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AI Test Automation
On-demand Webinar
On-demand Webinar

Beyond Code: Harnessing AIs potential across the SDLC | Harness Resource

Today’s dev teams are racing against tight deadlines, rising complexity, and ever-present security threats. The good news? AI isn’t just hype—it’s a game-changer. From eliminating tedious tasks to catching security issues before they escalate, AI is helping developers ship better software, faster and more securely.

In this information-packed Tech Talk, veteran technology journalist John K. Waters talks with AI innovation leader Pranav Rastogi about how teams are moving beyond code generation to smarter testing, streamlined deployment, and continuous security—all while staying within enterprise guardrails.

You’ll learn how to put AI to work for:

  • Automated code creation and documentation
  • Accelerating unit and end-to-end testing
  • Triaging and fixing security vulnerabilities
  • Enforcing policy with tools like Open Policy Agent
  • Building continuous verification into your CI/CD pipeline

Whether you're scaling DevOps or rethinking secure software delivery, this conversation will give you the playbook for AI-powered productivity with real-life user stories.

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Published
January 1, 2024

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What you'll learn

Key Takeaways

Augment Existing Developer Workflows

AI tools should integrate into current environments to minimize the cost of context switching. Forcing developers into completely new toolchains reduces overall efficiency.

Accelerate Automated Test Generation

AI significantly reduces the time required for test creation and maintenance. It also provides vital context to edge-case testing, improving upon traditional fault-injection methods.

Enforce Strict Code Generation Guardrails

Organizations must implement security and compliance checks before deploying AI-generated code. Tracking open-source attribution and maintaining visibility mitigates long-term security risks.

Simplify Policy Creation and Governance

AI helps translate complex languages to generate Open Policy Agent rules. Teams can then enforce these policies using standard templates and role-based access controls.

Protect Proprietary Customer Data

Enterprise AI platforms should avoid training models on proprietary customer code. Utilizing sanitized pipeline execution logs ensures intellectual property remains secure.

Transform Rather Than Replace DevOps

AI will not replace engineering teams but will act as a collaborative peer programmer. DevOps professionals will transition to supervising intelligent agents and analyzing context.