The moment has arrived when optimizing your resume for artificial intelligence stops being a competitive edge and becomes table stakes. Job search platforms including LinkedIn, Indeed, Glassdoor, and Greenhouse are now openly advising candidates on algorithm-friendly formatting, clear language, and structured skills data—not as optional tactics but as necessary adaptation to how hiring actually works now. This represents the inflection point where AI-mediated recruiting crosses from experiment to infrastructure.

When hiring platforms start publishing guidance on how to optimize for their own algorithms, the underlying technology has crossed a critical threshold. It's no longer bleeding edge—it's infrastructure. The fact that LinkedIn, Indeed, Glassdoor, and Greenhouse are now fielding direct questions about algorithm-friendly resume formatting tells us AI screening has matured from optional experiment to operational baseline in enterprise hiring. Job seekers aren't asking if they should optimize for AI anymore. They're asking how. The window for that transition just slammed shut.

The Verge's reporting captures this pivot perfectly. Senior AI reporter Hayden Field interviewed representatives across the major hiring platforms, and what emerges is a unified consensus: your resume's algorithmic readability now matters as much as its human appeal—arguably more, since algorithms read it first. The platforms aren't hiding this anymore. They're actively coaching candidates on the rules. That transparency is itself evidence of maturation. When systems are young and proprietary, companies guard the algorithms jealously. When they've become standard practice, they explain them.

What's actually shifting here is the baseline expectation for job applicants. Six months ago, resume optimization for AI was framed as a "hack"—an insight savvy candidates could use to gain advantage. That framing is already dead. Now it's just how resumes work. The platforms discussing it with Hilke Schellmann, author of The Algorithm, are signaling that this isn't a temporary technical detail. It's the operating system.

This inflection carries different implications for different audiences, and the timing is critical. For professionals actively job hunting, the message is immediate: if your resume is structured for human readers—narrative flow, creative formatting, clever language tricks—you're already losing to algorithmic screening before anyone senior ever sees it. The job market's filtering layer has changed, and you need to adapt now. Not eventually. Now. This quarter. Before the next hiring cycle.

For enterprise decision-makers, this represents a hard shift in what hiring infrastructure actually means. You're not just using a platform anymore; you're operating within an algorithmic system that has its own rules. Those rules are being published because they're now table stakes. Your organization's recruiting processes either align with how these systems work, or they're fighting against their own tools.

For builders in the hiring tech space, this is the moment when the market consolidates around proven platforms. LinkedIn, Indeed, Glassdoor—these aren't just job boards anymore. They're hiring operating systems. The companies publishing guidance on their algorithms are the ones that have enough scale and staying power to define the rules. Startups trying to compete by offering "better AI screening" are playing yesterday's game. The game moved to integration and standardization.

Investors should note the timing signal here. When platforms start explaining their algorithms to end users, it means they've achieved enough market penetration that optimization guidance becomes a feature, not a secret. It also means they've solved the hard problems around accuracy and fairness enough to be comfortable with transparency. Greenhouse, with its focus on structured hiring, has been pushing this direction for years. Now the entire market is following. That's consolidation. That's maturation. That's margin expansion.

The broader pattern mirrors what happened when mobile became dominant. Five years ago, "mobile optimization" was a competitive advantage. Companies that optimized early captured disproportionate value. Then it became expected. Then it became required. Then everyone was doing it, and the differentiation moved elsewhere. Hiring algorithm optimization is at that same inflection point—crossing from optional advantage into mandatory baseline. The platforms are documenting the transition as it happens.

The inflection point isn't that AI screens resumes now—that's been happening quietly for two years. The inflection point is that it's now public, discussed openly, and documented by the platforms themselves as standard practice. For professionals, that window to get ahead of this curve closes within the next hiring cycle. For decision-makers, it means your recruiting infrastructure is fundamentally algorithmic whether you've consciously designed it that way or not. For investors, it signals the consolidation of hiring infrastructure around platforms with sufficient scale to define the rules. The next threshold to watch: when algorithms begin outright rejecting non-standardized formats, forcing immediate industry-wide standardization.