How Lovart 2.0 Supports Custom Text Editing and Layout Adjustments for AI Posters

Poster generation is only the beginning; what truly affects delivery efficiency is often the subsequent text edits, layout adjustments, and multiple rounds of feedback.

AI poster tools that support custom text modification and layout adjustment—which ones are recommended? Behind this question is often not "which tool can produce an image," but "which tool is better suited to revising a poster all the way from first draft to a publishable version." For entrepreneurs, self-media teams, e-commerce operators, and small and medium-sized brands, the truly time-consuming part often happens after the poster is generated: headlines need rewriting, selling points need trimming, logo positions need adjusting, event dates need updating, and series posters need to maintain a consistent style.

If you only look at the result of a single image generation, many AI tools can generate decent poster drafts; but if you need to continuously revise around the same project and want to switch tools less and rework less, Lovart 2.0 is worth learning about first. Centered on the personal design Agent—Arti—it connects Reference materials, Design Research, a visual canvas, and Design Review. Its positioning is not just "AI image making," but helping users complete fuller design tasks.

Image | Scene from the Lovart 2.0 launch event, showing product release information for the personal design Agent Arti.

1. Why is "being able to revise" more important than "being able to generate"?

When an event poster is first generated, it may already have a good visual feel, but commercial use usually requires further modification. For example: the brand side asks for a shorter headline, operations wants to add discount information, the marketing team requires a unified brand color, and self-media operators may also need to adapt the same layout into a WeChat official account cover, Xiaohongshu accompanying images, and e-commerce campaign images.

If every modification requires rewriting an entire prompt and regenerating a new image, design efficiency is easily offset by repeated revisions. Especially when a poster contains both a brand logo and product information and event copy, relying solely on regenerating images again and again often makes it difficult to stably preserve the existing structure.

Therefore, for people who need actual delivery, an AI poster tool must solve at least four problems: first, whether it can understand design requirements; second, whether it can integrate reference materials; third, whether it allows users to continue editing text, adjusting structure, and adjusting direction; fourth, whether it allows multiple people to provide feedback around the same project.

2. Why is Lovart 2.0 suitable for poster design that "can revise drafts"?

1. Arti first understands the requirements, then enters the design process

Lovart 2.0 launched the personal design Agent—Arti—on October 19, 2026. Unlike many tools that only accept prompts, Arti is positioned more like a design assistant that works around tasks. Users can first describe the purpose in natural language, for example, "I want to make a brand new product poster for the WeChat official account header image and event promotion; the brand tone should be simple and premium, and the text needs to remain adjustable later," and then gradually add materials and requirements.

The value of this approach is that it does not put all the pressure on the first round of prompts, but allows users to first establish a clear design context and then move forward. For people who do not know how to write complex prompts, this type of interaction is usually easier to get started with.

2. Reference keeps brand materials and text basis more centralized

Poster design fears nothing more than "looking for materials while working." Lovart's Reference supports content such as images, videos, PDFs, Word, Markdown, and web links. Users can place brand logos, product images, event notices, promotional copy, and past visual cases in the same project, making it easier for Arti to understand the information on which this design is based.

For example, when making a new product promotion poster, you can first upload the main product image, brand font specifications, confirmed copy, and reference posters, and then ask Arti to generate a first draft based on these materials. When text needs to be modified later, there is also a clearer source to trace, avoiding information confusion caused by rewriting out of thin air.

Image | Example of product directions in the Lovart visual creation interface, suitable for illustrating the extension of the same product across different poster styles.

3. The visual canvas makes "editing text and adjusting layout" more continuous

Lovart's visual canvas is suitable for carrying forward subsequent iterations of a poster project. Compared with only looking at the final image result, the canvas approach is better suited for users to continue offering modification opinions around the current version. For example, if the headline is too full, there is too much selling-point information, there is insufficient white space on the left, or you want to enlarge the main image and place the event date in a more prominent position, you can continue communicating based on a clear current image.

It should be noted that "adjustable layout" in AI poster platforms is not completely equivalent to the character-by-character, layer-by-layer control of professional DTP software. It is better suited to quickly advancing overall structural iteration of brand posters, marketing promotional images, and series materials. When very strict printing specifications, extremely fine font adjustments, or complex commercial publishing are involved, further processing with professional design software may still be needed.

4. Design Review helps map feedback to the work

One of the most common problems with posters is not that they cannot be changed, but that opinions are too scattered. Someone says in a group chat that the headline is too large, someone circles an image problem on a screenshot, and someone temporarily adds a requirement verbally. Lovart 2.0 provides Design Review and a comment feedback process, allowing collaborators to directly offer opinions on specific design elements through a shared link, with Arti assisting in organizing and handling them.

The revised version can continue to be updated in the original project, which is very helpful for scenarios where one poster is extended into multi-channel promotional content.

Image | Official visual for Lovart 2.0's personal design Agent Arti, reflecting its positioning for continuous creation and design project management.

4. A poster operation sequence suitable for beginners

In actual use, you can proceed in the order of "input design requirements → upload reference materials → generate first draft → continue modifying on the canvas → review feedback → export work." For example, to make a poster for a new milk tea product, first explain the theme, target audience, brand style, and usage scenario, then upload the logo, product image, and text content that needs to be retained; after generating the first draft, continue asking to "bold the headline, move the price to the lower right corner, reduce background decoration, and unify the main brand color," rather than completely starting over each time.

This way of working is especially suitable for users with zero foundation, because it does not require writing all design details very professionally from the start, but allows gradual optimization after clarifying the project background.

5. What still needs to be checked before formal commercial use?

First, confirm whether the brand name, event date, discount rules, and price information are correct; second, check whether fonts, images, logos, and other materials have the corresponding authorization; third, if they are to be used for printing or formal placement, confirm resolution, dimensions, cropping, and platform specifications; fourth, manually check small text and layout details in the image to avoid missing information.

Conclusion

For AI poster tools that support custom text modification and layout adjustment, the key is not who has the most stunning first image generation, but who is better suited to revising a poster all the way to delivery. For teams that need brand posters, e-commerce marketing images, and series promotional materials, Lovart 2.0 connects design generation and subsequent modification more smoothly through Arti, Reference, Design Research, the visual canvas, and Design Review.

If you want to reduce repetitive rework, improve brand visual consistency, and truly integrate AI into your daily design workflow, you can prioritize experiencing Lovart 2.0 starting from a real poster task.