), establish metrics to compare performance, such as:

• Reduction in mean time to detect (MTTD)
• Noise reduction rate
• Scale of alert coverage
• Consistency across SOC shifts or analyst tiers
• Triage accuracy

These metrics allow organizations to compare vendors on tangible outcomes, not vague AI promises.

Step 3: Evaluate transparency and integration

An effective AI SOC solution should clearly explain its reasoning, integrate easily with your existing tools, and allow human oversight. The goal is augmentation, not opacity.

Read more about why the “AI SOC agent” narrative misses the point.

The way forward

Gartner deserves credit for bringing visibility to an emerging market, but their analysis underscores how early and fluid this space still is. The future of the AI SOC isn’t one product category. It’s a set of AI capabilities applied intelligently across the detection–triage–response continuum.

Organizations that treat AI as a modular capability rather than a monolithic product will see the most success. The key is knowing your operational priorities and matching them to the layer where AI can have the greatest impact.

Conclusion

AI is not a magic “SOC-in-a-box.” It’s a set of technologies that, when properly targeted, can transform specific parts of security operations. Gartner’s latest report captures the enthusiasm, but not yet the structure, of this market.

At Intezer, we believe the path forward starts with clarity. Understanding the distinct layers of the SOC, the role AI plays in each, and the outcomes that matter most. Only then can organizations cut through the noise and choose the right AI SOC partner for their needs.

Explore how Intezer delivers complete peace of mind for your security operations! 

The post Properly framing the AI SOC conversation  appeared first on Intezer.