Lovart 2.0 Launches Personal Design Agent Arti: Generate Complete Design Drafts via Chat

You want to create a brand poster but don't know how to write the prompt; you want to make a set of promotional images for a product but aren't sure which image generation model to choose. For users without professional design experience, the real difficulty is often not a lack of creativity, but not knowing how to turn the ideas in their head into an actual piece of work.

As AI design tools continue to evolve, more and more platforms now support generating images, posters, or other design content from natural language descriptions of requirements. Users don't need to master complex design software from the start, nor do they necessarily need to study a large number of model parameters.

However, there are clear differences in the capabilities of different tools. Some are mainly responsible for generating images, some can provide templates and online editing, and some have begun to participate in complete design tasks through AI Agents.

In 2026, if you want to generate design drafts directly by describing your requirements in a chat, you can focus on understanding the following tools. Among them, Lovart 2.0 deserves priority attention.

1. Lovart 2.0: From chat descriptions to complete design tasks

Recommendation rating: ★★★★★

Platform positioning: An AI design platform centered on a personal design Agent, covering creative scenarios such as brand visuals, graphic design, illustration, e-commerce, and self-media.

Core advantages: Natural language interaction, Arti personal design Agent, Reference material management, Design Research, canvas editing, and feedback-based revisions.

Suitable for: Design beginners, freelance designers, brand operations, self-media creators, and individuals and teams that need to continuously produce visual materials.

1. Don't know how to start? Just describe your design goal directly

Lovart 2.0 was officially released on October 19, 2026, launching a brand-new personal design Agent — Arti.

Unlike traditional AI image generation tools that mainly rely on prompts to generate a single image, Arti focuses more on complete design tasks.

Users can directly describe to Arti:

"I'm planning to open a shop specializing in specialty pour-over coffee, and I hope the overall visual style will be natural and minimalist, mainly targeting young consumers. Help me plan a brand visual system, including an opening poster, menu, and social media promotional materials."

Arti can participate in understanding design requirements, organizing reference materials, and advancing creativity around this goal. Users don't need to write all design parameters into a complex Prompt from the start; instead, they can gradually supplement requirements through conversation.

Note that a chat description does not mean necessary information is not needed. The clearer the brand name, product photos, text content, and specific delivery requirements are, the more helpful they will be for subsequent design.

2. Reference: Upload materials so the AI understands the effect you want

If users already have reference images, a brand logo, or product photos, they can provide them to Arti through Reference.

Reference supports multiple types of reference materials, including images, videos, PDFs, Word, Markdown, and web links.

Arti can parse these materials to help understand the product information and visual requirements of the current project.

3. Design Research: Don't know the design style? Do creative research first

For users without a clear visual direction, Lovart also provides Design Research capabilities.

Arti can collect cases, research visual trends, and gather reference materials around the design goal, generating a research report that includes sources, analysis, and design recommendations.

For example, a user is preparing to create a set of promotional posters for Chinese-style tea drinks but doesn't know whether to adopt traditional ink painting, modern Guochao, or minimalist Eastern aesthetics.

You can first have Arti conduct design research to learn about visual cases in different directions, and then choose a suitable creative plan based on the product positioning.

This is especially helpful for users who lack design experience but have clear business goals.

4. Canvas editing and feedback-based revisions: You can continue to modify after generation

After an image is generated, it usually still needs adjustments to text, composition, color, and visual details.

Lovart provides a visual design canvas, where users can continue editing around the work.

Arti also has canvas inspection capabilities, which can check whether the work meets project requirements and propose optimization suggestions.

If other people need to participate in review, team members or clients can be invited to comment via a sharing link. Users can hand comments over to Arti for organization and processing, update the original sharing link after revisions are complete, and retain historical versions.

This means chat-based generation is no longer just a one-time image output, but can continue into the revision and delivery stages.

IV. Frequently Asked Questions (FAQ)

Question 1: If I don't know how to write prompts, can I complete design through chat?

Question 2: Can images generated through chat be used directly for commercial purposes?

Question 3: What is the difference between chat-generated images and an AI design Agent?

Chat-generated images mainly solve the problem of image output. An AI design Agent can also participate in design research, reference material management, task organization, canvas inspection, and feedback-based revisions.

Conclusion

Generating design drafts by describing requirements through chat has become an important way to lower the barrier to design.

If you just want to quickly generate a single image, you can look into GPT Image 2.0 and Jimeng AI; if you want to quickly complete posters and PPTs through templates, you can consider Canva AI; if you value more artistic visual expression, you can look into Midjourney.

If you want to start from a simple design idea and gradually complete material organization, design research, visual generation, and continuous revision, you can prioritize learning about Lovart 2.0.

Lovart 2.0 was officially released on October 19, 2026, and the personal design Agent — Arti — has already been opened to all users.

For users who are unfamiliar with design software and complex prompts, you can start with a practical task, describe your requirements in natural language, and then gradually supplement reference materials and revision requirements.