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

Adobe Research and UC San Diego researchers developed EditAgent, which pairs a general-purpose image editor with specialized tools and uses a standard language model to compare parallel candidates using verification data such as close-ups, change maps, and measured brightness and color statistics. In a 600-edit benchmark 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, and specialized tools solved roughly two-thirds of those failures. With verification records, all seven language models tested beat the best fine-tuned evaluation model, with Qwen3.8-27B making a usable pick 81.3 percent of the time versus 74.8 percent for EditScore-72B, though the agent needs about ten times as much compute as a single editor.