Insights from experts shaping secure development

Post-quantum cryptography (PQC) is critical for protecting data from quantum computing threats. Learn how “harvest now, decrypt later” exposes risk and how developers can prepare for quantum-safe security.

Recently we interviewed some of the future leaders in the secure development or “DevSec” world and found their individual career paths into cybersecurity fascinating. For those of you out there wishing to become a security champion, jump into the elusive AppSec realm, or even just learn more about secure coding, here are the stories from three security professionals with a background in development, about how they got interested in security and the security lessons they wish every organization would follow.

Kamer van Koophandel shares how it embedded secure coding into everyday development through role-based certifications, Trust Score benchmarking, and a culture of shared security ownership.

See how Paysafe's partnership with Secure Code Warrior led to a 45% boost in developer productivity and a major reduction in code vulnerabilities.

DigitalOcean's use of Secure Code Warrior training has significantly reduced security debt, allowing teams to focus more on innovation and productivity. The improved security has strengthened their product quality and competitive edge. Looking ahead, the SCW Trust Score will help them further enhance security practices and continue driving innovation.

The concern is straightforward: development teams may place undue confidence in AI tools that are not equipped to interpret the nuanced context in which many security vulnerabilities arise. Large language models, for instance, can struggle to understand an application’s authentication or authorisation architecture, increasing the likelihood of missing critical safeguards.

Industry guidance on managing the risks of AI-generated code increasingly points to the same conclusion: effective safeguards rely on close collaboration between humans and machines, with developers remaining firmly in the loop.

Agentic artificial intelligence (AI) is set to reshape the enterprise landscape in the Asia-Pacific and Japan (APJ) region in 2026, according to industry executives. Organisations are expected to embrace increasingly autonomous software agents, raising both productivity and new categories of risk across business domains.

See how 16 leading AI models actually code, scored across 11 real-world frameworks and 1,760 codebases — the framework matters as much as the model.

AI risk doesn't stop at engineering. Get the one-pager on Citizen AI — build AI literacy and safe habits across your whole workforce.

From AI autocomplete to autonomous agents—explore how software development is evolving and what it means for security, governance, and your team.