Because software code is a language, LLMs are becoming superhuman coders. This makes them incredibly effective at finding system vulnerabilities for hacking (offense). However, this exact same capability makes them equally powerful for identifying and fixing those flaws (defense), leading to a rapid escalation in cybersecurity.

The same AI technology amplifying cyber threats can also generate highly secure, formally verified code. This presents a historic opportunity for a society-wide effort to replace vulnerable legacy software in critical infrastructure, leading to a durable reduction in cyber risk. The main challenge is creating the motivation for this massive undertaking.

While AI can be used to create exploits, its greater impact is on security. AI tools empower a vastly larger pool of contributors to scrutinize open codebases, identify flaws, and submit patches, strengthening the ecosystem faster than is possible in a closed environment.

Advanced AI cyber tools like Anthropic's Mythos don't create new vulnerabilities; they excel at discovering existing, dormant bugs in human-written code. Their proliferation will catalyze a one-time, industry-wide upgrade cycle, ultimately hardening global infrastructure and leading to a more secure equilibrium between AI-powered offense and defense.

Palo Alto Networks' CEO explains that AI tools are discovering software vulnerabilities at an unprecedented rate. This will cause a short-term deluge of patches, but it's effectively cleaning up years of bad code and will ultimately strengthen the entire ecosystem.

While AI enhances offensive capabilities, its greatest potential may be defensive. Easterly posits an optimistic future where AI models become so adept at finding and fixing vulnerabilities in code that they effectively 'end cybersecurity as we know it,' leading to a new era of inherently secure software, much like modern cars are inherently safer.

The narrative of AI models 'breaking out' and finding zero-day exploits is less about emergent superintelligence and more about the inherent flaws in legacy software written by humans. In the future, as AI writes most of the code, these security holes will become far less common because machines won't make the same tedious errors.

The long-term trajectory for AI in cybersecurity might heavily favor defenders. If AI-powered vulnerability scanners become powerful enough to be integrated into coding environments, they could prevent insecure code from ever being deployed, creating a "defense-dominant" world.

While AI will increase cyber risk by enabling faster vulnerability scanning and generating potentially insecure code, it will also be the solution. AI agents will be needed to review code and defend systems, creating a massive new market for "agentic security" companies.