Eli Cohen on Continuous AI Security Testing and Validation

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    Video summary

    Eli Cohen argues that AI-assisted coding increases the need for continuous application-security testing. Static analysis can identify suspicious patterns cheaply, while dynamic checks and human understanding help establish whether a finding matters in the application's actual business context.

    Eli Cohen describes an orchestratorAgent orchestration coordinates AI agents, tools, people, tasks, state, and control flow so a larger workflow reaches a verified outcome. that delegates reconnaissance and focused testingAI agent delegation assigns a bounded task, context, authority, and expected result from one participant to an agent or another agent. to specialized agents. A separate judging step checks proposed exploits and gathers reproducible evidence, rather than trusting an agent's first claim or treating every scanner alert as a confirmed issue.

    Eli Cohen presents this as a vendor's architecture and discusses evaluation questionsAgent evaluation tests whether an AI agent completes tasks correctly, consistently, and within its required boundaries. around coverage, false positives and useful remediation. The talk is not an independent benchmark, and its promotional comparisons do not establish general superiority.

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    Eli Cohen against a black background beside the blue and white headline Validate The Finding. Framed in blue with WWW.ARTIFICIAL-INTELLIGENCE.VIDEO, 7 October 2026 and duration 19m 28s.

    Eli Cohen describes a continuous security-testing architecture that combines cheap static checks, contextual testing agents and independent validation before treating a finding as an exploitable vulnerability.