Credit to original comic for the inspiration: @system32comics

Dessa is a full-duplex speech-to-speech model that you can run on consumer GPUs.

This is a GPT3 moment for speech.

I’ve been experimenting with AI image generation, trying to figure out why so much of the artwork has that instantly recognizable AI look.

You know what I mean. The excessive glowing edges, bizarrely detailed textures, unnecessarily dramatic lighting, overcrowded compositions, and typography that seems designed to be impressive rather than readable.

I have a background in art and design, so I started treating ChatGPT like a junior designer. Instead of just generating new images when something looked wrong, I critiqued specific problems and developed a set of principles to address them.

One of the biggest discoveries was that reducing clutter isn’t the same as changing styles. When I criticized a neon-heavy poster, AI would often replace it with an equally cluttered vintage poster. Different aesthetic, same underlying problems.

Eventually, we developed 43 principles across composition, typography, texture, lighting, and artistic direction.

I’m sharing them because I think they could be useful for anyone working with AI-generated images, whether you’re an artist, designer, or just someone tired of everything looking like the same over-processed fantasy illustration.

The overarching philosophy: Design should look intentional, not merely impressive.

Composition & Visual Hierarchy
Restraint over spectacle. Don’t add elements just to make an image look impressive.
One dominant focal point. Give the viewer something obvious to look at first.
Negative space matters. Empty space isn’t a problem that needs fixing.
Remove unnecessary elements. If something isn’t contributing to the design, get rid of it.
Complexity needs a purpose. Intricate artwork is fine. An uncontrolled composition isn’t.

Typography
Legibility comes first. Don’t sacrifice readable letters for decorative effects.
Integrate typography into the composition. Text shouldn’t look randomly pasted over an illustration.
Limit competing type treatments. Not everything needs outlines, shadows, gradients, and a different font.
Create a clear reading order. Title first, essential information second.

Content & Communication
Stop adding lists to every flyer. Unless specifically requested, avoid cramming in lists of attractions, features, or activities.
Use only necessary copy. AI loves inventing taglines and promotional filler. Most designs don’t need them.
Show rather than explain. Let the artwork communicate the concept.
Don’t invent details. Fake addresses, dates, prices, and QR codes aren’t useful design elements.

Avoiding Generic AI Aesthetics
Stop defaulting to AI clichés. Neon, glowing particles, lens flares, excessive gradients, and dramatic lighting shouldn’t be automatic.
Polish isn’t originality. An elaborate image can still be completely generic.
Avoid stock-image thinking. Develop imagery around an actual concept.
Not everything needs to be cinematic, mystical, or ornate. Sometimes a simple illustration is more interesting.
Choose a coherent visual direction. Color, imagery, typography, and texture should feel like parts of the same design.

Working With AI as an Art Director
Treat criticism as art direction. Fix the underlying problem instead of making cosmetic adjustments.
Don’t replace one cliché with another. Switching neon clutter for vintage clutter isn’t an improvement.
Preserve what already works. When revising, don’t randomly change successful elements.
Critique the result before presenting it. Check hierarchy, legibility, unnecessary details, and visual coherence.
Don’t automatically agree with every criticism. Good creative collaboration includes independent judgment.
Material Authenticity & Texture
This was probably the most interesting part of the experiment.
There’s a particular texture that seems to appear in an enormous amount of AI-generated art. Everything looks simultaneously painterly, photographic, grainy, and digitally sharpened.
The stone, clouds, fabric, skin, and foliage somehow all share the same artificial surface quality.
These principles specifically target that problem.
Texture needs a reason to exist. It should come from the material, artistic technique, or environment.
Materials should look different. Stone shouldn’t have the same surface treatment as fabric or skin.
Avoid universal grain and distressing. Don’t coat the entire image in the same scratches, speckles, or artificial noise.
Choose a coherent artistic medium. Photography, illustration, painting, printmaking, and 3D rendering have different visual languages.
Avoid accidental medium mixing. Photographic anatomy combined with painted clouds and digitally rendered architecture can create an inconsistent result.

Detail & Visual Information
Establish a hierarchy of detail. The focal point can be highly resolved while secondary elements remain simple.
Allow quiet surfaces. Not every shadow, wall, or patch of sky needs intricate texture.
Avoid artificial microdetail. Tiny scratches, pores, and surface patterns don’t automatically make an image better.
Focus on large shapes first. Silhouette, proportion, and value structure matter more than decorative detail.
Use selective sharpness. Everything doesn’t need to be equally crisp.
Stop faking craftsmanship with texture. Random distressing isn’t a substitute for deliberate mark-making.
Lighting & Tonal Control
Lighting needs consistent logic. Highlights and shadows should follow a believable or intentionally stylized lighting scheme.
Stop outlining everything with glowing rim lights. It’s one of the most recognizable AI habits.
Let shadows stay dark. Not every dark surface needs artificially revealed detail.
Control microcontrast. Excessive local contrast makes everything look hyper-sharpened, metallic, or wet.
Use atmospheric effects selectively. Fog, bloom, haze, glowing particles, and light rays should exist for a reason.
Artistic Process & Authenticity
Design for a believable production method. The artwork should feel like something that could have been photographed, illustrated, painted, printed, or otherwise intentionally created.
Respect the limitations of the medium. If you’re imitating screen printing or lithography, the textures and color separations should make sense.
Imperfections should be intentional. Random scratches and distressed surfaces don’t automatically make something feel handmade.
Actively look for the AI texture signature. Check for repetitive detail, inconsistent materials, overprocessed surfaces, and grain that doesn’t belong. Fix the underlying image rather than hiding it with filters.

The two biggest takeaways
1. Design should look intentional, not merely impressive.
2. Detail should reveal the nature of the subject, not advertise the sophistication of the image generator.
I’m not advocating that every AI-generated image should be minimalist, photorealistic, or resemble traditional artwork. I actually love elaborate, theatrical, and highly stylized imagery.

What I want is intentional complexity rather than visual noise.

One practical technique that helped was evaluating designs at two sizes. At thumbnail scale, look at composition, silhouette, and hierarchy. At full resolution, inspect texture, lighting, edges, and material consistency.
And perhaps most importantly, stop treating image generation as a slot machine. Generating another image isn’t the same thing as improving the design.
These principles don’t magically fix every generation. Even with detailed instructions, the model sometimes repeats exactly the mistake it was told to avoid. But they’ve given me a much better vocabulary for directing and critiquing the results.

I’m curious whether other designers have noticed that distinctive AI surface texture, and whether you’ve found reliable ways to get rid of it.

Also, what principles would you add?

EDIT: Examples added.

Bro asked permission to talk to himself...

I’ve noticed ChatGPT offering worse and worse code recently, getting confused about what I’m asking it and seemingly less efficient at solving issues.

Am I imagining this or is something going on? I did read that there’s a point of diminishing returns where adding more data eventually decreases performance.

Everyone’s talking about AI becoming more and more intelligent but I swear it’s getting worse.

Disclosure: ChatGPT wrote most of this (80ish%) because I’m too lazy to construct the words myself. I asked it to pull together our conversations about this and organize them into a post.

My son is 20, has ADHD, and moved out about two months ago. He works and lives independently, but getting started on overwhelming tasks can be difficult.

One example:

The bedroom he left behind looked like a disaster bomb had exploded in it. He needed to finish clearing it out and cleaning it, but couldn’t get over the hump of starting.

I used ChatGPT to help design an executive function coaching system he could use through his own Plus subscription.

We kept it simple:
1) one main chat for schedule management, email management, goals and check-ins
2) dedicated Projects for bigger tasks so that context would be retained over time. (Register for college, design a video game, prep my living space for a kitten, clean my room, etc)

The instructions tell ChatGPT to ask one question at a time, consider his actual schedule, and give him one manageable next action with a clear endpoint.

He can also ask it something as open ended as “I’m having trouble getting started with my day, review my goals and projects and give me a first step.”

For the bedroom, I had him take a video of the room and ask ChatGPT for help in a dedicated Project. Showing the mess meant he didn’t first have to figure out how to describe and organize it.

One prompt we gave him was: “Help me make a room-cleaning plan with three small steps and breaks. Ask one question at a time, and help me pick a first step that takes five minutes or less.”

He worked with ChatGPT and created a plan with a completion date, time around his work schedule, and specific stages for sorting, packing, cleaning, and moving furniture.

The instructions also cover getting stuck: help identify the obstacle, make the step smaller, and restart after a missed day without piling on extra work.

The final step: I added humorous, automated email nudges from my own assistant, Goose, until his ChatGPT emailed me back and confirmed he’d made the plan, and explained it. Apparently my parenting toolkit now includes an artificial goose with a clipboard.

It’s still early, but so far it’s working extremely well. He has a concrete plan and somewhere to go for help figuring out the next step when the whole job feels overwhelming.

He has started to use it, on his own, to plan, research, and move forward his own goals. The excuses about not having time have completely stopped, he tells me in advance when will be working on his room, what the outcome will be, and then he executes.

I hope this is helpful to other parents!

Prompt: Please could you create me a realistic horse model and walking animation in 3js

Used Terra 6.1 max. This took around 15 minutes and used 30% of my 5H limit (plus).

I first noticed it was going to find horse models online so told it to stop and that it must generate the model itself.

Cool that it made shadows but I probably should have prompted it to be photo realistic

BULLSHITE?!

UTTER bullshite. I don't feel like fully going into what I was talking to it about, but let's pick something similar.

Neither the Hiroshima bomb nor the Nagasaki bomb were very efficient fissioning only an extremely small portion of the fissionables aboard each.

"yes, but with an important clarification"

No there is no "clarification" to what I said UNLESS you are going to introduce, for instance, actual percentages.

It did something similar to saying

"There is no way to determine exactly how efficient either device was".

Uhmm yeah...yeah there is. It's called E=MC2.

Now as I said that isnt' what we were talking about but I said something equally obvious and it argued with me. Repeatedly. Despite the fact the logic was as simple as if A=B and B=C then C=A.

"yes, but with an important clarification".

Grrrrrrrr!!!!

Hello everyone. I do reverse engineering, but what I do is always personal, so I don't work for someone or a company to do RE. The problem I have is the unnecessary safeguards on mainstream AIs, Gemini is the worst in this case, and then it is chatGPT and then Claude in my experience.

Is there any way to fix this issue or any alternative? I really don't have powerful hardware; I have 12th Gen Intel CPU with iGPU. I can't locally host a model, and I don't know what to do.

For example, I have a VM and inside of that I was testing a sketchy "antivirus". it wasn't nod32 or Kaspersky or anything mainstream, it is from an unknown origin, and I wanted to know how it works and what it does, I noticed that virtual memory page exhaustion shuts it down and I figured it out by accident.

Now since I'm working on an "antivirus" and I want to find a way to replicate the same shutdown, AI just freaks out and refuses to help because it is "deactivating a security product". changing the wordings didn't help either.

Either I get "This answer cannot be shown" banner in chatGPT, when I give my IDA output to it, or I get "I'm sorry I can't do X" from Gemini.

I'm tired of wrestling with them

Frequently:

• The answer is obvious from the conversation.

• It offers a choice of two answers that mean the exact same thing.

• It claims the answer is somehow relevant to the advice when it's not.

And of course I keep falling for it and polluting the context with details that have nothing to do with my question. Really frustrating.

Is this good or bad? What solutions?

I just saw when upgrading to the Plus plan that Dots are available in the Pro plan for normal users, so non business. And also in the EU.

Can someone confirm this is true?

For me, Chat and Work have just been merged into one. The usage limits still seem to be separate tho. My 5h limit is completely used up, but I can still use Chat.

Edit: The work limit seems to apply to all models except GPT 6 Sol Instant/Medium High.

GPT-6.1 Sol, Astra, Terra, and Luna all count toward the Work/Codex limits.

I told it "do the math" and it came up with so many formulas that I can not keep up with. It worked for maybe 20 minutes and I can not do anything with the result. Its like a university professor spoke to me explaining stuff I dont know. Asking it "Explain it to me so that I can understand" took an entire hour for the model to break it down and I still dont understand it.

I've been using ChatGPT to generate images for a while, and until October it worked really well. But lately instruction-following seem to have gotten significantly worse.

My biggest issue is that when I ask for six separate images it keeps generating a single collage containing all six, despite explicitly telling it NOT to make a collage. Even after acknowledging the mistake and promising to fix it, it does the exact same thing again. And it keeps apologizing.

It swears up and down the image model hasn't changed recently.

Do you have any insights?

I can't pick a mode anymore when I make a new chat. It defaults to 6 Sol High (highest reasoning option available for that model for me, on Plus sub). I don't see it charging me usage for my messages on this model, so far. I tried Astra XHigh for one simple, short prompt and lost 7% of my 5-hour allowance. Did they combine work and chat today?