Why building AI applications still means building infrastructure-first
The article discusses the importance of building robust infrastructure for AI applications. It highlights a case where Moltbook, a social network for AI agents, faced significant issues due to inadequate data infrastructure. The piece emphasizes that as AI transitions from prototype to production, the risks associated with poor architecture can have serious business implications.
- ▪Moltbook learned that scaling AI requires proper infrastructure after experiencing data management issues.
- ▪The company faced unauthorized postings and exposed sensitive user information due to infrastructure gaps.
- ▪Once AI moves to production, shortcuts in compliance and data privacy become significant business risks.
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Pro Why building AI applications still means building infrastructure-first Opinion By Ugur Tigli published 29 May 2026 AI success depends on secure, scalable data infrastructure When you purchase through links on our site, we may earn an affiliate commission. Here’s how it works. (Image credit: Getty Images) Copy link Facebook X Whatsapp Reddit Pinterest Flipboard Threads Email Share this article 0 Join the conversation Follow us Add us as a preferred source on Google Newsletter Subscribe to our newsletter In February 2026, Moltbook, a social network built for AI agents, learned a familiar lesson in a new way: you can’t scale AI without building the right infrastructure underneath it.Despite rapid traction and heavy funding, the company rushed into production with parts of the stack…
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