The traditional 90-day vulnerability disclosure window, a cornerstone of coordinated security for decades, has effectively collapsed. Research published today by Himanshu Anand argues that the integration of Large Language Models (LLMs) into offensive security tooling has compressed the time between patch release and weaponized exploit from weeks to minutes. The core of this shift is 'Automated Diff Analysis.' In one case study involving a React security patch (CVE-2026-23870), an LLM was used to analyze the code changes, identify the vulnerable logic path, and generate a working Proof-of-Concept (PoC) in under 30 minutes. This bypasses the human reverse-engineering bottleneck that previously gave defenders a 'patching head start.' Furthermore, we are observing a phenomenon of 'Vulnerability Convergence.' Because AI-assisted scanners are now widely available, multiple independent researchers (and threat actors) are discovering the same zero-days simultaneously. In a recent report, a vendor noted that 11 different researchers reported the same P0 vulnerability within a six-week window. This convergence means that an embargo no longer contains a secret; it merely provides a race condition. The Linux Kernel exploits 'Copy Fail' (CVE-2026-31431) and 'Dirty Frag' (CVE-2026-43284) further illustrate this, where public PoCs appeared within days of the initial AI-driven discovery. The strategic implication is profound: the defense can no longer operate on monthly or even weekly patching cycles. We are entering an era of 'Real-Time Defense,' where security must be integrated at the PR-level (Pull Request) using the same AI tools that the attackers are using to find the flaws. The 90-day window is not just failing; it is a dangerous illusion of safety in an AI-accelerated threat environment.