Bond wants AI to cure your doomscrolling, then monetize your memories
April 22, 2026 - 9:24 am
In short: Bond, a new “post-feed” social network founded by former Index Ventures principal Dino Becirovic and ex-Google DeepMind researcher Arthur Brazinskas, launched on April 21st with no infinite scroll or algorithmic feed. Instead, it uses AI trained on users’ photos, videos, and audio to suggest real-world activities. Positioning itself as a healthier alternative to social media, Bond joins the ranks of Tangle, BeReal, and Locket. However, its business model of licensing user data for AI training and lack of end-to-end encryption raise tensions with its anti-exploitation stance.
Bond, a social platform that launched on Tuesday, breaks from traditional feeds. There’s no infinite scrolling or algorithmic content; instead, users post memories—photos, videos, and audio—which Bond’s AI analyzes to recommend offline experiences tailored to individual preferences. The app aims to inspire users to put down their phones, not keep them engaged online. Yet, the platform hasn't fully addressed how its business model will survive in the tech industry.
Founded by Dino Becirovic, previously a principal at Index Ventures, and Arthur Brazinskas, a researcher with a background in user signals and reinforcement learning, Bond boasts a team of experts from major tech companies. The app is available on iOS and Android. Although funding details remain undisclosed, Bond has clearly differentiated itself through its unique concept.
What “post-feed” means in practice
The interface displays user profiles in clusters rather than a scrollable feed. Unlike typical social media platforms, Bond requires intentional navigation. Users tap on profiles to view their current stories and avoid passive content consumption.
The AI system leverages memories—photos, videos, and audio—to train itself on individual interests. It then generates personalized recommendations for experiences, events, and activities based on these data points. As Becirovic explains, if a user frequently posts about pho but hasn't tried it recently, Bond might suggest a nearby Vietnamese restaurant with good reviews.
If you have been posting about your love for hiking and haven’t been outdoors lately, Bond could recommend trails near your last hiking spot or even suggest joining a local hiking group. This level of personalization is what sets Bond apart from traditional social media platforms but also raises questions about data ownership and privacy.