Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

AI for Career Development: From Skill Assessment to Professional Growth

Most professionals don't have a clear picture of how their skills compared to what employers are actually looking for. This is a gap that career coaching has traditionally tried to fill, but the process was often slow and based on limited information. AI now makes it possible to assess your skills accurately and get direct, data-backed guidance on what to improve. In this article, we'll look at how AI is changing skill assessment, professional growth, and the broader career development process - from the moment you evaluate your abilities to the moment you land a role that actually fits.

Security Interviews Should Leave Room for What Remains Unknown

An incident story can sound impressively clear once everyone knows how it ended. The suspicious login becomes an obvious warning, the escalation looks inevitable, and the response appears to follow a straight path. A security interviewer needs to look earlier in the story, when the candidate had incomplete information and still had to choose what to do.

Corelight Agent Builder Library: AI Investigation Demo

What happens when you ask a generic SIEM AI assistant and a Corelight-powered threat hunter agent the exact same question about a suspicious IP? The difference is not the model. It is the investigation expertise. In this demo, we walk through a side-by-side comparison using Elastic's agent builder. A default AI assistant returns a surface-level summary. An agent built with the Corelight Agent Builder Library identifies lateral movement, flags potential ransomware and data exfiltration, surfaces IDS alerts, maps involved hosts, and recommends next steps.

AI Agent Security: Detecting Risky Behavior (Live Demo)

Watch five AI agents tackle a CTF and start coordinating with one another. Learn how to detect risky agent behavior using @goteleport graphs, risk scoring, and custom classifiers. Ben Arent explores lessons from the Hugging Face incident, then demonstrates how agent identity, scoped access, and activity monitoring help secure AI agents running against infrastructure.

The AI Agent Whose Builder Already Left

Somebody in operations builds an automation inside a sanctioned platform to solve a problem in their own workflow. It works, other people come to depend on its output, and eighteen months later that person leaves. ‍ The platform still lists the automation. Nobody inherits it, because it was never anybody's asset to begin with, and the offboarding checklist has no line for a thing that was never recorded as belonging to the person departing. ‍

Agentic AI for ITOps: Is your organization ready for the security challenges?

AI is set to provide increasing value in IT by enabling more ways to simplify complex IT operations, offering actionable insights, automating routine tasks with context-aware automation, and detecting abnormal events with advanced machine learning algorithms. With agentic AI, systems can understand what is happening in an IT environment, reason about the most probable root causes, determine the right course of action, and implement these changes without requiring additional human intervention.

AI Governance for Content Nobody Has Released Yet

Confidential data is usually something to protect indefinitely. Customer records, financial results, contract terms and personal information all need the same treatment next year as this year, so controls are judged on how well they hold over time. ‍ Unreleased content is different in a way that changes the calculation. Its commercial value depends entirely on not existing publicly yet, and on release day that requirement disappears completely.

The answer to AI uncertainty is adaptability, not paralysis

AI uncertainty is not a strategic reason to wait; it is a strategic imperative to build adaptable organizations that can innovate confidently, govern risk proportionately, and respond effectively as technology and threats evolve. Every few weeks, the AI conversation seems to reset around a new warning. A model demonstrates an unexpected capability. An autonomous agent behaves in a way its designers did not anticipate. A new forecast describes how quickly AI could transform work, security or society.

Engineered for Trust: How We Built the AI Trust Engine

The rapid advancement of frontier AI models has fundamentally changed how security products are built. Capabilities that once took months to develop can now be delivered at machine speed, and the market is filling up with agentic security operations centers (SOCs). Numerous vendors now promise AI agents that can investigate alerts, correlate evidence, reason over complex signals, and even close incidents on their own. The technology appears capable, but what often gets left out is a reason to believe it.