Insights from experts shaping secure development

El desarrollo asistido por IA ya no está en el horizonte: ya está aquí y está cambiando rápidamente la forma en que se escribe el software. Herramientas como GitHub Copilot, Cline, Roo, Cursor, Aider y Windsurf están transformando a los desarrolladores en copilotos propios, lo que permite una iteración más rápida y acelera todo, desde la creación de prototipos hasta los principales proyectos de refactorización.

When reflecting on our own technology, SCW’s Developer Risk Management platform, I am buoyed by recent metrics from one of our core enterprise clients, and going down the proverbial rabbit hole into this data tells a tale of a high-adoption, potent Secure by Design initiative that has been proven to considerably reduce risk in their organization.

Secure Code Warrior se complace en anunciar nuestra nueva integración con HackerOne, líder en soluciones de seguridad ofensiva. Juntos, estamos creando un ecosistema poderoso e integrado. HackerOne identifica dónde se producen realmente las vulnerabilidades en entornos del mundo real, revelando el «qué» y el «dónde» de los problemas de seguridad.

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.

Developers have long struggled to truly claim a seat at the table in traditional threat modeling programs, but with the right skills, they have the opportunity to wield AI responsibly to seriously cut risk and rework in their codebase.

AI-generated code may be “made by machine”, but taking a cookie-cutter approach to securing that code would fall well short of mitigating the vulnerabilities LLMs can introduce. Organizations need to establish precise security reviews, with human developers anchoring the process to implement effective security controls while also managing the specific coding temperament of each LLM used. AI-generated code must undergo the same personalized risk assessments as code written by human developers.

s artificial intelligence (AI) tools become more widely used in the software development process, their impact on security is becoming clearer. According to recent research, nearly 70% of organisations have discovered vulnerabilities caused by AI tools while one in five have experienced a serious incident as a result of those vulnerabilities.

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.

Gartner named SCW twice in the 2026 Hype Cycle for Secure Software Engineering. Here's why it matters for AI-driven development.