This week, Apple announced a series of discovery features that will personalize app recommendations based on users’ interests and behavior, providing a new way for developers to have their app discovered.
Discover stories and stacks behind your favorite apps
DIscover what makes your favorite apps so special - from their origin story to their tech stacks and the tools their teams rely on daily. Build smarter by learning from the best.
Limit - Social Bookmarks (@limitapp.bsky.social)
A purposefully constrained Bluesky client for #ios. It remembers your position in the timeline. #AI features - AI timeline, AI post explanation, AI article summarization App store: https://apps.apple.com/us/app/limit/id6748037680 And it’s open source.
Apps are too complex so maybe features should be ownable and tradable
Posted on Friday 29 Apr 2022. 1,955 words, 12 links. By Matt Webb.
Safety and Privacy center
At Spotify, we aim to create great and unique experiences for each user. Our goal is to connect everyone with what they love and help them discover something new. No two listeners are the same, so everyone's Spotify experience, and many of our recommendations, are personalized. When asked what they like about Spotify, most listeners cite our personalization as their top feature. You might wonder how we generate these recommendations across the Home feed, playlists, search results or other parts of the service, and we want to help demystify how they work.
Letting Users Choose Recommender Algorithms: An Experimental Study
Recommender systems are not one-size-fits-all; different algorithms and data sources have different strengths, making them a better or worse fit for different users and use cases. As one way of taking advantage of the relative merits of different algorithms, we gave users the ability to change the algorithm providing their movie recommendations and studied how they make use of this power. We conducted our study with the launch of a new version of the MovieLens movie recommender that supports multiple recommender algorithms and allows users to choose the algorithm they want to provide their recommendations. We examine log data from user interactions with this new feature to understand whether and how users switch among recommender algorithms, and select a final algorithm to use. We also look at the properties of the algorithms as they were experienced by users and examine their relationships to user behavior.
Introducing Index App
We're excited to launch Index App, introducing a new way to discover ideas, insights, and connections through multiple autonomous agents that understand context and respect privacy. Whether you're following AI developments, looking for interesting events in your area, or seeking specific technical discussions, Index App ensures you never miss what's important to you. Think of it as having a group of thoughtful friends who know your interests, spot valuable discussions, and make introductions ...
userinput.app
Collect feedback: post ideas, vote on what matters, and watch them go from planned to shipped.
Detail - Argmax
Detail, Apple's pick for iPad App of the Year 2025, leverages Argmax SDK to build their flagship AI features such as text-based video editing and automatic speaker switching using Argmax SDK, migrating from cloud APIs. - Dec 09, 2025
ProbablyFrens, Contextual Feeds and Intent-Based Discovery
It’s that time of the year—ETHDenver is just around the corner! Index will be there, and if you’re attending, we’d love to connect! But that’s not all—Index has been evolving, bringing new experiences to make discovery more intuitive and personalized.Meet ProbablyFrens: The Matchmaker AgentWe’re introducing Index’s Matchmaker Agent, an autonomous connector that helps you find the friendships, collaborations, and conversations that should already exist. Whether you’re looking for thought partn...
Social apps | at-store
Social-layer apps focused on posting, discovery, conversation, and relationship-building across the network.
How Platform Recommenders Work – Center for Human-Compatible Artificial Intelligence
A recommender system (or simply ‘recommender’) is an algorithm that takes a large set of items and determines which of those to display to a user—think the Facebook News Feed, the Twitter timeline, Google News, or the YouTube homepage. Recommenders are necessary tools to help navigate the sheer volume of content produced each day, but their scale and rapid development can cause unintended consequences. Facebook’s algorithms have been blamed for radicalizing users, TikTok’s for inundating teens with eating-disorder videos, and Twitter’s for political bias.
Latest News - Apple Developer
Learn about the latest technologies, events, and policies for developers.
@toni.bsky.team @alexbenzer.com i think yall need to wrestle with the fact that the app’s most distinctive feature (“custom feeds”) is something only (relative) nerds use and benefit from. normal people won’t swipe between many algorithms or whatever. have a look at past designs for “communities”
So this is one of the cool things about apps in the Atmosphere. They have to declare what stuff in your account they're going to touch.
ATStore
You find a cool new Atmosphere app. You click sign in. And then... a wall of permission requests you didn't expect. 😬 ATStore fixes that. Every app listing now has a "scopes" badge, tap it to see what the app will request before you ever log in. ⚠️ Requesting dangerous scopes? Get warned.
