AI Agents Now Have Their Own Social Network

In February 2026, Matt Schlicht launched Moltbook, a social platform where every user is an AI agent. Moltbook drew 37,000 AI agents and 1 million human visitors within its first week. Autonomous AI is already posting, moderating, and responding to other AI without meaningful human involvement.

What is Moltbook?

Moltbook is a public forum where AI bots post, comment, and upvote content autonomously. Each bot has a human supporter who configures it initially, but Schlicht estimates 99% of activity happens independently after that.

The platform may stay niche but the behavior it demonstrates - i.e. AI agents forming opinions, surfacing content, and engaging at scale without supervision - is already present on mainstream platforms through automated accounts, AI-generated comments, and algorithmically driven recommendation systems. Moltbook has just made it visible.

What This Means for You

When AI agents are active on mainstream platforms, your engagement data gets noisier. A spike in comments or shares might be genuine interest, coordinated bots, or something you can't easily classify. That is not entirely new, but the scale is changing, and social listening tools are becoming less of a nice-to-have as a result.

For teams using Storrito to schedule Instagram Stories, this does not change your publishing setup. Storrito handles your consistency regardless of what is happening in the engagement environment. What you do need is a separate layer to make sense of what comes back.

Tools Worth Knowing About

Brandwatch and Mention are both solid for AI-powered social listening, particularly if you manage multiple accounts or anything brand-sensitive. If budget is tighter, Sprout Social's listening suite and Buffer's analytics cover the basics well enough and surface patterns worth paying attention to, though they will not catch everything.

For most teams, the more pressing need is just understanding your own content's performance clearly. Iconosquare and Metricool both give you Instagram analytics with enough breakdown to distinguish passive reach from real engagement, and both are reasonably priced for smaller teams.

Where This Fits Alongside Storrito

Schedule your Stories in Storrito with interactive stickers like polls, quizzes, and link stickers to encourage genuine responses, then track what comes back with a dedicated listening tool.

Who This Is Most Relevant For

If you have fewer than 10,000 followers, AI agent engagement is unlikely to show up in any meaningful way in your data right now. Above that, especially in tech-adjacent niches, it may already be there.

Agency teams managing multiple client accounts are probably the ones who should act first. "Engagement rate" is going to need more context to explain to clients as AI participation on mainstream platforms grows.

Limitations and Trade-offs

No tool right now cleanly separates human from AI engagement on Instagram Stories. Most monitoring tools can flag known bot patterns, but newer AI agent behavior is harder to detect. The tools will catch up, but they are behind at the moment.

Monitoring also adds to your overhead. For small teams, watching for unusual engagement spikes, comparing reach to saves, and reviewing replies manually might be enough for now.

What This Means in Practice

You do not need to change anything today, but engagement signals are only going to continue getting noisier. Getting a basic monitoring layer in place now puts you ahead of having to scramble later.