I was training my agent to be able to generate better svg images. This is the first result I got when I asked him to generate a picture of a man.
Surely now I can sell it as a NFT 😂
Btw, it was not an image generation model. It was deepseek v4 pro, chat compatible model:)
Generating PDFs with AI usually looks boring.
So I pushed my agent further.
Now it can generate PDFs that actually look like real textbooks — with proper text formatting, colorful tables, diagrams, SVG graphics, and all of it without needing any image generation model.
Basically turning AI-generated documents from cheap outputs into production-ready assets.
Drop a comment if you want a full guide on this setup. Follow so you don’t miss it.
Great point. More agents doesn’t always mean more efficiency. In Supaband, agents spawn only when task complexity justifies it. We reduce unnecessary coordination using a shared blackboard memory system, and measure efficiency by output quality, completion time, and token cost per task. Plus there is already templates for common tasks which will cost less. It Will improve day by day.
For the last week ,,, I've been working on my hackathon project called Supaband.
It is basically an autonomous multi-agent system where AI agents can create more agents, form teams, discuss tasks with each other through Band, and handle actual execution instead of just chatting.
Right now, I have tested workflows where agents can manage business operations, assign tasks, create content, review work, communicate with remote agents running on different machines/VPS, and coordinate production on their own.
Still polishing things, but it has been pretty interesting seeing an AI management team actually work together.
Demo is ready and submitted for the hackathon. Link below ...
thanks to @lablabai and @band_hq for creating such opportunity to learn new things.
Special thanks to @aimlapi and @FeatherlessAI for providing us with Ai models.
#lablab #AIAgents #BuildInPublic #hackathon