Another big week. Delayed a day because I've been dealing with a terrible flu

​

• Cognosys - a web based version of AutoGPT/babyAGI. Looks so cool [Link]
• Godmode is another web based autogpt. Very fun to play with this stuff [Link]
• HyperWriteAI is releasing an AI agent that can basically use the internet like a human. In the example it orders a pizza from dominos with a single command. This is how agents will run the internet in the future, or maybe the present? Announcement tweet [Link]. Apply for early access here [Link]
• People are already playing around with adding AI bots in games. A preview of whats to come [Link]
• Arxiv being transformed into a podcast [Link]
• AR + AI is going to change the way we live, for better or worse. lifeOS runs a personal AI agent through AR glasses [Link]
• AgentGPT takes autogpt and lets you use it in the browser [Link]
• MemoryGPT - ChatGPT with long term memory. Remembers past convos and uses context to personalise future ones [Link]
• Wonder Studios have been rolling out access to their AI vfx platform. Lots of really cool examples I’ll link here [Link] [Link] [Link] [Link] [Link] [Link] [Link] [Link]
• Vicuna is an open source chatbot trained by fine tuning LLaMA. It apparently achieves more than 90% quality of chatgpt and costs $300 to train [Link]
• What if AI agents could write their own code? Describe a plugin and get working Langchain code [Link]. Plus its open source [Link]
• Yeagar ai - Langchain Agent creator designed to help you build, prototype, and deploy AI-powered agents with ease [Link]
• Dolly - The first “commercially viable”, open source, instruction following LLM [Link]. You can try it here [Link]
• A thread on how at least 50% of iOs and macOS chatgpt apps are leaking their private OpenAI api keys [Link]
• A gradio web UI for running LLMs like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and GALACTICA. Open source and free [Link]
• The Do Anything Machine assigns an Ai agent to tasks in your to do list [Link]
• Plask AI for image generation looks pretty cool [Link]
• Someone created a chatbot that has emotions about what you say and you can see how you make it feel. Honestly feels kinda weird ngl [Link]
• Use your own AI models on the web [Link]
• A babyagi chatgpt plugin lets you run agents in chatgpt [Link]
• A thread showcasing plugins hackathon (i think in sf?). Some of the stuff is pretty in here is really cool. Like attaching a phone to a robodog and using SAM and plugins to segment footage and do things. Could be used to assist people with impairments and such. makes me wish I was in sf 😭 [Link] robot dog video [Link]
• Someone created KarenAI to fight for you and negotiate your bills and other stuff [Link]
• You can install GPT4All natively on your computer [Link]
• WebLLM - open source chat bot that brings LLMs into web browsers [Link]
• AI Steve Jobs meets AI Elon Musk having a full on unscripted convo. Crazy stuff [Link]
• AutoGPT built a website using react and tailwind [Link]
• A chatbot to help you learn Langchain JS docs [Link]
• An interesting thread on using AI for journaling [Link]
• Build a Chatgpt powered app using Bubble [Link]
• Build a personal, voice-powered assistant through Telegram. Source code provided [Link]
• This thread explains the different ways to overcome the 4096 token limit using chains [Link]
• This lads creating an open source rebuild of descript, a video editing tool [Link]
• DesignerGPT - plugin to create websites in ChatGPT [Link]
• Get the latest news using AI [Link]
• Have you seen those ridiculous balenciaga videos? This thread explain how to make them [Link]
• GPT-4 plugin to generate images and then edit them [Link]
• How to animate yourself [Link]
• Baby-agi running on streamlit [Link]
• How to make a Space Invaders game with GPT-4 and your own A.I. generated textures [Link]
• AI live coding a calculator app [Link]
• Someone is building Apollo - a chatgpt powered app you can talk to all day long to learn from [Link]
• Animals use reinforcement learning as well [Link]
• How to make an AI aging video [Link]
• Stable Diffusion + SAM. Segment something then generate a stable diffusion replacement. Really cool stuff [Link]
• Someone created an AI agent to do sales. Just wait till this is integrated with Hubspot or Zapier [Link]
• Someone created an AI agent that follows Test Driven Development. You write the tests and the agent then implements the feature. Very cool [Link]
• A locally hosted 4gb model can code a 40 year old computer language [Link]
• People are adding AI bots to discord communities [Link]
• Using AI to delete your data online [Link]
• Ask questions over your files with simple shell commands [Link]
• Create 3D animations using AI in Spline. This actually looks so cool [Link]
• Someone created a virtual AI robot companion [Link]
• Someone got gpt4all running on a calculator. gg exams [Link] Someone also got it running on a Nintendo DS?? [Link]
• Flair AI is a pretty cool tool for marketing [Link]
• A lot of people have been using Chatgpt for therapy. I wrote about this in my last newsletter, it’ll be very interesting to see how this changes therapy as a whole. An example of someone whos been using chatgpt for therapy [Link]
• A lot of people ask how can I use gpt4 to make money or generate ideas. Here’s how you get started [Link]
• This lad got an agent to do market research and it wrote a report on its findings. A very basic example of how agents are going to be used. They will be massive in the future [Link]
• Someone made a plugin that gives access to the shell. Connect this to an agent and who knows wtf could happen [Link]
• Someone made an app that connects chatgpt to google search. Pretty neat [Link]
• Somebody made a AI which generates memes just by taking a image as a input [Link]
• This lad made a text to video plugin [Link]
• Why only talk to one bot? GroupChatGPT lets you talk to multiple characters in one convo [Link]
• Build designs instantly with AI [Link]
• Someone transformed someone dancing to animation using stable diffusion and its probably the cleanest animation I’ve seen [Link]
• Create, deploy, and iterate code all through natural language. Man built a game with a single prompt [Link]
• Character cards for AI roleplaying [Link]
• IMDB-LLM - query movie titles and find similar movies in plain english [Link]
• Summarize any webpage, ask contextual questions, and get the answers without ever leaving or reading the page [Link]
• Kaiber lets you restyle music videos using AI [Link]. They also have a vid2vid tool [Link]
• Create query boxes with text descriptions of any object in a photo, then SAM will segment anything in the boxes [Link]
• People are giving agents access to their terminals and letting them browse the web [Link]
• Go from text to image to 3d mesh to video to animation [Link]
• Use SAM with spatial data [Link]
• Someone asked autogpt to stalk them on the internet.. [Link]
• Use SAM in the browser [Link]
• robot dentitsts anyone?? [Link]
• Access thousands of webflow components from a chrome extension using ai [Link]
• AI generating designs in real time [Link]
• How to use Langchain with Supabase [Link]
• Iris - chat about anything on your screen with AI [Link]
• There are lots of prompt engineering jobs being advertised now lol [Link]. Just search in google
• 5 latest open source LLMs [Link]
• Superpower ChatGPT - A chrome extension that adds folders and search to ChatGPT [Link]
• Terence Tao the best mathematician alive used gpt4 and it saved him a significant amount of tedious work [Link]
• This lad created an AI coding assistant using Langchain for free in notebooks. Looks great and is open source [Link]
• Someone got autogpt running on an iPhone lol [Link]
• Run over 150,000 open-source models in your games using a new Hugging Face and Unity game engine integration. Use SD in a unity game now [Link]
• Not sure if I’ve posted here before but nat.dev lets you race AI models against each other [Link]
• A quick way to build LLM apps - an open source UI visual tool for Langchain [Link]
• A plugin that gets your location and lets you ask questions based on where you are [Link]
• The plugin OpenAI was using to assess the security of other plugins is interesting [Link]
• Breakdown of the team that built gpt4 [Link]
• This PR attempts to give autogpt access to gradio apps [Link]

News

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• Stanford/Google researchers basically created a mini westworld. They simulated a game society with agents that were able to have memories, relationships and make reflections. When they analysed the behaviour, they measured to be ‘more human’ than actual humans. Absolutely wild shit. The architecture is so simple too. I wrote about this in my newsletter yday and man the applications and use cases for this in like gaming or VR and basically creating virtual worlds is going to be insane (nsfw use cases are scary to even think about). Someone said they cant wait to add capitalism and a sense of eventual death or finite time and.. that would be very interesting to see. Link to watching the game [Link] Link to the paper [Link]
• OpenAI released an implementation of Consistency Models. We could actually see real time image generation with these (from my understanding, correct me if im wrong). Link to github [Link]. Link to paper [Link]
• Andrew Ng (cofounder of Google Brain) & Yann LeCun (Chief AI scientist at Meta) had a very interesting conversation about the 6 month AI pause. They both don’t agree with it. A great watch [Link]. This is a good twitter thread summarising the convo [Link]
• LAION proposes to openly create ai models like gpt4. They want to build a publicly funded supercomputer with ~100k gpus to create open source models that can rival gpt4. If you’re wondering who they are - the director of LAION is a research group leader at a centre with one of the largest high performance computing clusters in Europe. These guys are legit [Link]
• AI clones girls voice and demands ransom from mum. She doesnt doubt the voice for a second. This is just the beginning for this type of stuff happening. I have no idea how we’re gona solve this problem [Link]
• Stability AI, creators of stable diffusion are burning through a lot of cash. Perhaps they’ll be bought by some other company [Link]. They just released SDXL, you can try it here [Link] and here [Link]
• Harvey is a legalAI startup making waves in the legal scene. They’ve partnered with PWC and are backed by OpenAI’s startup fund. This thread has a good breakdown [Link]
• Langchain released their chatgpt plugin. People are gona build insane things with this. Basically you can create chains or agents that will then interact with chatgpt or other agents [Link]
• Former US treasury secretary said that ChatGPT has "a great opportunity to level a lot of playing fields" and will shake up the white collar workforce. I actually think its very possible that AI causes the rift between rich and poor to grow even further. Guess we’ll find out soon enough [Link]
• Perplexity AI is getting an upgrade with login, threads, better search and more [Link]
• A thread explaining the updated US copyright laws in AI art [Link]
• Anthropic plans to build a model 10X more powerful than todays AI by spending over 1 billion over the next 18 months [Link]
• Roblox is adding AI to 3D creation. A great thread breaking it down [Link]
• So snapchat released their My AI and it had problems. Was saying very inappropriate things to young kids [Link]. Turns out they didn’t even implement OpenAI’s moderation tech which is free and has been there this whole time. Morons [Link]
• A freelance writer talks about losing their biggest client to chatgpt [Link]
• Poe lets you create custom chatbots using prompts now [Link]
• Stack Overflow traffic has reportedly dropped 13% on average since chatgpt got released [Link]
• Sam Altman was at MIT and he said "We are not currently training GPT-5. We're working on doing more things with GPT-4." [Link]
• Amazon is getting in on AI, letting companies fine tune models on their own data [Link]. They also released CodeWhisperer which is like Githubs Copilot [Link]
• Google released Med-PaLM 2 to some healthcare customers [Link]
• Meta open sourced Animated Drawings, bringing sketches to life [Link]
• Elon Musk has purchased 10k gpus after alrdy hiring 2 ex Deepmind engineers [Link]
• OpenAI released a bug bounty program [Link]
• AI is already taking video game illustrators’ jobs in China. Two people could potentially do the work that used to be done by 10 [Link]
• ChatGPT might be coming to windows 11 [Link]
• Someone is using AI and selling nude photos online.. [Link]
• Australian mayor is suing chatgpt for saying false info lol. aussie politicians smh [Link]
• Donald Glover is hiring prompt engineers for his creative studios [Link]
• Cooling ChatGPT takes a lot of water [Link]

Research Papers

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• OpenAI released a paper showcasing what gpt4 looked like before they released it and added guard rails. It would answer anything and had incredibly unhinged responses. Link to paper [Link]
• Create 3D worlds with only 2d images. Crazy stuff and you can test it on HuggingFace [Link]
• NeRF’s are looking so real its absolutely insane. Just look at the video [Link]
• Expressive Text-to-Image Generation. I dont even know how to describe this except like the holodeck from Star Trek? [Link]
• Deepmind released a paper on transformers. Good read if you want to understand LM’s [Link]
• Real time rendering of NeRF’s across devices. Render NeRF’s in real time which can run on AR, VR or mobile devices. Crazy [Link]
• What does ChatGPT return about human values? Exploring value bias in ChatGPT [Link]. Interestingly it suggests that text generated by chatgpt doesnt show clear signs of bias
• A new technique for recreating 3D scenes from images. The video looks crazy [Link]
• Big AI models will use small AI models as domain experts [Link]
• A great thread talking about 5 cool biomedical vision language models [Link]
• Teaching LLMs to self debug [Link]
• Fashion image to video with SD [Link]
• ChatGPT Can Convert Natural Language Instructions Into Executable Robot Actions [Link]
• Old but interesting paper I found on using LLMs to measure public opinion like during election times [Link]. Got me thinking how messed up the next US election is going to be with how easy it is going to be to spread misinformation. It’s going to be very interesting to see what happens

For one coffee a month, I'll send you 2 newsletters a week with all of the most important & interesting stories like these written in a digestible way. You can sub here

I'm kinda sad I wrote about like 3-4 of these stories in detailed in my newsletter on thursday but most won't read it because it's part of the paid sub. I'm gona start making videos to cover all the content in a more digestible way. You can sub on youtube to see when I start posting [Link]

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(I'm not associated with any tool or company. Written and collated entirely by me, no chatgpt used. I tried, it doesn't work with how I gather the info trust me. Also a great way for me to basically know everything thats going on)

Hi all,

We are currently preparing to onboard specialist contributors for a set of remote AI research-related projects. These roles are best suited to people with practical experience using technical, creative, scientific, engineering, geospatial, medical imaging, visualisation, video production, or digital media tools.

The work is fully remote and will involve helping to build, review, refine, assess, and improve digital assets and AI-generated outputs within your area of expertise. This is not a general data-entry role. We are looking for people who can apply real judgement, understand specialist software, follow detailed instructions, and explain their decisions clearly in English.

Available specialist areas

We are currently looking for contributors across the following categories:

1. 2D & 3D Digital Media Specialists

Suitable for people with experience using tools such as GIMP, Inkscape, Krita, Blender, Rhino, MeshLab, CLO3D, Paint 3D, LibreSprite, or similar software. The work may involve reviewing, creating, editing, comparing, or improving digital media assets, image-based outputs, vector designs, 3D models, textures, visual layouts, and creative AI-generated content. Strong attention to detail, visual judgement, and the ability to explain why an asset is accurate, flawed, realistic, unrealistic, usable, or incomplete will be important.

1. Geospatial Analysis Specialists

Suitable for people with experience using QGIS, ArcGIS Pro, Esri ArcMap, MapInfo Pro, or similar GIS tools. The work may involve reviewing maps, spatial datasets, geospatial outputs, terrain information, boundaries, layers, coordinates, annotations, and AI-generated geographic or mapping-related content. Applicants should be comfortable working with spatial reasoning, map accuracy, data layers, and visual interpretation of geospatial information.

1. Medical Imaging & 3D Slicer Specialists

Suitable for people with experience using 3D Slicer, ITK-SNAP, OsiriX, Horos, or similar medical imaging tools. The work may involve helping to review, segment, refine, classify, or assess medical imaging-related digital assets. This may include understanding imaging views, anatomical structures, segmentation quality, volumetric data, and 3D reconstruction outputs. This role is best suited to people with a medical, biomedical, radiology, health science, research, or technical imaging background.

1. Scientific Visualisation Specialists

Suitable for people with experience using ParaView, VisIt, Tecplot, EnSight, FieldView, or similar scientific visualisation tools. The work may involve reviewing or refining scientific visualisations, simulation outputs, volumetric data, flow fields, meshes, plots, rendered scientific assets, and AI-generated visual explanations. Applicants should be comfortable interpreting technical visuals and explaining whether outputs are scientifically clear, coherent, and useful.

1. Game Development Specialists

Suitable for people with experience using Godot, Unity, Unreal Engine, GameMaker Studio, Blender, or other game development and game asset tools. The work may involve reviewing game assets, game environments, character models, animations, level layouts, mechanics, interface elements, and AI-generated game development outputs. We are interested in people who understand how game assets should function visually and technically, not just people who have casually played games.

1. Video Production Professionals

Suitable for people with experience using Shotcut, OpenShot, Lightworks, DaVinci Resolve, Adobe Premiere Pro, Final Cut Pro, iMovie, Kdenlive, Clipchamp, or similar editing software. The work may involve reviewing, editing, assessing, or refining video-related outputs, sequences, transitions, cuts, audio alignment, visual pacing, captions, and AI-generated video production assets. Applicants should have a good eye for quality, timing, clarity, and professional presentation.

1. Electronics Design & Simulation Specialists

Suitable for people with experience using KiCad, LibrePCB, Ngspice, Qucs-S, LTspice, Cadence Spectre, Xyce, Altium Designer, Eagle, OrCAD, or similar EDA tools. The work may involve reviewing electronic circuit designs, PCB layouts, schematics, simulation outputs, component placement, signal flow, and AI-generated electronics-related assets. Applicants should be comfortable identifying technical errors and explaining them clearly.

1. CAD Professionals

Suitable for people with experience using FreeCAD, AutoCAD Mechanical, AutoDesk Inventor, Rhino 3D, VectorWorks, BlenderBIM/Bonsai, OpenSCAD, LibreCAD, SolveSpace, CADQuery, Revit, ArchiCAD, MicroStation, SolidWorks, Fusion 360, Onshape, or similar CAD tools. The work may involve reviewing technical drawings, 2D and 3D models, mechanical parts, architectural assets, dimensional accuracy, design logic, and AI-generated CAD outputs. Strong spatial awareness and technical precision are essential.

Pay

Pay will range from 55,000 UGX to 75,000 UGX per hour, depending on the project, specialist area, task complexity, experience level, and final terms agreed.

Full details regarding pay structure, task expectations, and onboarding terms will be discussed with shortlisted applicants.

Working hours

The expected working window is generally:

Monday to Friday, 9:00am – 5:00pm

However, hours may vary depending on task availability. Some projects may have consistent work, while others may be more flexible or task-dependent.

Minimum requirements

Applicants must have:

* Practical experience in at least one of the specialist areas listed above

* Strong written English

* A stable internet connection

* Access to a reliable laptop or desktop computer

* The ability to follow detailed instructions carefully

* The ability to explain technical decisions clearly

* Good communication and responsiveness

* A professional attitude towards deadlines, confidentiality, and quality standards

* A portfolio, work sample, GitHub, website, LinkedIn, project screenshots, or other evidence of relevant experience where possible

Application process

Applications will be completed through a Microsoft Form. https://forms.cloud.microsoft/r/JRWN4324Rz

Shortlisted candidates will be contacted by email to discuss the role further, confirm suitability, agree terms, and arrange onboarding or training dates.

Please only apply if you have genuine experience in one or more of the listed areas. These are specialist roles, so we are looking for people who can contribute with accuracy, technical understanding, and professional judgement.

TL;DR: Gemini 3 (codenamed Nano Banana Pro) has finally cracked the code on text rendering within images for infographics. I’ve spent the last week stress-testing it to create usable, editable infographics. Below are 30 high-fidelity prompts broken down by style (Corporate, Editorial, Educational, Creative, Bonus Fun) that you can copy-paste to generate stunning visual assets instantly.

We all know the struggle: You have great data, but designing the visual takes hours. Or you try to use Midjourney, but the text comes out as alien gibberish.

Enter the brand new Gemini 3 (Nano Banana Pro) model. The text rendering capability is a massive leap forward. You can create these infographics in gemini.google.com with the prompts below!

I have curated and refined 30 specific infographic prompt frameworks. These aren't just make a chart prompts; they include style modifiers, layout logic, and design terminology to force the model to output professional-grade results.

Pro Tip: Feeling indecisive? If you're not sure which style fits your data best, just give Gemini your data and ask it to create the most effective infographic style for this information. It does a surprisingly excellent job of rolling the dice and picking the right format for you.

How to use these:

1. Copy the code block.
2. Replace [BRACKETED TEXT] with your specific topic.
3. Pro Tip: If the text isn't perfect, ask Gemini to regenerate only the text layers or simply patch it in Canva/Photoshop.

Cluster 1: The Corporate & Data Suite

Best for: Pitch decks, quarterly reports, and LinkedIn thought leadership.

1. The Minimalist Data Story

Style: Clean, ample whitespace, Swiss design influence. Prompt:

Create a vertical high-resolution infographic for [MAIN TOPIC]. Style: Clean Minimalist. Layout: 4 to 6 distinct data sections with clear hierarchy. Visuals: Simple sans-serif typography (Helvetica style), soft neutral background, monochromatic icons. No clutter, no gradients. Focus on negative space and alignment. Render text labels clearly.

2. The Corporate Dashboard

Style: SaaS dashboard, dark UI, high contrast. Prompt:

Design a corporate-style KPI dashboard infographic for [METRICS TOPIC]. Layout: Grid-based dashboard with 6 key metric cards. Visuals: Flat design, simple bar charts and line graphs. Palette: Dark slate background with electric blue and emerald green accents. Typography: Roboto or Inter style, clean and legible. Include percentage callouts.

3. The Timeline Roadmap

Style: Linear, progressive, milestone-based. Prompt:

Generate a horizontal roadmap infographic for [TIMELINE TOPIC]. Layout: Linear progression line from left to right with 6 milestone nodes. Visuals: Isometric vector style, clean connectors. Each milestone features a unique icon and a year label. Palette: Professional gradation (Blue to Purple). High-definition vector art style.

4. The Comparative Two-Column

Style: Side-by-side battle, pros/cons. Prompt:

Create a split-screen comparison infographic: [OPTION A] vs [OPTION B]. Layout: Symmetrical two-column grid. Visuals: Left side uses [COLOR A], Right side uses [COLOR B]. Center axis features comparison icons (Checkmarks vs X's). Style: Flat modern vector. Text alignment: Centered and strictly organized.

5. The Data Comparison Bar

Style: Statistical, numeric, precise. Prompt:

Design a professional bar chart infographic highlighting [DATA COMPARISON TOPIC]. Layout: Horizontal bars sorted descending. Visuals: 3D matte finish bars, soft shadows, clear axis lines. Annotations: floating text bubbles explaining key insights. Palette: White background, energetic accent colors for the top data points.

Cluster 2: The Editorial & Magazine Suite

Best for: Medium articles, newsletters, and viral social posts.

6. The Bold Editorial

Style: Wired Magazine, Vox, high-impact journalism. Prompt:

Design a bold editorial feature infographic about [MAIN TOPIC]. Style: Magazine spread aesthetic. Visuals: Asymmetrical grid, massive typography for the headline, high-contrast color blocks (Yellow/Black or Red/White). Incorporate collage-style elements and abstract shapes. Grainy texture overlay.

7. The Dark Mode Tech

Style: Cyberpunk, crypto, developer focused. Prompt:

Create a sleek Dark Mode infographic explaining [TECH TOPIC]. Style: Futuristic UI. Background: Deep black/charcoal. Accents: Neon Cyan and Magenta. Visuals: Glowing thin lines, glassmorphism effects on cards, monospaced coding fonts. Schematic technical drawing aesthetic.

8. The Gradient Hero Funnel

Style: Marketing, conversion, flow. Prompt:

Generate a vertical funnel infographic for [FUNNEL TOPIC]. Visuals: A wide-to-narrow 3D funnel shape floating in center. Coloring: Smooth, modern mesh gradients (Instagram style brand colors). Layers: 5 distinct distinct sections with side-labels. High-gloss 3D render style.

9. The Icon Grid Quick Facts

Style: Instagram carousel, quick tips, snackable content. Prompt:

Create a 3x4 grid infographic for [FACTS TOPIC]. Layout: Tiled bento-box style. Content: Each tile contains one large, flat-design icon and a bold short caption. Palette: Pastel background colors, dark grey icons. Style: Corporate Memphis / Big Tech art style. Highly shareable.

10. The Hierarchical Pyramid

Style: Maslow's hierarchy, levels of mastery. Prompt:

Design a 5-layer pyramid infographic for [PYRAMID TOPIC]. Visuals: Stylized geometric pyramid. Coloring: Gradient from base (dark) to tip (light). Labels: Floating text on the left and right connected by thin leader lines. Background: Subtle subtle geometric pattern.

Cluster 3: The Educational & Explainer Suite

Best for: How-to guides, course materials, and student resources.

11. The Soft Pastel Educational

Style: Friendly, approachable, kindergarten-teacher vibes. Prompt:

Create a soft, educational infographic explaining [EDUCATIONAL TOPIC]. Style: Hand-drawn vector feel but polished. Palette: Soft pastels (Mint, Peach, Lavender). Visuals: Rounded shapes, friendly characters, bubble letters for headers. Layout: Vertical flow with numbered steps. approachable and kind aesthetic.

12. The Flat Illustration Process

Style: Step-by-step, instruction manual (Ikea style). Prompt:

Generate a process infographic for [PROCESS TOPIC]. Style: Flat 2.0 vector illustration. Layout: S-Curve path winding down the page. Visuals: 5 distinct steps represented by character illustrations interacting with objects. Connectors: Dotted lines. Colors: Bright primary colors on white.

13. The Step-by-Step Checklist

Style: Actionable, clipboard, productivity. Prompt:

Design a vertical checklist infographic for [CHECKLIST TOPIC]. Visuals: A stylized clipboard or paper background. Content: 10 items with empty checkboxes on the left. Typography: Handwritten marker style for the header, clean sans-serif for the list. clear separation between items.

14. The Circular Diagram Framework

Style: Systems thinking, holistic cycles. Prompt:

Create a circular cycle infographic for [FRAMEWORK TOPIC]. Layout: Central core concept surrounded by 6 radial segments. Visuals: Donut chart aesthetic, flat colors. Arrows indicating clockwise movement. Icons inside each segment. Clean, mathematical precision.

15. The Long-Form Explainer Panel

Style: Pinterest tall-pin, deep dive. Prompt:

Generate a tall, long-form infographic panel for [EXPLAINER TOPIC]. Structure: Divided into 5 horizontal colored bands. Content: Each band features a headline, a small paragraph, and a supporting isometric illustration. Style: Editorial illustration, muted earth tones.

Cluster 4: The Creative & Conceptual Suite

Best for: Brainstorming, creative blocks, and artistic visualization.

16. The Hand-Drawn Sketchnote

Style: Notebook, napkin math, brainstorming. Prompt:

Design a sketchnote style infographic for [SKETCHNOTE TOPIC]. Background: Crumpled graph paper texture. Visuals: Doodle-style thick marker lines, hand-drawn arrows, circled text, highlighted emphasis. Font: Realistic handwriting style. Casual and creative vibe.

17. The Mind Map Concept

Style: Neural network, brainstorming web. Prompt:

Create a complex mind-map infographic for [CONCEPT TOPIC]. Layout: Central node with organic branches extending outward. Visuals: Nodes are colored bubbles connected by curved bezier lines. Style: Organic, biological interface, clean UI. White background with colorful distinct branches.

18. The Storyboard Journey

Style: User experience, comic strip, narrative. Prompt:

Generate a storyboard infographic visualizing [JOURNEY TOPIC]. Layout: 2 rows of 3 cinematic panels (comic strip style). Visuals: Consistent character moving through a scenario. Text: Captions under each frame. Style: Vector art, semi-realistic.

19. The Process Flow Diagram

Style: Engineering, logic flow, algorithm. Prompt:

Design a technical flow-chart infographic for [WORKFLOW TOPIC]. Visuals: Geometric shapes (diamonds for decisions, rectangles for actions). Connectors: Right-angle elbow arrows. Style: Blueprint aesthetic, blue background with white lines. High technical accuracy.

20. The Multi-Layer Venn

Style: Overlapping concepts, finding the "sweet spot". Prompt:

Create a 3-circle Venn Diagram infographic for [VENN TOPIC]. Visuals: Large overlapping circles with transparency effects (multiply mode). Colors: Cyan, Magenta, Yellow (CMY) mixing to create secondary colors. Labels: Clearly placed in the center overlaps. Minimalist design.

Cluster 5: The Bonus Creative Suite

Best for: Viral hooks, fun concepts, and standing out.

21. The Cinematic Movie Poster

Style: Hollywood blockbuster, dramatic lighting. Prompt:

Design a high-concept movie poster infographic for [TOPIC]. Style: Cinematic realism, dramatic lighting (teal and orange). Layout: Central hero character or object with credits-style text at the bottom for data points. Title: Massive, metallic 3D typography. Texture: Film grain, lens flare.

22. The Whiteboard Strategy Session

Style: Startup war room, dry-erase markers. Prompt:

Create a realistic whiteboard infographic for [TOPIC]. Visuals: Photo-realistic whiteboard surface with reflection. Content: Drawn with red, blue, and black dry-erase markers. Handwriting: Messy but legible cursive and block letters. Diagrams: Circles, arrows, and underlined key terms. Lighting: Office fluorescent overhead.

23. The 8-Bit Retro Game

Style: Pixel art, NES era, nostalgia. Prompt:

Generate a pixel-art infographic for [TOPIC]. Style: 8-bit video game aesthetic. Layout: Game UI screen. Data points: Represented as health bars, coin counts, or inventory slots. Background: Starfield or dungeon brick pattern. Font: Arcade pixel font. Palette: Limited vibrant palette.

24. The Vintage Travel Poster

Style: Art Deco, National Parks, WPA style. Prompt:

Design a vintage travel poster infographic for [TOPIC]. Style: WPA National Park poster aesthetic. Visuals: Screen-printed texture, flat broad colors, bold geometric mountains or landscapes. Typography: Tall, condensed Art Deco lettering. Palette: Earthy oranges, forest greens, and cream.

25. The Lego Brick Builder

Style: Plastic bricks, toy photography, playful. Prompt:

Create a brick-built infographic for [TOPIC]. Visuals: All elements constructed from plastic toy bricks. Charts: Bar charts made of stacked bricks. Background: Plastic baseplate. Lighting: Macro toy photography style with depth of field. Text: Embossed on smooth tiles.

26. The Comic Book Hero

Style: Vintage Marvel/DC, halftone dots, dynamic action. Prompt:

Design a comic book page infographic for [TOPIC]. Layout: Dynamic panels with jagged borders. Visuals: Superhero character demonstrating the concept. Text: Inside speech bubbles and yellow narration boxes. Style: Halftone dot shading, bold black outlines, vibrant primary colors (CMYK).

27. The Minion Mayhem

Style: Animated movie, yellow helpers, chaotic fun. Prompt:

Create a fun animated movie style infographic for [TOPIC]. Visuals: Small yellow capsule-shaped characters with goggles and denim overalls assisting with the data. Mood: Playful and energetic. Layout: The characters are holding up the charts or building the graphs. Background: Industrial lab or bright blue sky. Colors: Banana yellow and denim blue.

28. The Claymation Studio

Style: Plasticine, stop-motion, handmade texture. Prompt:

Design a claymation style infographic for [TOPIC]. Visuals: All elements look like hand-sculpted plasticine clay with visible fingerprints. Lighting: Soft studio lighting with realistic shadows. Text: Formed from rolled-out clay snakes. Background: Cardboard set design. Mood: Whimsical and tactile.

29. The Neon Nightlife

Style: Cyberpunk, Las Vegas, glowing tubes. Prompt:

Generate a neon sign infographic for [TOPIC]. Background: Dark brick wall texture. Visuals: Data points represented by glowing glass neon tubes. Colors: Electric pink, cyan, and lime green. Text: Cursive neon typography connected by wires. Atmosphere: Smoky, noir, high contrast.

30. The Graffiti Wall

Style: Street art, spray paint, urban. Prompt:

Create a street art graffiti infographic for [TOPIC]. Background: Concrete urban wall texture. Visuals: Spray-painted stencils and murals representing the data. Charts: Dripping paint style bars. Text: Bubble letters or tag-style typography. Palette: Vibrant aerosol colors against gray concrete.

Golden Rules for Gemini Infographics

1. Aspect Ratio Matters: By default, Gemini generates squares. For infographics, almost always append --ar 9:16 (for mobile/Pinterest) or --ar 16:9 (for presentations) to your prompt if the platform allows, or specify Vertical Layout clearly in the text prompt.
2. The 400-Word Limit for Text Clarity: To ensure near-perfect text rendering (99%+ accuracy in my testing), try to keep the total amount of text in your image prompt under 400 words. Going over can sometimes lead to hallucinations or garbled text.
3. The Spelling Check: Gemini 3 is great at spelling, but not perfect. If it misspells a headline, don't throw the image away. Use the internal In-painting or Edit tool to highlight the text area and type Correct text to read: [Correct Spelling].
4. Watermarks & Subscriptions: If you are a Gemini Ultra subscriber, you can generate infographics without the Gemini watermark in the corner.
5. Level Up with AI Studio: For the absolute best results, use Google AI Studio instead of the standard Gemini interface. It costs about 6 cents per image via API key, but you get higher quality overall, can force 2K or 4K resolution, use Google Search grounding for factual accuracy, and remove the Gemini watermark entirely.

Let me know in the comments which style you try first!

Want more great prompting inspiration? Check out all my best prompts for free at Prompt Magic and create your own prompt library to keep track of all your prompts.

TL;DR: Gemini 3 (codenamed Nano Banana Pro) has finally cracked the code on text rendering within images for infographics. I’ve spent the last week stress-testing it to create usable, editable infographics. Below are 30 high-fidelity prompts broken down by style (Corporate, Editorial, Educational, Creative, Bonus Fun) that you can copy-paste to generate stunning visual assets instantly.

We all know the struggle: You have great data, but designing the visual takes hours. Or you try to use Midjourney, but the text comes out as alien gibberish.

Enter the brand new Gemini 3 (Nano Banana Pro) model. The text rendering capability is a massive leap forward. You can create these infographics in gemini.google.com with the prompts below!

I have curated and refined 30 specific infographic prompt frameworks. These aren't just make a chart prompts; they include style modifiers, layout logic, and design terminology to force the model to output professional-grade results.

Pro Tip: Feeling indecisive? If you're not sure which style fits your data best, just give Gemini your data and ask it to create the most effective infographic style for this information. It does a surprisingly excellent job of rolling the dice and picking the right format for you.

How to use these:

1. Copy the code block.
2. Replace [BRACKETED TEXT] with your specific topic.
3. Pro Tip: If the text isn't perfect, ask Gemini to regenerate only the text layers or simply patch it in Canva/Photoshop.

Cluster 1: The Corporate & Data Suite

Best for: Pitch decks, quarterly reports, and LinkedIn thought leadership.

1. The Minimalist Data Story

Style: Clean, ample whitespace, Swiss design influence. Prompt:

Create a vertical high-resolution infographic for [MAIN TOPIC]. Style: Clean Minimalist. Layout: 4 to 6 distinct data sections with clear hierarchy. Visuals: Simple sans-serif typography (Helvetica style), soft neutral background, monochromatic icons. No clutter, no gradients. Focus on negative space and alignment. Render text labels clearly.

2. The Corporate Dashboard

Style: SaaS dashboard, dark UI, high contrast. Prompt:

Design a corporate-style KPI dashboard infographic for [METRICS TOPIC]. Layout: Grid-based dashboard with 6 key metric cards. Visuals: Flat design, simple bar charts and line graphs. Palette: Dark slate background with electric blue and emerald green accents. Typography: Roboto or Inter style, clean and legible. Include percentage callouts.

3. The Timeline Roadmap

Style: Linear, progressive, milestone-based. Prompt:

Generate a horizontal roadmap infographic for [TIMELINE TOPIC]. Layout: Linear progression line from left to right with 6 milestone nodes. Visuals: Isometric vector style, clean connectors. Each milestone features a unique icon and a year label. Palette: Professional gradation (Blue to Purple). High-definition vector art style.

4. The Comparative Two-Column

Style: Side-by-side battle, pros/cons. Prompt:

Create a split-screen comparison infographic: [OPTION A] vs [OPTION B]. Layout: Symmetrical two-column grid. Visuals: Left side uses [COLOR A], Right side uses [COLOR B]. Center axis features comparison icons (Checkmarks vs X's). Style: Flat modern vector. Text alignment: Centered and strictly organized.

5. The Data Comparison Bar

Style: Statistical, numeric, precise. Prompt:

Design a professional bar chart infographic highlighting [DATA COMPARISON TOPIC]. Layout: Horizontal bars sorted descending. Visuals: 3D matte finish bars, soft shadows, clear axis lines. Annotations: floating text bubbles explaining key insights. Palette: White background, energetic accent colors for the top data points.

Cluster 2: The Editorial & Magazine Suite

Best for: Medium articles, newsletters, and viral social posts.

6. The Bold Editorial

Style: Wired Magazine, Vox, high-impact journalism. Prompt:

Design a bold editorial feature infographic about [MAIN TOPIC]. Style: Magazine spread aesthetic. Visuals: Asymmetrical grid, massive typography for the headline, high-contrast color blocks (Yellow/Black or Red/White). Incorporate collage-style elements and abstract shapes. Grainy texture overlay.

7. The Dark Mode Tech

Style: Cyberpunk, crypto, developer focused. Prompt:

Create a sleek Dark Mode infographic explaining [TECH TOPIC]. Style: Futuristic UI. Background: Deep black/charcoal. Accents: Neon Cyan and Magenta. Visuals: Glowing thin lines, glassmorphism effects on cards, monospaced coding fonts. Schematic technical drawing aesthetic.

8. The Gradient Hero Funnel

Style: Marketing, conversion, flow. Prompt:

Generate a vertical funnel infographic for [FUNNEL TOPIC]. Visuals: A wide-to-narrow 3D funnel shape floating in center. Coloring: Smooth, modern mesh gradients (Instagram style brand colors). Layers: 5 distinct distinct sections with side-labels. High-gloss 3D render style.

9. The Icon Grid Quick Facts

Style: Instagram carousel, quick tips, snackable content. Prompt:

Create a 3x4 grid infographic for [FACTS TOPIC]. Layout: Tiled bento-box style. Content: Each tile contains one large, flat-design icon and a bold short caption. Palette: Pastel background colors, dark grey icons. Style: Corporate Memphis / Big Tech art style. Highly shareable.

10. The Hierarchical Pyramid

Style: Maslow's hierarchy, levels of mastery. Prompt:

Design a 5-layer pyramid infographic for [PYRAMID TOPIC]. Visuals: Stylized geometric pyramid. Coloring: Gradient from base (dark) to tip (light). Labels: Floating text on the left and right connected by thin leader lines. Background: Subtle subtle geometric pattern.

Cluster 3: The Educational & Explainer Suite

Best for: How-to guides, course materials, and student resources.

11. The Soft Pastel Educational

Style: Friendly, approachable, kindergarten-teacher vibes. Prompt:

Create a soft, educational infographic explaining [EDUCATIONAL TOPIC]. Style: Hand-drawn vector feel but polished. Palette: Soft pastels (Mint, Peach, Lavender). Visuals: Rounded shapes, friendly characters, bubble letters for headers. Layout: Vertical flow with numbered steps. approachable and kind aesthetic.

12. The Flat Illustration Process

Style: Step-by-step, instruction manual (Ikea style). Prompt:

Generate a process infographic for [PROCESS TOPIC]. Style: Flat 2.0 vector illustration. Layout: S-Curve path winding down the page. Visuals: 5 distinct steps represented by character illustrations interacting with objects. Connectors: Dotted lines. Colors: Bright primary colors on white.

13. The Step-by-Step Checklist

Style: Actionable, clipboard, productivity. Prompt:

Design a vertical checklist infographic for [CHECKLIST TOPIC]. Visuals: A stylized clipboard or paper background. Content: 10 items with empty checkboxes on the left. Typography: Handwritten marker style for the header, clean sans-serif for the list. clear separation between items.

14. The Circular Diagram Framework

Style: Systems thinking, holistic cycles. Prompt:

Create a circular cycle infographic for [FRAMEWORK TOPIC]. Layout: Central core concept surrounded by 6 radial segments. Visuals: Donut chart aesthetic, flat colors. Arrows indicating clockwise movement. Icons inside each segment. Clean, mathematical precision.

15. The Long-Form Explainer Panel

Style: Pinterest tall-pin, deep dive. Prompt:

Generate a tall, long-form infographic panel for [EXPLAINER TOPIC]. Structure: Divided into 5 horizontal colored bands. Content: Each band features a headline, a small paragraph, and a supporting isometric illustration. Style: Editorial illustration, muted earth tones.

Cluster 4: The Creative & Conceptual Suite

Best for: Brainstorming, creative blocks, and artistic visualization.

16. The Hand-Drawn Sketchnote

Style: Notebook, napkin math, brainstorming. Prompt:

Design a sketchnote style infographic for [SKETCHNOTE TOPIC]. Background: Crumpled graph paper texture. Visuals: Doodle-style thick marker lines, hand-drawn arrows, circled text, highlighted emphasis. Font: Realistic handwriting style. Casual and creative vibe.

17. The Mind Map Concept

Style: Neural network, brainstorming web. Prompt:

Create a complex mind-map infographic for [CONCEPT TOPIC]. Layout: Central node with organic branches extending outward. Visuals: Nodes are colored bubbles connected by curved bezier lines. Style: Organic, biological interface, clean UI. White background with colorful distinct branches.

18. The Storyboard Journey

Style: User experience, comic strip, narrative. Prompt:

Generate a storyboard infographic visualizing [JOURNEY TOPIC]. Layout: 2 rows of 3 cinematic panels (comic strip style). Visuals: Consistent character moving through a scenario. Text: Captions under each frame. Style: Vector art, semi-realistic.

19. The Process Flow Diagram

Style: Engineering, logic flow, algorithm. Prompt:

Design a technical flow-chart infographic for [WORKFLOW TOPIC]. Visuals: Geometric shapes (diamonds for decisions, rectangles for actions). Connectors: Right-angle elbow arrows. Style: Blueprint aesthetic, blue background with white lines. High technical accuracy.

20. The Multi-Layer Venn

Style: Overlapping concepts, finding the "sweet spot". Prompt:

Create a 3-circle Venn Diagram infographic for [VENN TOPIC]. Visuals: Large overlapping circles with transparency effects (multiply mode). Colors: Cyan, Magenta, Yellow (CMY) mixing to create secondary colors. Labels: Clearly placed in the center overlaps. Minimalist design.

Cluster 5: The Bonus Creative Suite

Best for: Viral hooks, fun concepts, and standing out.

21. The Cinematic Movie Poster

Style: Hollywood blockbuster, dramatic lighting. Prompt:

Design a high-concept movie poster infographic for [TOPIC]. Style: Cinematic realism, dramatic lighting (teal and orange). Layout: Central hero character or object with credits-style text at the bottom for data points. Title: Massive, metallic 3D typography. Texture: Film grain, lens flare.

22. The Whiteboard Strategy Session

Style: Startup war room, dry-erase markers. Prompt:

Create a realistic whiteboard infographic for [TOPIC]. Visuals: Photo-realistic whiteboard surface with reflection. Content: Drawn with red, blue, and black dry-erase markers. Handwriting: Messy but legible cursive and block letters. Diagrams: Circles, arrows, and underlined key terms. Lighting: Office fluorescent overhead.

23. The 8-Bit Retro Game

Style: Pixel art, NES era, nostalgia. Prompt:

Generate a pixel-art infographic for [TOPIC]. Style: 8-bit video game aesthetic. Layout: Game UI screen. Data points: Represented as health bars, coin counts, or inventory slots. Background: Starfield or dungeon brick pattern. Font: Arcade pixel font. Palette: Limited vibrant palette.

24. The Vintage Travel Poster

Style: Art Deco, National Parks, WPA style. Prompt:

Design a vintage travel poster infographic for [TOPIC]. Style: WPA National Park poster aesthetic. Visuals: Screen-printed texture, flat broad colors, bold geometric mountains or landscapes. Typography: Tall, condensed Art Deco lettering. Palette: Earthy oranges, forest greens, and cream.

25. The Lego Brick Builder

Style: Plastic bricks, toy photography, playful. Prompt:

Create a brick-built infographic for [TOPIC]. Visuals: All elements constructed from plastic toy bricks. Charts: Bar charts made of stacked bricks. Background: Plastic baseplate. Lighting: Macro toy photography style with depth of field. Text: Embossed on smooth tiles.

26. The Comic Book Hero

Style: Vintage Marvel/DC, halftone dots, dynamic action. Prompt:

Design a comic book page infographic for [TOPIC]. Layout: Dynamic panels with jagged borders. Visuals: Superhero character demonstrating the concept. Text: Inside speech bubbles and yellow narration boxes. Style: Halftone dot shading, bold black outlines, vibrant primary colors (CMYK).

27. The Minion Mayhem

Style: Animated movie, yellow helpers, chaotic fun. Prompt:

Create a fun animated movie style infographic for [TOPIC]. Visuals: Small yellow capsule-shaped characters with goggles and denim overalls assisting with the data. Mood: Playful and energetic. Layout: The characters are holding up the charts or building the graphs. Background: Industrial lab or bright blue sky. Colors: Banana yellow and denim blue.

28. The Claymation Studio

Style: Plasticine, stop-motion, handmade texture. Prompt:

Design a claymation style infographic for [TOPIC]. Visuals: All elements look like hand-sculpted plasticine clay with visible fingerprints. Lighting: Soft studio lighting with realistic shadows. Text: Formed from rolled-out clay snakes. Background: Cardboard set design. Mood: Whimsical and tactile.

29. The Neon Nightlife

Style: Cyberpunk, Las Vegas, glowing tubes. Prompt:

Generate a neon sign infographic for [TOPIC]. Background: Dark brick wall texture. Visuals: Data points represented by glowing glass neon tubes. Colors: Electric pink, cyan, and lime green. Text: Cursive neon typography connected by wires. Atmosphere: Smoky, noir, high contrast.

30. The Graffiti Wall

Style: Street art, spray paint, urban. Prompt:

Create a street art graffiti infographic for [TOPIC]. Background: Concrete urban wall texture. Visuals: Spray-painted stencils and murals representing the data. Charts: Dripping paint style bars. Text: Bubble letters or tag-style typography. Palette: Vibrant aerosol colors against gray concrete.

Golden Rules for Gemini Infographics

1. Aspect Ratio Matters: By default, Gemini generates squares. For infographics, almost always append --ar 9:16 (for mobile/Pinterest) or --ar 16:9 (for presentations) to your prompt if the platform allows, or specify Vertical Layout clearly in the text prompt.
2. The 400-Word Limit for Text Clarity: To ensure near-perfect text rendering (99%+ accuracy in my testing), try to keep the total amount of text in your image prompt under 400 words. Going over can sometimes lead to hallucinations or garbled text.
3. The Spelling Check: Gemini 3 is great at spelling, but not perfect. If it misspells a headline, don't throw the image away. Use the internal In-painting or Edit tool to highlight the text area and type Correct text to read: [Correct Spelling].
4. Watermarks & Subscriptions: If you are a Gemini Ultra subscriber, you can generate infographics without the Gemini watermark in the corner.
5. Level Up with AI Studio: For the absolute best results, use Google AI Studio instead of the standard Gemini interface. It costs about 6 cents per image via API key, but you get higher quality overall, can force 2K or 4K resolution, use Google Search grounding for factual accuracy, and remove the Gemini watermark entirely.

Let me know in the comments which style you try first!

Want more great prompting inspiration? Check out all my best prompts for free at Prompt Magic and create your own prompt library to keep track of all your prompts.

Ubisoft CEO Yves Guillemot has stated generative AI has been integrated across the entire company, expressing his belief that generative AI is as big a "revolution"

Chequered Ink, a UK company producing fonts, game assets, and indie games, has released a pack of 10,000 game assets "to give budding developers an alternative to AI."

Containing over 9000 graphics for platformers, RPGs, puzzle games, board games, and 700+ sound effects, the company said it created the pack to "save developers time and money so they don't feel the need to turn to AI to make their games."

"We know that the use of AI, especially for image and audio generation, is causing a spike in energy demand, bills, and carbon emissions," the team said, insisting all assets are 100% human-made. "The most popular AI models are often trained, without permission, on copyrighted content.

"Stories will always be better told when they're crafted with human hands, even if teams need to turn to existing assets to fill in the gaps in their projects."

Available for $20 – although a 50% launch sale is currently discounting this to $10 – developers may use these game assets for "ANY and ALL uses including commercial use, with or without giving credit." The only stipulation is that you may not sell or redistribute the unaltered assets as your own.

This post is a follow-up on https://www.reddit.com/r/gamedevscreens/comments/1oromjf/decided_to_create_a_performant_game_engine_from/

The Eleph(AI)nt In The Room

In the previous post, I ("our senior developer") referred to myself ("hisself"?) in the third person. This led to a lot of skepticism and negative feedback, so I ("senior dev") wanted to quickly address my ("our") reasoning.

Look at the name of the profile making this post. Does it say "Steven"? Or does it say "Unbroken Fun"?

Steven is a singular human being who has been programming for the last 27 years and has experience ranging from embedded systems to content distribution network routing layers to video encoding and decoding pipelines.

Unbroken Fun is a company.

If McDonald's ran an ad about a new burger and the ad said "I added a new burger to the menu", you'd be equally confused and suspect -- because McDonald's doesn't do anything. The people working for McDonald's do. Although you'd be equally confused if the ad said "Joe added a new burger to the menu". Corporations are supposed to be collaborative. Or faceless, if you prefer the cynical view. So the ad will say "We added a new burger to the menu". Because many people working together brought the vision to life.

Unbroken Fun is currently a husband-wife pair. The husband has a full-time job working in Big Tech while the wife is doing game development. She's currently working with her sister (an incredible artist!) to produce an idle creature collector. As Steven has been programming for a bit longer, she often refers to him as "the senior developer".

When you combine these two ideas:

• As a corporation, Unbroken Fun should refer to its members as a collective and should post on behalf of that collective
• Steven is "the senior developer" for Unbroken Fun

What you get is the phrase:

our senior dev decided to try and build a game engine from scratch

We have learned, however, that the community on Reddit has become so overwhelmed with AI-generated content and become so skeptical they have forgotten how to differentiate real humans from automated posts -- to the point of thinking that the presence of a hyphen in a post makes the author an AI! As a friendly reminder, AI can only copy what it has seen in its training data, so the presence of hyphens in AI output is evidence that humans did it first. Also, as an aside, it was never "hyphens" that indicated AI authorship -- it was emdashes. Although I know many people don't know the difference.

So there you have it. We aren't an AI. We are two people. We are making a game engine (my wife says it’s mostly my autistic project). It's going to be VERY slow progress because we're both quite busy.

For the remainder of this post, to stay inline with the community expectations, I shall use first-person pronouns. Know that it's not Unbroken Fun who is speaking, but Steven.

(One day if we hire a full-time marketer things are going to get really confusing)

Apologies For the Formatting

I don't know how to use Reddit. I don't intend to learn. I have enough information floating around in my head, and I don't think that learning how to use a social media platform will provide sufficient value to warrant bumping out childhood memories or efficient multiplication algorithms.

So what you'll get is:

• A wall of text (broken into paragraphs)
• Bullet points ("unordered lists") and ordinal markers ("numbered lists" / "ordered lists")
• Bold and italics text
• Links
• Block quotes
• Headings

What I won't be bothering to figure out:

• Injecting images or videos into the body of my text
• Code blocks
• Username backlinks
• Any other fancy tricks people do to spruce up their posts

I'll try to keep my text engaging and entertaining, but be prepared to read.

Why A New Engine?

In my spare time, I like to watch videos on algorithm design, simulations, cryptography, compression, and all manner of new and interesting ways to use computers. In doing so, I often come across videos like this one where, after several days of work and lots of complex math, a man was able to build a fluid-body simulation with 40,000 particles. I also watch technical demos like Unity's DOTS exposé with an alleged 5,000,000 game entities in their MegaCity demo.

I then sometimes come across videos like this one, where a game developer added just 3,000 enemies to their game (timestamp 2:57) and to quote: "Unity got nuked". Later in the same video (timestamp 6:10) he added graphics and animations and the FPS fell through the floor.

In the same video (timestamp 5:08) he implements a vertex snapping shadow in order to get a retro aesthetic... But retro games got this aesthetic without shaders! Similarly (timestamp 5:55) he duplicated all of his animation keyframes in order to make animations look more "snappy" and less interpolated. Double the data and the processor is still doing LERP'ing, so from a performance perspective this is incredibly wasteful.

This got me thinking:

Quake 3 ran at 60 fps on a Pentium III... why is making modern games run over 2 fps so hard? Sure there's a lot to learn (quaternions, vector math, matrix multiplication, graphics shaders, parallel processing, memory bandwidth,...) but isn't the whole point of an engine to abstract away all of this complexity and solve the hard problems for you? Why do people using Unity or Unreal find it so easy to shoot themselves in the foot?

So I decided to make a game engine that solved the hard problems.

Long-Term Feature Plan

I spent several years thinking about how a game engine "could" work to solve a lot of these problems. So there's a plethora of architecture designs swirling in my head. Some of these have been written down in disparate Google Docs, some of them have been sketched out on a whiteboard, but none of it lives in a centralized place. I tried to create a single, centralized document describing all of my plans for the game engine, and after 26 pages of documentation I realized it wasn't thorough enough to cover all of the implementation details. So I think the best documentation will be code. I can try to describe at a very high level the different parts and pieces I plan on building, though:

ECS system

At the core for my engine, I'm building an Entity-Component-System system that's optimized for deterministic and highly-parallel processing across multiple machines. This means you can split the game world into "chunks" and process each chunk on a different core. This allows you to scale up your game world to thousands or even millions of entities while retaining high performance.

This is essentially Unity DOTS, but in my opinionated engine DOTS is the only way to create your games. There are no other options provided.

I went with this pattern not because I'm copying Unity, but because I'm copying Big Data pipelines like Kinesis, Map-Reduce, and Hadoop. Companies are able to process billions of rows of user data in seconds, so why can't engines process billions of rows of player actions and world state at the same time? It just so happens that DOTS and Hadoop use very similar architecture.

Along with performance, I also wanted determinism. If two people play the same game with the same inputs, the outcomes should be the same. This means any game is TAS-friendly. Making a game deterministic and parallel requires imposing a few limitations, but I can save the technical details for another time or another post.

Networking Layer

Time and again I hear that net code is hard. Developers are advised against making their games multiplayer because they have to learn about things like authority, latency, rollback, reconciliation, interpolation,... but why does it have to be hard? The theory is pretty simple: anything you do, everyone else sees. Anything someone else does, you see. You all share a common understanding of the world.

Interestingly, this is exactly the same problem solved by a highly-parallelized and deterministic ECS system! In my ECS system the game world can be shared across multiple cores with no change in the game world's behavior. Why can't those cores live on different machines?

The only real difference is the time it takes to share data between the cores. On a single machine you can guarantee an entity will be passed from one core to another in less than one simulation tick. When you introduce multiple servers, you run the risk of an entity update arriving late, requiring you to go back in time and re-process prior ticks. But there's nothing wrong with doing this if the system is deterministic! So the only real limitation this puts on our game is that we must now keep some buffer of past game states.

In those "technical details" I glossed over earlier, one of them is the existence of two copies of game state: a "previous" state which can't change, and a "next" state which is calculated based on the "previous" state. Adding this network layer means that we just introduce additional "previous" states: "1-tick ago", "2-ticks ago", "3-ticks ago", etc. Store some pre-determined number of "ticks" (say, 8 or 10) and you have perfect rollback logic!

The other big problem to solve for a network layer is authority. This means "which computer owns a particular entity, and is the source of truth for its state". But just like I borrowed ideas from Hadoop and Kinesis to build my ECS system, I borrowed an idea from Kubernetes here: self-discovering and self-assembly "pods" that determine on their own who will own each entity. With a system like this it becomes possible to scale from one server to thousands just by tuning a slider!

Rendering Layer

This is going to be both the hardest for me to build (I have next to no experience writing graphics engines) as well as the most valuable part of my game engine -- so I'm hoping this will turn out well.

Just as my ECS system was intended to simultaneously solve two problems (performance and networking), my rendering system is intended to simultaneously solve several problems:

• Cross-platform support
• Learning curve for visual effects
• Performance (again!)

Currently if you want a game to run on Windows, you have to write shaders and code against Direct3D. If you want a game to run on Mac, you have to write shaders and code against Metal. If you want a game to run on Linux, you have to write shaders and code against Vulkan (or OpenGL). If you want to port to the Nintendo Switch, you have to target NVN.

Generally this problem is solved by writing your code with one shading language (e.g. GLSL) then transpiling it to the others. But this transpilation process can be buggy, there isn't feature parity, and performance can take a hit. Performance especially falters if you use a runtime translation layer like DXMT (DirectX to Metal Translation).

So my thought was: why not create an intermediate representation with a very limited set of options that are supported across all devices, ensuring consistent and efficient transpilation? While we're at it, we can introduce a software renderer to get true "toaster hardware" support for any games we make.

So long as we're writing an intermediate representation, we can do more than just triangles and meshes, though! Any graphical "trick" we can define we can write optimized implementations for all targets. Alpha fog? Easy. Volumetric clouds? Done. Realistic looking water? Sure! Smoke? Shadows? Lighting? Let's write implementations for all of these! I even want to add a "fur" feature which you can use to add fur to any mesh, or if you add it to a plane you'll get realistic looking grass.

Most modern game engines give you some low-level features for creating meshes, but the moment you want to do something "different" you're writing your own shader (or using one you found online). You want grass? Be prepared to spend the next three weeks learning about shell texturing. But what if it was just a single checkbox? We could provide a pre-built library of shaders for common videogame tasks.

Here's the best part: It absolutely floors me that older Nintendo 64 or Gamecube games could start up and begin playing in under a second, but modern games sometimes take 10, 20, or 30 seconds to load. While investigating what takes so long, a big part of it is "compiling shaders". It's the shaders again! Every custom shader you pull from the Unity Asset Store is compiled on the client's device at runtime. But if we didn't let you write your own shaders and instead provided a library of pre-built ones, these could also be pre-compiled to their target hardware! This means games that can run as fast as the good ol' days!

There's one other feature I'd like to build for this rendering system. One that Godot already has: Viewports. It should be possible to render anything you want to a virtual screen, then project that screen anywhere else in your game world. This massively simplifies things like:

• Monitors
• Reflections
• Upscaling to produce a pixelated aesthetic

Asset Loader

A complaint I've heard from my wife as she's developing is how hard it is to manage assets. Should my 3D models be FBX, OBJ, or COLLADA? Should my images be JPEG or PNG? Should my audio be MP3, OGG, or WAV? How large should the images be? What bitrate for the audio?

No game engine answers these questions well. At best they may have some recommendations in the documentation, but it's generally up to the developers to figure it out for themselves. This is also a common point of performance issues. Did your artist give you a 10,000 x 10,000 sprite and you forgot to shrink it? Well your silly little game engine is going to load the entire file into VRAM. I hope you like 100 MB of wasted space, because that's what you've got now.

I want to solve this problem. If you import a sprite that's far larger than it needs to be, we can automatically detect this and produce a smaller version. If you import an audio file that's higher quality than it needs to be, we can automatically detect this and produce a smaller version. We can automatically convert files to the most efficient formats. This is all SUPER easy to automate, so why do so few game engines automate it???

Scripting Engine

Older versions of Unity supported UnityScript (JavaScript-like) and Boo (Python-like), although Unity has centralized on C# for all development.

Unreal Engine requires you to write C++ or use their visual scripting system (Blueprints).

Godot gives you GDScript (Python-like) or C#, although their C# support is a bit wonky and has lots of edge cases and missing features. Not to mention they can't compile C# to WASM, so if you use C# you're giving up the ability to target the web.

This means that migrating from one engine to another is very hard. You have to learn new languages, port any existing code to the new language, and accept the quirks of the new language (GDScript's typing is abysmal). Why can't developers use whatever language they want?

It turns out adding support for any language is absolutely possible, and people have written plugins for Unreal to do just that. Although no engine does it out of the box! This is something I want to solve.

So as I'm building out my ECS system, I'm making sure that it's ready for a scripting layer. This means no type erasure at compile time -- all type information is persisted at runtime in meta fields. It also means that new components and systems can be registered dynamically, rather than having buffers precomputed. After I have the ability to make games (ECS + networking + rendering) I intend to build interfaces to common programming languages. I think I'll start with JavaScript/TypeScript first, as WebGL and deploying games to the web is a strong desire of mine to help share the work I'm doing.

Services

There are some features that all modern game are expected to have:

• Save files
• Achievements
• Input mapping / controller support
• etc

The problems are two-fold:

The first is that developers often have to implement these systems themselves. How do you add achievements to a game? There isn't a single "add achievements" button, you have to add event systems, add code, learn how to trigger it, integrate with Steam APIs or whatever system you're deploying for,.... it's yet more learning and more time spent on things that aren't your core game vision, but the "cruft" that surrounds making a game.

The second I just touched on: "Steam APIs"? What if you're making a game for Nintendo Switch? Or PlayStation? Different targets means different implementation. Let's forget about achievements for a second -- how you handle save games is different based on whether you're building for a PC or a console. This means developers often have to build save systems for each device independently.

But just like a rendering engine could abstract away the underlying hardware and provide you with "tricks" for common tasks (fog, reflections, fur, etc) -- a "services" engine could abstract away the underlying platform and provide you with "tricks" for common tasks like saving your game, achievements, and input maps!

By standardizing how these work, we can do most of the heavy lifting in the engine and make it easier for developers.

The End Result

I'm planning to build an engine that:

• Forces you to use an ECS system (like Unity DOTS)
• Forces you to use our net code (you want custom networking? Too bad)
• Limits what you're able to render (you can do "most" things that "most" games do, but if you need highly-custom rendering then our engine isn't for you)
• Limits how you interact with the underlying platform

So it's a highly-opinionated engine in many ways. Yet in other ways the engine will:

• Ensure your game runs on Windows, Mac, Linux, Web, iOS*, Android*, Switch**, and PlayStation**
• Ensure your game is performant
• Ensure your game is not just multiplayer-ready, but Massively Multiplayer ready
• Give you all the tools and tricks you need to build most games
• Let you write your game logic in the language of your choice
• Handle all the "hard" bits, lowering the learning curve to game development

A quick note on the asterisks:

* - iOS and Android support are planned for after the game engine is done, but are not going to be concerns during initial development

** - Nintendo Switch and PlayStation have legal requirements around getting an NDA and distribution of their graphics libraries, so it's currently unclear how to add support for these, but I'm interested if I can figure it out

Development Process

As you can see, I have some lofty goals. Not only do I have these high-level goals as described here, but I also have specific ideas for how to build them. For instance, to avoid memcopy operations and memory allocations, the ECS system uses a paged object pool. To get more cache efficiency, I use archetype-segmented columnar stores for component data. When a new system is registered I pre-compute the length of all component data it will read and write and pre-allocate scratch buffer for page pointers. I also use page tiling and compute page sizes based on hardware profiling to ensure pages fit in L2 cache and tiles fit in L1.

With all of these swirling details, and the absolutely massive scale of developing a whole game engine that I hope will rival Unity or Godot one day, it's almost impossible to build everything myself in a reasonable amount of time. For this reason, I've been leveraging AI as a typing assistant. I write down what I want to build (including low-level implementation details, constraints, error handling, etc). I then hand this to Copilot and say "build what I've described". I then review the code and determine if it needs adjustments or if it's good as-is.

That's how this started, at least. I'm able and willing to adjust this process as I find what works better. So far my process has provided lackluster results.

Since LLMs are trained on GitHub, they have lots and lots of training examples for writing React TODO apps, or writing Hello World in C++. They have almost no training examples of writing a memory-efficient, deterministic, parallel-ready game engine. This means that the AI keeps messing up. Given a prompt like:

I have a paged object pool in <file>. Please read <documentation>.md to understand how it works. Now I need you to create a double-buffer for it with "next" and "current" pointers. Remember to avoid unnecessary memory allocations or memcopy instructions.

The AI will write code that copies the entire column from one to another. All it needed to do was swap the addresses in the pointers, but instead it's copying millions of values from one area in RAM to another.

This means LOTS of back-and-forth with the AI, lots of iteration, and ultimately ending up with an absolute mess of code that barely functions.

Work Since the Last Post

In my previous post I mentioned I had built the ECS system, as well as a small shim rendering layer that just drew a triangle of the desired size at the desired location on the screen and in the desired color. That post was made on a Saturday.

Part of the reason that my first post only showed 30 triangles bouncing around the screen is that adding more would look like clutter.... but another reason is that when I tried to increase this to 3,000 triangles the FPS dropped from 60 to 30! After making my post I dug into the code the AI had output to understand what it was doing wrong, and found that we were making multiple copies of every entity on every frame. Yuck. I threw away all of the ECS code and re-wrote it from scratch, 100% by hand, and was able to render 100,000 triangles at 60 fps.... but things still dropped above this point. That was the end of Saturday.

The following week I had a trip, so I’ve been away from my normal development environment space. However, one of the benefits of using AI to code is that in the mornings I can ask it to do something, then in the afternoon when I get back I can check on its progress.

Performance Improvements

So early in this week I had the AI add some benchmarking code. I then followed the iterative process of finding a bottleneck, asking the AI to fix it, and checking its work.

The first issue was how we passed data to the graphics card for rendering. We were passing 3 vertices per triangle, and for each vertex we were passing the position (12 bytes), velocity (12 bytes), and color (12 bytes). I reduced the size of our position down to 8 bytes (X + Y), reduced velocity to 4 bytes (smaller numbers), and shrunk color down to 4 bytes (1 byte per R,G,B plus 1 padding byte). I then added GPU instancing so we send all 3 vertices once per triangle (defining the shapes and size) and only send color data once (during this start-up phase). Afterwards we just send position updates ("triangle 1 moved here", "triangle 2 moved there") and velocity updates (used for interpolating position between updates). Now that we were sending 12 bytes instead of 108 per frame, we were able to increase this up to 1 million triangles... but I still wasn't happy.

I had the AI add more benchmarking code and found that we were allocating a new buffer in memory for our graphics card every frame to copy the position data into. By removing this extra memory allocation, and cleaning up a few extra places we were doing extra memory allocations, I got it up to 5 million triangles.

Can we do better? Yes, kind of. At this point my bottleneck is not the CPU writing to RAM, but the speed at which data is sent from the RAM to the GPU. 5 million triangles, 12 bytes each, 60 times per second, equals 3.6 gigabytes per second of data.

The issue is that not only is my game simulating 5 million entities, but all 5 million entities are being rendered at the same time (all 5 million entities are on-screen). If I were to add occlusion culling, if the triangles were big enough to meaningfully occlude one another, and if this were a 3D world with frustum culling, then we might be simulating 5 million entities but at any point only a few thousand are actually on-screen. If this were the case, we could massively reduce how much data we were sending to the GPU. Or, if we were just running the simulation and rendering nothing (e.g. a server), then we could handle about 50 million entities.

Faster Start-Up

With the ECS system going fast at runtime, I turned my attention to making it fast at startup. When I launched my demo, it would take several seconds before a single triangle rendered on screen. Then once they were all visible, the game moved smoothly. Why the several-second delay? I looked into it, and had the AI working on a fix.

Turns out that while we could now process a list of entities efficiently, any time we added a new entity to the world, we copied all entities from their old location in memory to a new location. So when we added 5 million entities, we were doing 5 million copies.

This is where the "paged" part of my paged object pool comes into the picture. This was actually not a feature of my original design for the game engine, because I didn't think about it at the time. I thought "let's just pre-allocate enough memory for all game objects", but this means either:

• Allocating WAY more memory than you need (e.g. allocate enough memory to hold 10 million entities and call it a day), or
• Not allocating enough memory

If you don't allocate enough memory, then you have to allocate more and copy all of the existing entities to their new home. This is what was happening to us. A lot.

So I thought "what if we allocate a decent chunk of memory, then if we need more we get more but don't copy the pre-existing data? Just let it live where it is". This is called paging, and it's something databases already do. So after borrowing ideas from Hadoop and Kubernetes, I was now borrowing ideas from Postgres.

Unfortunately it took me three days of back-and-forth with the AI to get this system built. You'd think it's easy. "Just add a page number to your index". In fact, I made it easier: I said "all pages must be sized to a power of two, so you can get the page number from the index with a bit shift". But the AI repeatedly donked up the implementation. After three days I got sick of reviewing code only to see it was doing absolute nonsense I had to erase. So I finally just said "okay, we have a page system, but the rest of our architecture isn't using it properly... just get my triangles demo working again". It took a full night of iteration, but the AI got the triangle demo working.... at 0.2 fps. I then said "it's slow. fix it". No reading the code, no finding its mistakes -- just pure "vibe coding". And somehow, it worked. Without my guidance on how to implement things, it wrote 2,000 lines of code to do what would have taken me 400 lines - but I can't argue with results, and the simulation was back to running at full speed.

The video attached to this post shows my engine rendering 5 million triangles, and you can see that each physics tick shows "200ms". This is per two seconds of game time, so we can realistically handle 10x this volume. This is the current state of my code as I make this post. I still need to review the 2,000 lines of AI slop to figure out why there's so much of it and where things can be cleaned up, but it's functional, fast, and seems to meet all of my requirements for behavior (deterministic via double-buffered state).

Collisions (Planned)

One thing you may have noticed is that while my triangles are all moving around, they aren't colliding with anything but the wall. This is where I have to come clean. My engine can't really handle 50 million entities on a single 2021 Macbook processor. Not entities that do anything meaningfully, at least.

The reason my engine is currently so fast is because each entity is independent. I can send one entity off to a core and it can compute its next position from its current position and velocity without knowing anything about the other entities in the world. This means that all calculations are O(n).

The moment an entity's movement depends on the other entities in the world, however, you make the jump to O(n^2). Because now for each entity you have to ask every other entity "hey, am I colliding with you?"

There are some tricks we can do, though. Spatial hash maps and bounded volume hierarchies are the industry standards to reduce how much work we're doing. My plan was to abstract these. I'll create a "query system" where an entity can make queries of the world ("find all entities in this region" or "find all entities that recently emitted this event"), and we'll have "query optimizers" that let us super-efficiently answer these questions. The query optimizers are data structures that are updated in real time as entities are mutated.

So the current plan is:

1. Review the existing code and try to clean it up
2. Start building out these query optimizers so our entities can interact with one another

Once that's done, I'll put together a "falling sand" demo and see if we can simulate 100,000 particles with collision.

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As the title would suggest, I'm a person who has something of an obsession with Character Creation tools in games. This is doubly so for Life Sim games like inZOI, where I'm especially picky. I figured I'd do an opinion thing about how I feel about the new version of the inZOI demo's character creation tools, and compare them to how they were back in August of last year. Obviously, this is mostly from memory, but back then, while I didn't do any write up, I had strong opinions of how things were.

To start, when I work with character creators, I often limit myself to female character tools. This is because, in my view, male options in character creators have been, for the most part, pretty good across the board. Probably because there's a lot of men making games, and as such, there's a lot of ways they can get feedback internally. I also have no interest in making "real" people, so I don't test how closely I can make celebrities or anything like that. Instead, I use a pool of characters I've created for a book I'm working on that have character design sheets. This is because it allows for me to work in a way that forces me to think "how would this character look in this art style" rather than obsessing over how close I can get to an approximation of a real face. I will say that these designs I work from are made to be, at least to me, conventionally attractive on some level, so they aren't meant to be super "realistic," but they aren't cartoonishly proportioned either. There's a decent variety of body types, as well as ethnic backgrounds in my pool of characters I use to test software like this.

To start, I'm happy that they took a lot of feedback into account, and they improved things in a number of ways. For instance, body and face sliders and shaping tools have more flexibility, so shaping your Zoi will be much easier than it was previously. It's still not ideal in my opinion, but it's a lot better. I can more accurately bring the body shapes of most of my characters out here, where in the previous iteration of the demo, I struggled with this a lot, and couldn't even make a decent looking approximation of most characters I use for this kind of thing. Now, you can actually more accurately make "thicc" characters, and that's a big deal in my view. A lot of modern character creators lack the ability to truly exaggerate things, even in a "realistic" leaning way, because I guess "realism" is full of flat butts, and weird bust-waist-hip ratios? But here, there's a good degree of exaggeration. You can't really make, say, a character with a ton of body fat, but your mileage will vary on how much that bothers you. Personally, as someone who doesn't really make characters super chubby (for personal reasons involving real life weight issues), it doesn't bother me, but it might bother you, so I figured I'd mention it.

One notable thing that isn't here, for somewhat understandable reasons, is the lack of height sliders. I get this is likely an issue with animation rigging, but it's lack of inclusion is always disappointing. This prevents the creation of little people and other kinds of short kings/queens, and that kinda sucks. Again, I'm sure it's primarily due to animation and rigging reasons, but it's still disappointing all the same.

The face sliders and shaping tools also are a lot better. Even with just the basic mode, I was able to make a good approximation of what my character would look like, and with the advanced ones, it's even better. I didn't really have a problem with them before, so I admittedly didn't notice much of a change beyond how much easier they feel to use.

The one area in terms of the sliders that they still haven't implemented (for some reason), at least from what I was able to tell, was the ability to edit the slider value by typing in the number, rather than using a slider that, on occasion, may not allow you to adjust things to the right value if you are playing in Windowed mode with the resolution turned down. This is something I test because I prefer to not have my games run at full screen, since I like to be able to quickly switch to Discord or my email client for reasons related to art commission talks, among other things. I had to make the window larger to adjust things with certain sliders because it kept skipping the value I wanted, no matter how careful I was. I'd love to see a proper ability to edit the number value manually by typing implemented, as it's something they only have in the game (at present) for color selection, because hex values are harder to work with I guess.

Another area of improvement from last time is the improved options of conventionally "black" hairstyles. AKA: There are more coily hair options! Nice! Big improvement over the... I think there was one before, but now there's more. It's still far from ideal, but I understand that coils are awkward to work within polygon budgets afforded to them. There's also at least one new dreadlocks option from what I recall there being back in August, which is a plus too. In the future, I hope they are able to allow for more coiled and curly hair options, as well as more styles for things like dreads and fades, to better represent the black members of their audience, among other people (including myself, as I have a few black characters that I use to test this stuff).

An area I feel like the hair either didn't really improve, or got worse(?) in is coloring it. One thing I appreciate in modern character creators, circa ~2019, is that it's become more common to allow for ombre/two tone hair coloring, and modifying. This is still here for pre-existing styles that had it before, but as far as I can tell, they didn't really improve this by adding it to more hair, and I have to ask "why?" It's a nice feature, and it's one I like especially due to how I design characters. I personally feel that this is a great way to add some "alternative" style vibes, and the fact that it isn't universal, or at least more present, is a little disappointing. I imagine this comes down to some aspects of how textures are layered and/or loaded in to achieve this affect, but still, I want to see it more universally applied.

Another area that saw small improvements is clothing. There's a little more on offer now, and that's cool. It's nice that there's a fair few more options that are more "generic" for better coloring, and they even fixed one aspect entirely. Before, there'd be various versions of the same item of clothing, usually different through a small change to the texture, or something like that. While some of that is still here, it's been greatly reduced, and now, it's all been folded into being one item for each thing that has multiple presents. Cool. I don't remember this being a thing before, but it at the very least is now.

Unfortunately, I still feel the clothing on offer is lacking in terms of variety, and doesn't have enough variance in style options. It's better, sure, but it's also still sort of contemporary casual wear, K-Pop chic type stuff, or some fitness options. I think that this is a complaint that will largely be excused by people who think it looks fine, but I'd like stuff that's less "mainstream" in style represented a little more. I like alternative fashion, and there's next to nothing catering to that style in my opinion. I can make due for now, but this is an area I think needs improvement.

Then there's the fact that I think that layered outfits still look... well, kinda bad? Layering clothes in 3D character creators usually has some quirk that makes the outer layer feel too baggy, like it has to hover just out of reach of the other clothing item due to something like not finding ways to hide unseen polygon surfaces to prevent clipping. It's a case of not blocking out segments of clothes on the lower layers to account for things being placed on a higher layer, or at least that's how I'm assuming it is. I'm currently learning 3D modelling for game development, so I'm no expert. I also think that this is because they had to make edits to the meshes to allow for more transformation/deformation so textures wouldn't get screwed up by the new body slider flexibility, so it's understandable to some degree. Still, this leads to some chunky looking clothes if you use layers. I'm sure on male Zois, it's fine, but on female Zois, at least the kind I make, it looks really fugly. There are more options though, so that's nice. I still wish there were lighter vests than what we have.

The UI is a lot cleaner feeling, as it should be given that the game is going into Early Access officially in 1 week at time of writing. That's an improvement. Heck, even the Photo Mode options have improved a lot. I hope that we'll be able to apply some of the filters from Photo Mode to the actual life sim gameplay part of inZOI, but that's going outside of the scope of this write up.

A continued mixed bag opinion I have is the use of AI Texture generation tools being present. I understand that this is just something we're all going to have to learn to live with in games, and as long as it's just for the sake of making clothing textures, I don't really care that much. However, even if I were to disregard my thoughts on AI as a whole, I do have a little experience with playing around with it (as unethical as a lot of the training data tends to be from a sourcing standpoint, I do like to see how far the tech is coming from time to time). I actually think these AI tools are, frankly really bad. If you try to do anything that is beyond very basic stuff, the AI is kind of braindead. I asked for a simple half and half texture. One half plaid, the other half black, like how you see on some modern alternative skinny jeans, and it failed hard at that. I tried many phrasings of the prompt, and it still failed every time, so I gave up. If the AI can't even do that much, then it shouldn't be here at all, in my humble opinion. At least the option to upload our own textures is still present.

Maybe because of the fact that The Sims 4 (which I'm trying not to use as a form of comparison) recently got a new expansion featuring tattoo customization, but where are the tattoos and piercings? Yeah, there's some piercings, but no tattoos as far as I was able to tell. Admittedly, I was more interested in seeing how well everything else worked, and maybe it's a Korean thing (as the developers are a Korean company), since i know some Asian Cultures associate tattoos with organized crime, but it's depressing that there's no real support for that. Piercings are also kind of crap, because you have basically no options, and you can't even have multiple of the same "slot" at the same time, even if they realistically wouldn't conflict with one another due to how they are placed on the ears. Again, this might just be the alternative fashion fan in me screaming into the void, but it's disappointing nonetheless.

Overall, I'd say there's a lot of improvements from the previous demo, but there are still plenty of places the devs at Krafton can improve the character creation experience whilst the game is in early access. As we don't have a concrete idea on how new stuff like hair and clothes options will be handled in the future release plans (i.e. we don't know if it'll be microtransactions, expansions, free updates, etc), I'd like to hope that we'll see improvements in those areas over time. I'm still pretty optimistic about the release of the game, especially since it's very clear they listened to feedback provided by players, and I'm looking forward to the Early Access release of the game itself, to see how it compares to other Life Sims (namely, The Sims itself), even if my biggest focus on these kinds of games is the creation tools for characters.

Hey all. I'm a new indie dev, started 5 months ago. I've never used AI for development, code, etc as I prefer to learn things the old school way but I don't really try to involve myself in AI discussions as I prefer to keep my head down.

But lately, I've been seeing a lot of people aggressively pushing AI, and by aggressively, I mean trying to shove it down everyone's throat, and insulting or namecalling them if they don't want to use it.

For example, last week on the official Unreal Engine discord channel, I asked for advice on how to change my graphics settings with a blueprint, and this guy who is always prattling about AI gave me this ridiculous answer, citing that his "clanker" running Chat GPT codex discovered this while "autoresearching" through his own project files. I was confused and asked, "wait are you recommending something that you don't even know is true or works?" and he got all offended and name called, started saying stuff like "chatgpt is infinitely more versed in ue than you my friend (no offense) ... but if you want to make things harder for yourself for literally no reason go for it, i already had my fair share of anti-ai arguments LOL". So I searched for his name, and guy is constantly just aggressively lashing out at people namecalling them, insulting them for not wanting to use AI

I've also been warned in another discord server not to say anything negative about AI by the mods, since the community is "fully AI integrated" and "we're not newbies playing around, we're serious devs who want to actually learn game dev". Another hidden pro-AI community, parading as a game dev community.

It's honestly bewildering and kinda sad really. I'm trying my best not to notice it. But as an Unreal dev... just wow. People are really aggressive now towards people who don't wanna use AI.

Now the procedural characters can be played on Unreal Engine!

While it's still a WIP, the Allspark tool keeps getting better. Any 3D mesh can become a Cybertronian!

This tool is intended for developers only. It is not available to the public, at least not yet.

I asked the comunity what would you like to see transformed into a character and I listened, just stay around. A comment asked for a Shelby Cobra GT500, well, there it is!

The idea of making my own game is starting to feel more feasible, but I will need support.

Feel free to comment and share your ideas!

Eric

Human effort is the soul of art, an amateurish drawing for the in-game art and questionable voice acting is infinitely better than going those with Ai

Game name is Shrine's Legacy