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How AI Helps Restaurants Stop Reshooting Expensive Seafood.
For premium Japanese dining, freshness is everything.
The challenge with sashimi photography is that the quality of the visual depends heavily on timing. The moment a dish leaves the kitchen, its texture, moisture, color, and natural shine begin to change. Miss the perfect shot, and the food may need to be replated, recreated, or reshot.
For restaurants serving premium seafood, this often translates into higher production costs and unnecessary ingredient waste.
For Okuzono, we explored how AI can create marketing content without relying on repeated food shoots. Instead of racing against freshness, we focused on building a content system that allows premium dishes to be showcased consistently across campaigns, social media, and promotional materials.
The result is a faster, more scalable approach to restaurant marketing that protects both creative quality and operational efficiency.
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To the AI creatives:
I remember when AI became a sensation a few years ago. Everyone was amazed by the realistic quality and the infinite possibilities for creation. It was new, exciting, fun—but also intimidating.
Fast-forward to today. Even though its popularity has grown and the technology has improved significantly, I've realized that many people who are not experienced with these tools have developed certain expectations about them.
AI = Fast = High Quality = Cheap
No.
Yes, tools like Nano Banana, Kling, and Seedance can produce impressive results, but don't forget that behind those results is a person sitting at a computer, iterating over and over and over again until they find that "perfect" final image.
I've had bad experiences with clients who think that just because I'm using AI, I should charge less.
"You use AI. You can do it in 20 minutes. Why are you charging so much?"
Well, what about the credits? What about post-production in Photoshop and Lightroom when needed? What about the constant back-and-forth to match branding guidelines and client feedback?
Those minutes and hours count too—not just the speed of Higgsfield, Kling, or ComfyUI.
And what about our hardware? Our storage drives? Our electricity costs? Our subscriptions?
Know your value.
Just because you're using AI doesn't mean you're an emotionless robot working nonstop, generating endless iterations for cheap dollars.
Take your time. Trust your process. Don't fall for the "it's instant and effortless" narrative that many content creators promote—or that some clients expect.
Plan your work. Define your goals. Sometimes a single image can take hours to get right.
If a client thinks that because something is generated quickly it should automatically be cheap, the answer is still:
No.
Know your value. Have a detailed understanding of how much you spend on credits, software, hardware, post-production, and revisions.
Clients are paying for results, experience, taste, creative direction, problem-solving, and the countless hours you've invested in mastering these tools—not just for the seconds it takes an AI model to render an image.
Peace.
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⛳️ 𝗦𝗸𝗶𝗹𝗹 𝗔𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁 𝗠𝗮𝘁𝗿𝗶𝘅 & 𝗥𝗼𝗮𝗱𝗺𝗮𝗽 𝗕𝘂𝗶𝗹𝗱𝗲𝗿 𝗳𝗼𝗿 𝗗𝗲𝘀𝗶𝗴𝗻𝗲𝗿𝘀
Skill Assessment Matrix is a SaaS designed to help Product Designers and UI/UX Designers better understand their current level, identify their strongest skills, and build a personalized growth roadmap
The idea came from a problem I experienced early in my career:
"𝙃𝙤𝙬 𝙙𝙤 𝙄 𝙠𝙣𝙤𝙬 𝙞𝙛 𝙄'𝙢 𝙖 𝙅𝙪𝙣𝙞𝙤𝙧, 𝙈𝙞𝙙-𝙡𝙚𝙫𝙚𝙡, 𝙤𝙧 𝙎𝙚𝙣𝙞𝙤𝙧 𝙙𝙚𝙨𝙞𝙜𝙣𝙚𝙧?"
This first version is focused on the desktop experience and was designed as the foundation for a larger SaaS product
𝗣𝗥𝗢𝗕𝗟𝗘𝗠
Designers often struggle with:
✦ Understanding their current level
✦ Identifying their strongest skills
✦ Knowing what to improve next
✦ Creating a clear career growth plan
𝗦𝗢𝗟𝗨𝗧𝗜𝗢𝗡
Skill Assessment Matrix helps designers answer three simple questions:
✦ Where am I today?
✦ What are my strongest skills?
✦ What should I focus on next?
The product guides users through a complete career planning flow:
𝗦𝘁𝗲𝗽 𝟭 [Career Goals Setup] Users define their career goals and desired direction
𝗦𝘁𝗲𝗽 𝟮 [Self Assessment] Users evaluate their current skills across multiple competency areas
𝗦𝘁𝗲𝗽 𝟯 [Summary] The system generates a personalized overview highlighting strengths and growth opportunities.
𝗦𝘁𝗲𝗽 𝟰 [Roadmap Builder] Users receive a personalized roadmap and can further customize it by adding their own skills
𝗦𝘁𝗲𝗽 𝟱 [PDF Export] The final roadmap can be exported as a PDF and used as a practical career development plan.
⚡️This roadmap generation and export flow became one of the most valuable features of the project⚡️
𝗥𝗘𝗦𝗘𝗔𝗥𝗖𝗛 𝗙𝗢𝗨𝗡𝗗𝗔𝗧𝗜𝗢𝗡
This project is based on more than 5 years of research into Skill assessment frameworks. The primary foundation for this work was the Figma Community Skills Matrix documentation, supported by dozens of additional public frameworks
𝗪𝗛𝗔𝗧 𝗪𝗔𝗦 𝗧𝗘𝗦𝗧𝗘𝗗
✦ Figma AI Agent for generating new interfaces
✦ Figma Make for transforming designs into interactive product flows
✦ Combining a custom design system with generated product experiences
✦ Building complex multi-step user journeys inside Figma Make
✦ Creating SaaS-style product logic without traditional development workflows
𝗧𝗢𝗢𝗟𝗦 𝗨𝗦𝗘𝗗
Figma ✦ Figma AI Agent ✦ Figma Make ✦ MCP Servers
🔗 𝗣𝗥𝗢𝗝𝗘𝗖𝗧 𝗟𝗜𝗡𝗞: https://meta-poet-59855448.figma.site
🎥 Watch the video to see the full design process and how the project was built
🔗 𝗩𝗜𝗗𝗘𝗢: https://youtu.be/S3q38_kpTXo
𝗖𝗢𝗟𝗟𝗔𝗕𝗢𝗥𝗔𝗧𝗢𝗥𝗦:
Special thanks to @Illia Skliarov for contributing to the creative process, design discussions, design, brainstorming sessions, and product thinking throughout the project.
𝗦𝗨𝗣𝗣𝗢𝗥𝗧 (っ◔◡◔)っ
Please like, comment, share, or save this project to help more designers discover it ❤️
🔗 𝗦𝗢𝗖𝗜𝗔𝗟 𝗠𝗘𝗗𝗜𝗔 𝗣𝗢𝗦𝗧: https://www.instagram.com/reel/DZwXAvhoMHA/?igsh=MWpmZGRwYmx0Y2lwdA==
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Lately, I’ve been diving deep into Cursor, Claude, and AI agents.
Instead of just watching tutorials, I decided to learn by building something myself — a Figma plugin from scratch. There are already plenty of similar solutions out there, but my goal was to understand the entire creation process, from idea to a working product.
And here’s the result: I went from zero knowledge to a functioning plugin in just two days.
The plugin already helps identify issues in design files and highlights things that are easy to miss during day-to-day work. Of course, I’m still not 100% satisfied with it — there’s always room for improvement. But for a first attempt, I’m pretty happy with the outcome.
The most exciting part is that while building it, I started coming up with new ideas for Design System automation: naming conventions, component structure, style organization, and other repetitive tasks that could be streamlined with AI.
Looks like this is just the beginning 😄
Tech stack: Cursor, Claude, ChatGPT, and the Figma Plugin API.
For now, here’s a look at what I’ve built so far 👇
Wowww, great job 😍 Intrigued for part 2! You know, your approach to testing things yourself (from scratch!) reminded me the Tumblr times back in idk 2012-2014 maybe when everyone was photoshopping pics, memes, gifs etc. and I created my own "colors" (layers with different image...
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