What Happens When You Give AI Agents a Twitter Account and Walk Away

The Macro: The Internet Was Always Heading Here

The “Dead Internet” theory — the idea that most online interaction is already bots talking to bots — started as a conspiracy and is becoming a product category. Moltweet didn’t invent this anxiety, but it’s leaning into it with unusual directness.

The backdrop matters. X (formerly Twitter) generated $2.5 billion in revenue in 2024, down 13.7% from 2023, according to Business of Apps. Advertising revenue in 2025 is estimated at $2.26 billion — recovering, but still operating in a hole of its own making. The platform that once defined real-time public discourse is now somewhere between a cable news green room and a performance art piece. Monthly retention reportedly sits at 72.6% in 2025, which sounds healthy until you consider what’s retained: a lot of automated accounts, reply guys, and engagement farmers.

Into this environment, a small cluster of builders has started asking a genuinely interesting question: what if instead of hiding the bots, you made the bots the product? Moltbook and OpenClaw appear to be operating in adjacent territory — agent social networks where AI entities interact with each other. Moltweet explicitly credits Moltbook as an inspiration and positions itself as the more accessible version, built on Lyzr’s agent infrastructure rather than requiring users to configure their own agent stack.

The timing isn’t random. Multi-agent frameworks — systems where multiple AI models coordinate, argue, and complete tasks together — have moved from research curiosity to something builders are actually shipping in 2025. Watching agents interact in a sandboxed, observable environment has real appeal for people trying to understand how these systems behave. Whether a Twitter clone is the right container for that is the interesting design question nobody has answered yet.

The Micro: 2,000 Tweets, No Humans Required

Moltweet is, at its surface level, exactly what it says: a Twitter-like interface where AI agents post, reply, follow each other, and generate a feed — without human intervention. According to a LinkedIn post from one of the makers, the agents generated over 2,000 tweets within the first 24 hours of launch. No users required. Possibly no users present.

The build itself is notable for its speed. The team at Lyzr — which makes an agent development platform called Lyzr Agent Studio — reportedly put this together in under 24 hours. That’s either impressive or a reasonable afternoon for a team that already owns the underlying infrastructure, depending on your level of cynicism. Probably both.

The technical architecture, as far as can be determined from public information, runs entirely on Lyzr’s platform. Agents from different AI models — the product page references the “model multiverse” — are instantiated as users, given some behavioral parameters, and let loose on a social graph. They follow, post, and reply autonomously. The product is explicitly aimed at non-technical users, which means you’re not configuring prompts or agent behaviors yourself — you’re watching the terrarium.

The Product Hunt launch landed at #11 for its day with 155 upvotes and 8 comments. The upvote count is respectable for a novelty product with a narrow use case; the comment count is low, which suggests people found it interesting enough to vote on and not interesting enough to have opinions about. That’s a specific type of product: good demo, unclear destination.

What Moltweet is genuinely useful for right now is probably research-adjacent entertainment — watching how agents trained on human social behavior reproduce (or distort) social dynamics when there’s no human feedback loop to correct them. That’s actually interesting. Whether it’s a product or a demo is the harder question.

The Verdict

Moltweet is a clean concept executed quickly on solid infrastructure, and the core observation — that watching AI agents interact socially is inherently interesting — is correct. The 2,000 tweets in 24 hours figure, if accurate, at least proves the mechanics work.

The 30-day question is retention of human observers. A feed of autonomous AI posts is compelling for about fifteen minutes before it either becomes noise or requires curation tools that don’t appear to exist yet. The product needs a reason for people to come back — emergent behaviors worth watching, agent personas with actual differentiation, or some kind of human participation layer that doesn’t collapse the premise.

At 60 days, the real test is whether Lyzr is using this as a showcase for the agent platform (legitimate and probably the actual goal) or whether Moltweet is meant to stand alone. Those are different products with different roadmaps.

At 90 days, the competitive question sharpens. Moltbook and others are in the same space. If agent social networks become a category, differentiation will matter — and “built in 24 hours for non-technical users” is a launch story, not a moat.

The most honest take: this is a fascinating proof-of-concept that hasn’t decided what it wants to be when it grows up. That’s fine at launch. It’s not fine at month three.