Devoured - April 30, 2026
The AI Economy: Five Adobe Sneaks Worth Watching in 2026 (5 minute read)

The AI Economy: Five Adobe Sneaks Worth Watching in 2026 (5 minute read)

Design aimarketing Read original

Adobe showcased seven experimental AI prototypes at its annual Sneaks event, with five standouts that could dramatically accelerate creative and marketing workflows if they reach production.

What: Adobe Sneaks is an annual showcase where employees pitch experimental prototypes outside the official roadmap. This year, 500 submissions were narrowed to seven demonstrations, though historically only 30-40% of Sneaks projects ever ship as actual features. The five most notable prototypes focus on simulated A/B testing, collaborative image generation, video localization, dynamic web personalization, and multi-channel asset creation.
Why it matters: These prototypes signal where Adobe thinks AI-powered creative tools are headed—away from single-use prompt boxes toward collaborative, multi-dimensional workspaces that can generate entire marketing ecosystems from a single asset. The audience-favorite Project Face Off could eliminate weeks of waiting for A/B test results by using synthetic personas to predict performance in seconds, potentially reshaping how marketing teams validate creative decisions.
Takeaway: Watch the full Sneaks presentations on YouTube at adobe.ly/sneaks to see which experimental features might become part of your creative toolchain in the coming year.
Deep dive
  • Project Face Off won the audience vote and simulates A/B testing by generating synthetic user personas that scroll, click, and convert in seconds rather than requiring weeks of real-world traffic for statistical significance
  • Traditional multivariate testing forces marketers to build variants, configure tracking, and wait days or months for enough traffic—Face Off lets them test dozens of variations cheaply upfront and promote only strong candidates to real tests
  • Project Test Kitchen reimagines AI image generation as a collaborative workspace where multiple designers can contribute tastes and constraints along controllable axes without chaos, moving beyond single-prompt boxes
  • Project Tailored Takes treats videos as flexible templates with modular shots, product imagery, and narrative structure that can be recombined for different markets without separate shoots for each region
  • Project Page Turner aims to replace static websites with dynamically assembled, intent-aware experiences generated in real-time based on user needs, eliminating the need for marketers to anticipate every possible journey
  • Project Asset Amplify turns a single creative asset into a full family of platform-specific content (social posts, print ads, websites) by understanding the campaign's visual language and adapting for different demographics
  • Adobe's workflow addresses the content demand problem where formats multiply faster than creative teams can produce—freeing designers to focus on work requiring human judgment
  • Sneaks is deliberately entertainment-focused with celebrity co-hosts (past guests include Jordan Peele, Kenan Thompson); this year featured comedian Iliza Shlesinger
  • The prototypes integrate across Adobe's existing tools: Firefly, Workfront, Experience Manager, Frame.io, Photoshop, and Express
  • Past Sneaks successes include Generative Fill, one of Adobe's most popular features, showing these experimental showcases can lead to major product innovations
Decoder
  • Adobe Sneaks: Annual showcase where Adobe employees pitch experimental prototypes outside the official product roadmap, with only 7 selected from hundreds of submissions
  • A/B testing: Marketing method where two variants of creative content are shown to different audiences to determine which performs better based on real user behavior
  • Multivariate testing: Testing multiple variables simultaneously across different versions to find the optimal combination
  • Statistical significance: The threshold of data needed to be confident that test results reflect true differences rather than random chance
  • Localization: Adapting content for different geographic markets, languages, and cultural contexts
Original article

Adobe Sneaks 2026: Five AI Prototypes Marketers Should Watch

IN THIS ISSUE: This week, I'm sharing some standout projects from Adobe Sneaks—the company's annual showcase of experimental prototypes that hint at where AI-powered creative tools are headed next. From simulated A/B testing to real-time web personalization, five projects stood out as potential game-changers for marketers and creative teams.

The Prompt

Every year, Adobe gives its employees a hall pass—the chance to pitch ideas that exist outside the company's official product roadmap. The best ones surface at the end of the company's Summit and Max events in a showcase called Sneaks. Typically, there are hundreds of submissions—500 this year—and only seven make the cut, a selection overseen by Principal Evangelist Eric Matisoff's team.

However, not every Sneak makes it to market. Matisoff tells me that historically, between 30 and 40 percent of these projects ever make it into production. Those lucky enough may even become some of Adobe's most popular features, such as Generative Fill.

Sneaks isn't a typical demo day experience, and you should certainly not expect it to feel like another keynote. It's meant to be fun and entertaining, which is why Adobe brings on a celebrity co-host. Past guests include Rainn Wilson, Joseph Gordon-Levitt, Jordan Peele, Kumail Nanjiani, Chelsea Handler, Kenan Thompson, and Jessica Williams. This year, Matisoff was joined by actress and comedian Iliza Schlesinger.

Adobe Principal Evangelist Eric Matisoff and actor and comedian Iliza Schlesinger

This week in Las Vegas, I attended my first Sneaks. Here are the prototypes that caught my attention and that I hope will make it onto Adobe's product roadmap.

Project Face Off (Winner)

Created by research scientist Doga Dogan, Project Face Off simulates A/B testing to predict which creative variant will perform the best and why. Instead of waiting weeks for real-world traffic, marketers can upload competing designs, define the primary conversion goal, and let the system generate synthetic user personas that scroll, click, consider, and either convert or drop off. Results are generated in seconds.

Traditional multivariate testing is slow by design. Marketers have to build multiple variants, configure tracking, stand up experimental frameworks, and then wait—days, weeks, sometimes months—for enough traffic to reach statistical significance. And even when the test runs cleanly, the result is still just A versus B. What if you have a dozen variations worth testing? This prototype promises to let marketers run as many simulated tests as cheaply up front, eliminate the weak options earlier, promote stronger candidates into real-world tests, and save traffic and time for higher-quality experiments.

Project Face Off was named the Summit audience favorite, which means it has a much better chance of being productized in the future.

Project Test Kitchen

Project Test Kitchen reimagines AI image generation as a collaborative, multidimensional design workspace rather than a one-shot prompt box. Created by research intern Yuzhe You, it tackles the "too many cooks" problem head-on—giving multiple designers a seat at the table without the chaos. This prototype combines multiple people's tastes and constraints. It enables exploration of visual directions along clear, controllable axes. The AI becomes a co-creator capable of understanding style, composition, and branding—not just keywords.

Project Tailored Takes

This AI-powered system connects workflows across Adobe Firefly, Workfront, Experience Manager, and Frame.io, making it easier to create highly localized, multi-version video ads. Today, transforming a "master" video into multiple localized spots requires separate shoots— sometimes entirely new productions—for each region. Multiple editing passes are also needed, as well as coordination across agencies and in-house teams. This can be costly, slow, and risky.

Adobe Foundry AI Creative Technologist Jordan Hall developed Project Tailored Takes to have AI do the heavy lifting. It treats videos not as single, finished files but as flexible templates. Shots, product imagery, motion, and narrative structure become modular elements you can recombine and regenerate for different markets, audiences, and channels. The goal: Marketers define what the ad should communicate and where it should run. Then, the AI-powered system handles how it'll be visually and culturally adapted.

Project Page Turner

What if you could use AI to turn your website from a static, one-size-fits-all page into a dynamically assembled, intent-aware experience? That's the idea behind Project Page Turner, created by Adobe's Experience Manager engineering chief Paolo Mottadelli. The aim is to redefine personalization in the ChatGPT era by eliminating the need for a handful of fixed templates, the need for users to hunt and peck across entire websites to find information, and the need for marketers to anticipate every journey. Instead, AI will do it all by assembling, in real time, pages centered on a user's intent.

To learn more about Project Page Turner, read my exclusive interview with Mottadelli.

Project Asset Amplify

Project Asset Amplify lets you turn a single asset into a full marketing ecosystem. With a prompt, you can leverage that artifact to create social media posts, print ads, and a website. And everything is editable within Adobe Photoshop and Express.

The brainchild of software developer Shivangi Aggarwal, it understands the source campaign's visual language, messaging, and intent. It also knows the psychology and preferences of different audiences and demographics (e.g., millennials versus Gen Z, parents vs. performance-focused buyers).

Marketers face a content demand problem—too much needed, not enough capacity to produce it. Hero images, social posts, display ads, YouTube covers: the formats multiply faster than designer and writer bandwidth can keep up. Project Asset Amplify uses AI to turn a single asset into a full family of creative files, scaled across audiences, platforms, and use cases—freeing creative teams to focus on the work that actually requires human judgment.

You can watch every Sneaks presentation from this year now on YouTube. Alternatively, you can browse them individually at adobe.ly/sneaks.

"This deal also signals the next utility phase of the AI economy: infrastructure and foundation model providers moving upstack to acquire the few remaining defensible application layers. Expect a new wave of AI M&A as neoclouds and AI hyperscalers merge with SaaS companies in a move to control both infrastructure and distribution. GPU and inference providers need software reach. Software companies need infrastructure scale. The mergers write themselves."

— WEKA Chief AI Officer, Val Bercovici, on xAI's potential acquisition of Cursor, describing the latter as a rare exception in the AI wrapper bubble.

Disclosure: I attended Adobe Summit as a guest of the company, with my flights and hotel stay paid for. The AI Economy's coverage is editorially independent from those that it covers. These words are my own.