This guide explores how application security must evolve in an AI-driven development world where speed outpaces traditional security approaches. It argues that legacy tools focus too much on aggregating alerts instead of validating real risk. Modern ASPM platforms shift to exploitability-based prioritization by correlating code, cloud, and runtime context to identify true attack paths. The guide also highlights the importance of securing AI-generated code, integrating security into developer workflows, and using AI agents for validation, investigation, and remediation. The key takeaway is that effective ASPM reduces noise and delivers actionable, context-driven fixes—aligning security and engineering around real risk reduction.

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