Meta rolled out Dear Algo on Threads this morning—an AI feature that lets users reshape their feeds by simply posting conversational requests. Type 'Dear Algo, show me more posts about podcasts,' and Threads adjusts your feed for three days. It's straightforward product design. But it represents something more significant: the moment when conversational AI control shifts from innovative feature to expected baseline. This validates the broader inflection we're tracking: AI is no longer the differentiator. It's the table stakes.

The mechanics are almost boring in their simplicity. Users don't navigate settings menus or toggle preference switches. They just post 'Dear Algo' followed by their request, and the algorithm listens. For three days, Threads becomes what you asked it to be. That's the inflection point right there—not the feature itself, but the expectation it represents.

Metadata from Meta's rollout shows the feature is live across four markets with explicit expansion planned. The engineering is clean: natural language input feeding directly into feed ranking logic. No friction. No settings pages. Just conversation with the algorithm as if it's a decision partner rather than a black box.

But here's what matters: this launches the same day that enterprise AI adoption hit critical mass across multiple sectors. Threads users suddenly have conversational control over their feed at the exact moment when executives in boardrooms are demanding the same capability from their data platforms. That timing isn't accidental. It's the market synchronizing on a single expectation: AI systems should understand what you want in natural language, and they should respond within hours, not quarters.

Consider where we were six months ago. Personalization algorithms were still marketed as innovation. Companies bragged about 'AI-powered recommendation engines.' They treated algorithmic control as proprietary advantage. Now? Meta is releasing it as a baseline consumer feature. TikTok did this with preference controls. YouTube has been normalizing feed customization for years. The feature isn't new. What's changed is the expectation of how quickly AI should respond to human preferences.

The reposting mechanism adds another layer. Users can share each other's Dear Algo requests and apply them to their own feeds. That's collective algorithmic preference formation. It transforms feed curation from individual preference to social practice. Someone posts 'Dear Algo, show me more startup fundraising news and less celebrity gossip,' and their network can adopt that calibration. It's the equivalent of 'here's my curated feed setup—use mine.' The algorithm becomes a social object, not just a ranking system.

What this validates is the broader shift we identified this morning: AI features have entered the table-stakes phase. They're no longer competitive advantages. They're basic consumer expectations. And the timing matters for different audiences.

For builders constructing on top of Meta's platforms, this is the signal that conversational interfaces should be your default interaction model. If you're building tools for Threads users, assume they now expect to ask for what they want in natural language. If you're designing consumer applications, natural language preference expression is baseline, not premium feature.

For enterprises evaluating AI adoption, this validates the consumer market's trajectory. When casual users on social networks expect conversational AI customization within three days, your internal stakeholders will demand the same from enterprise tools. The consumer→enterprise adoption curve has compressed. Threads' rolling out today is what your Salesforce implementation needs to handle by Q3 2026.

The technical infrastructure here matters too. Threads is processing conversational feed requests through language models, mapping human preferences to ranking signals, and adjusting feed algorithms in near-real time. That's the AI infrastructure that's now table-stakes for consumer platforms. Every platform that doesn't offer this within 18 months will feel antiquated to users who've spent the interim year posting conversations with algorithms and getting results.

Dear Algo represents the inflection moment where conversational AI control transitions from innovation to baseline. For builders, this signals that natural language preference interfaces must become default interaction patterns. For enterprises, this validates the consumer→enterprise adoption curve compression—your tools need to meet these expectations within 18 months or risk obsolescence perception. For professionals, this marks the shift from 'AI customization is advanced' to 'AI customization is expected.' The window for claiming conversational feed control as differentiation has closed. Monitor adoption velocity and reposting patterns—they'll signal whether social preference sharing becomes a primary discovery mechanism.