Runtime Protection Agent
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On-demand Webinar
On-demand Webinar

From DevOps to AI-Powered DevSecOps: Building the Modern Platform Engineering Stack | Harness Resource

DevOps is evolving. Security is no longer a separate team's problem. It is becoming a core responsibility of platform engineering and DevOps teams. That means expanding your thinking beyond pipelines and deployments to include application security testing, runtime protection, and AI security as first-class citizens of your delivery platform.In this session, we'll break down the five pillars of a modern DevSecOps platform: powerful pipelines, end-to-end governance, safe releases, pipeline-native security, and AI-powered automation. Then we’ll go deep on the pieces most DevOps teams are still figuring out: how to build a mature, integrated security posture and leverage AI to accelerate and optimize your entire software delivery lifecycle.Key Takeaways:Why security and AI are becoming core responsibilities of platform engineering and DevOps teamsThe five pillars of a modern DevSecOps platform and how to evaluate your gapsHow to embed security across the pipeline, from SAST/SCA and supply chain protection to runtime API securityHow AI can automate toil, surface insights, and accelerate delivery across your entire DevSecOps platformHow to make the case internally for expanding your DevOps program to include security and AI

Published
March 31, 2026

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What you'll learn

Key Takeaways

AI Code Generation Increases Production Risks

AI has accelerated code creation by up to five times, but it also multiplies attack surfaces. Consequently, nearly three-quarters of deployments linked to AI-generated code encounter problems.

Integrate Security Natively Within Pipelines

Modern development requires security tools that deploy instantly without lengthy per-repository configurations. Pipeline-native security ensures holistic governance and rapid scaling across thousands of pipelines.

Enforce Strict Governance for AI Agents

As AI agents modify and generate pipelines, organizations must maintain strict audit trails and granular access controls. AI agents should strictly inherit the role-based permissions of their assigned users.

Implement Continuous Verification for Safe Releases

Safe software releases rely on continuous verification using telemetry data and progressive delivery techniques like feature flags. Teams must establish automated controls to instantly roll back problematic deployments.

Prioritize Vulnerabilities Using Runtime Context

Organizations should use runtime insights to evaluate the actual risk of security vulnerabilities. Identifying whether flawed code runs in an internet-facing application helps teams prioritize critical remediations.