Aakar Desai

Generative AI and Character Design: An overview of Zuraverse's Approach I had a fascinating conversation with my best buddy, Abhishek Sagar , the founder of Zuraverse.xyz, about how his team leverages generative AI for character design. It's a complex challenge, especially for a gaming platform with thousands of unique, NFT-based characters that need to maintain consistency while remaining true to their core identity. Abhishek shared some great insights, particularly their method of creating highly descriptive character prompts. Instead of generic descriptors, they use multi-layered strategy for character design consistency: • Prompt Engineering: They use a "recipe" of descriptive elements for each character. This goes beyond just physical appearance and includes: • Core Visuals: Specific details on body shape, color palette, unique markings (scars, tattoos), and accessories (a glowing sword, a specific type of armor). • Personality & Emotional Cues: Describing a "mischievous rogue with a sly grin" or a "somber sorceress with a furrowed brow" helps the AI generate consistent facial expressions and body language. • Style Cues: They include instructions to maintain a specific art style, whether it's "hyper-realistic," "anime-style," or "dark fantasy," to ensure all characters in a specific game universe look cohesive. • Reference Images: In addition to text, Zuraverse uses a core set of reference images for each character. This allows the AI to learn and replicate a character's "look and feel" with much greater accuracy, even when generating the character in new situations, poses, or wearing different outfits. • Agentic AI for Iteration: Abhishek also gave me a sneak peek into his journey with agentic AI. They are not just using a simple text-to-image generator. They're building AI agents that can take the initial character prompt and a set of rules, and then autonomously iterate on the design. This would allow the system to generate hundreds of variations—different outfits, poses, and expressions—while ensuring each one adheres to the character's core design principles. This isn't just theory—it's a practical application of AI by industry experts to tackle a real-world problem. Abhishek also promised that he will be sharing more details in the form of hands-on examples and podcasts in the coming weeks for the benefit of new explorers in his field. Feel free to checkout what zuraverse is Upto at: Zuraverse Story: https://lnkd.in/gz6Wuc4V Zuraverse: https://zuraverse.xyz Review: https://lnkd.in/gqkTSNxK #GenerativeAI #AIinGaming #Zuraverse #CharacterDesign #NFT #Gaming #AIagents #Innovation

13

ACTORS + AI: Director/Actor/Producer/Writer AI Chef 🧑‍🍳 Hans Obma visits the Cozy AI Kitchen 🎂 https://lnkd.in/gjiAvEfP to share his insights on how AI has transformed his creative processes. You may have seen Chef Hans in such 📺 hits as Better Call Saul, Wandavision, or Narcos — and yes, he's probably the most handsome AI 🧑‍🍳 chef we've had in the kitchen to date :-). Hans needed to learn a new language ... how did he do it? He got multimodal AI models to help him speak Welsh. Hans needed a way to scale how he communicated with his stakeholders ... how did he do it? He created an authentic-to-him way of scaling by creating an instant entourage of supporting agents. HT 🧑‍🍳 Ross Heise 🧑‍🍳 Matt Scholz and the power of the Wisconsin network for bringing such a storied talent to the Cozy AI Kitchen! --- This 🍰 episode: https://lnkd.in/gjiAvEfP All 50 episodes: https://lnkd.in/g6upvbGX

89

11 Comments

If you’re shipping faster but feeling more drained, you’re not alone. Our role changed from building to constantly evaluating AI output. Great read on why that’s exhausting

7

2 Comments

Here's what I get from it: - big tech companies are literally burning billions on "A.I." without any clear ROI plan - organic "A.I." adoption is abysmally low by their own employees because it simply doesn't work as promised, which is hypocritically embarassing for them, so now they're desperately trying to mandate its usage to prop up their reputational bubble a bit longer - CEOs still don't understand how their own sausage gets made and still don't care about producing quality products that will delight the true customers (the end users) - we have passed "peak A.I." (as all the big tech companies are starting to panic at the realization they have vastly overextended themselves by vastly overinvesting in "A.I.") and are now beginning to coast down the other side of the roller coaster track

5

TL;DR: AI is changing our workflows—and the change is exhausting us. Recently, I read Siddhant Khare’s piece on how AI is draining software engineers. He noted that AI has turned builders into custodians, shifting developers from the joy of writing elegant code to the drudgery of debugging probabilistic outputs. Prompted by conversations with UX colleagues, I looked into whether this burnout is isolated to engineering. The short answer? No. We are scrambling to build new skills, too, but the tech is evolving faster than our ability to standardize it. From an anthropological perspective, we aren't just adopting a new tool; we are experiencing a fundamental shift in our labour. AI promises "cognitive offloading," but the reality is often cognitive overload. Across Tech and UX, the root causes of AI Fatigue boil down to three things:  1️⃣ The Evaluative Shift: Moving from a satisfying "creator" role to an exhausting "reviewer/editor" role.  2️⃣ The Output Treadmill: Time saved by AI is immediately filled with more tasks.  3️⃣ The Hype Cycle: The ambient anxiety of constantly needing to learn new tools just to stay relevant. In UX Research, this hits hard when foundational field work is bypassed for "synthetic users" (prompting an LLM to act like a customer). Or when researchers trade the deep synthesis of user interviews for the tedious task of fact-checking AI generated summaries to ensure the emotional subtext wasn't hallucinated and conclusions actually make sense. In Design, practitioners are increasingly treated as "AI fixers" by cross-functional peers. Instead of driving deep design thinking, they are handed low-quality, AI-generated concepts by non-designers and told to "fix them"—creating immense extraneous cognitive load. We are trading the satisfying and pride-inducing mental effort of human-centered problem-solving for the exhausting task of algorithmic oversight. AI is changing our workflows in unexpected ways, and we need new skills to adapt. But until these skills are more stable and best practices emerge, any stop-gap workflows will take time and hard work. Until then, we need to be honest about the friction. I think we need to talk more about how profoundly exhausting this transition is, and what we can do about it. Have you noticed this shift from creator to editor in your day-to-day work? How does it manifest? What are the threats and opportunities for your role, and /or for our industry right now? PS. I did use AI help to research examples and case studies, and to help me formulate my thoughts in better English. I also asked for meaningful additional references (see in first comment) - which I checked to verify my sources, but I selected only a few key ones.

73

12 Comments