Adobe is testing how well AI agents can use editing tools like a Photoshop professional would

Adobe researchers built an AI agent for image editing that pairs a general-purpose editor with specialized tools. A standard language model compares results using measured data and picks the best one.

AI agents for image editing break complex requests into steps and typically retry failed steps with the same tools, while a separate model judges the output by eyeballing it.

Researchers at Adobe Research and UC San Diego want to change that with EditAgent, a system that works more like a pro in Photoshop, according to a new paper. It picks the right tool for each task and compares the result against the original using hard numbers.

General-purpose editors fail at too many tasks

In a test of 600 image edits, blind-rated by five professionals, the general-purpose editor Flux-2-Klein-9B failed to produce a usable result 42.7 percent of the time. Specialized tools solved roughly two-thirds of those failures, especially for sharpening, rotation, and zooming. More retries with the same editor barely helped.

The researchers also tested whether an agent does better by refining results step by step or by generating multiple variants in parallel. Iterative refinement piles up small errors because each round builds on an already altered image. Professionals preferred the parallel variants generated from the original in 78.5 percent of the comparisons where they picked a side. The agent needed only half as many evaluation passes. EditAgent is built on these two findings.