Managing the AI Surge: Governing & Scaling in the AI Era
summary
AI multiplies repos, commits and artifacts into an automated deluge where binaries become the primary output and agents both write and deploy code, creating 48% vulnerability rate in generated code and an industry where Gartner predicts 70% agent remediation by 2028 and 30% severe incidents. Examples include a July 2025 incident where Replit wiped a production database. Practical controls described: guarded gates, an “upsec-on-your-shoulder” remediation agent, MCP and skill registries, JFrog Artifactory + security curation + AI catalog, evidence-based promotion flows and environment isolation.
AI-written summary · about
chapters (13)
- 0:00Introduction and trust in AI
- 2:00AI trust parallels with TV technology
- 4:23AI-driven software supply chain challenges
- 9:10Verification debt and new risks
- 12:24Context and software integrity
- 14:42AI-generated code security risks
- 17:40Securing AI coding agents
- 21:04Agents beyond coding in supply chain
- 23:21Governance for AI agents
- 27:15Defining AI-driven software
- 30:54AI SBOM and governance needs
- 32:08Managing MCP and skill risks
- 34:45Summary and call to action
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