In technology, speed has always been a competitive advantage. But in cybersecurity, this relentless pace – with its rapid deployments, AI-generated features, and shortcuts to market – creates a critical challenge. The faster developers are pushed to innovate, the less time they have to address security issues. This lack of time means that vulnerabilities, misconfigurations, and risky code are often deferred, creating a growing backlog known as security debt.

For years, we’ve assumed we could manage that debt later, but the pace of innovation has changed the equation. The faster we move, the more that debt compounds, and the harder it becomes to pay down.

Today, two powerful forces are relentlessly accelerating this security debt. First, cloud-native development has dramatically increased the pace of delivery, leaving security teams less time to identify and fix issues before deployment. Second, as developers rely on AI assistants to generate large portions of application code, each release now contains far more code. This makes it harder for security to keep up and can result in insecure code reaching production faster than ever.

In fact, some predict that by 2030, AI could produce 95% of all code. And with research indicating that a third of that code may introduce security issues, the scale of our security debt is poised to skyrocket.

The traditional approach of catching vulnerabilities late in the cycle simply can’t keep pace with this new reality. This is compounded by another critical factor: the longer an issue goes unaddressed and the closer it gets to production, the more time, effort, and resources it takes to fix. As a result, security debt will continue to compound, leaving organizations exposed and slowing the very innovation these new tools are designed to accelerate.

To break free from this cycle, organizations must rethink their entire philosophy of what it takes to secure their applications. The shift-left movement in security is already well underway, with many organizations focusing on identifying vulnerabilities earlier in the development lifecycle. But early detection alone is not enough. To truly strengthen application security, we need to evolve from simply finding issues to actively preventing them—embedding security so seamlessly into development that insecure code never has the chance to reach production.

From security debt to prevention-first development

This goal is achievable, but it requires a new architectural mindset built on one core principle: complete context drives prevention. Organizations need a unified understanding of their application posture, from code to cloud, to craft more targeted prevention policies, prioritize risk with precision, automate remediation, and align security more closely with business priorities.

For starters, developers are often overwhelmed by a flood of security alerts, many of which are low priority or ambiguous. This constant noise slows innovation and can lead teams to bypass critical safeguards. To address this, organizations need to focus on the issues that truly matter and understand them in the context of the entire application, from code to cloud. With this full view of the highest risks, security becomes a natural part of the development process, reducing friction for developers while keeping innovation moving forward.

With a complete, code-to-cloud view of risk, organizations can then create intelligent guardrails that automatically block the most critical issues before they reach production, while letting other development continue smoothly. This approach not only prevents problems before they escalate but also significantly reduces the time and effort spent on fixes. For example, our own Infosec team at Palo Alto Networks has seen remediation of existing issues accelerate by 52% and has reduced developer time spent on fixing issues by 90% simply by finding and fixing at the source. This allows application security teams to reduce application risk with precision and keep pace with the speed of modern development.

This context-driven, prevention-first model prevents new risks while also giving teams the tools to address the existing backlog at scale. And with a single view of their applications’ posture, teams can move beyond chasing alerts and focus on the security issues that truly matter.

Integrating security directly into developer workflows with real-time feedback and automated remediation suggestions in the tools they use every day also encourages collaboration between security and development teams. This approach makes it easier to resolve existing issues while catching new ones early, when fixes are fastest and most cost-effective.

Keeping pace with AI-driven development

With development accelerating as AI-generated code and vibe coding enter the mainstream DevOps process, vulnerabilities are appearing faster than ever, creating a compounding backlog that threatens both speed and innovation. A prevention-first approach that uses complete code-to-cloud context and embeds security earlier in the development process means preventing risks before they reach production, reducing friction for developers, and ensuring innovation continues at the pace the business demands.

This philosophy is built into the Application Security Posture Management (ASPM) platform, which applies intelligent, context-driven prevention policies to both new and existing code. By integrating real-time feedback into developer workflows and prioritizing the issues that truly matter, teams can address their security debt while staying ahead of emerging trends like AI-generated applications.

Learn more about how ASPM enables prevention-first security and empowers faster, safer innovation.