Medium: Google Colab, VQGAN + CLIP
Focus: Create and remix surreal environmental scenes
Notes: Remixing visual prompts using vqgan_imagenet_f16_16384 w/ keyword blending. Painting with language—minimal control over textures/worlds but better than nothing. In Disco Diffusion discord. Prompt hacking + collaboration. Prompt engineering = less science, more alchemy. Iteration, randomness, remixing = foundation of AI image generation.
Medium: Midjourney
Focus: Retrying things
Notes: Trying to generate blue-eyed lucy snake (specific morph of ball python) lying in a pile of cigarettes. Keep getting blue-eyed women named Lucy instead. AI completely missing context, fixating on most common usage of individual words. Think the snake + cigarettes = too much semantic bloat for model to handle. (blue eyed + lucy) Model prioritizing human interpretation over literal meaning. Progressively weighting snake.
Medium: Midjourney
Focus: Messing around with aesthetic blends, reference guides
Notes: Night playing with "gas station at night, des moines iowa, gaspar noé movie, hyper realistic, cinematic, dirk dzimirsky painting style" prompts. Liminal spaces + night lighting. People generating a lot of horror scenes + dark scenes on blog / midjourney public forum. Do not like that unreal engine 8k image style. Looking for art that feels “real art”. Gaspar Noé + horror aesthetic helped direct model away from weird fixations. Like the idea of exploring suburbia. Trying to add snake back in too soon but unexpected cinematic quality in lighting. Specific contexts >
Medium: Midjourney
Focus: Experimentation fatigue, noticing things
Notes: Noticing all generated text elements are representing Asian-style characters, vaguely Hangul-inspired? Interesting pattern mimicry + dataset training, lots of faux asian gylphs everywhere. If you don’t input model
Medium: Midjourney
Focus: Just messing around
Notes: /Imagine A mac 10 gun designed by hans wegner, with bang and olufsen wood, white background, detailed, 8k. Surprising architectural discipline, materiality + concept together beyond solo style transfer.
Medium: Midjourney
Focus: Finding focus, subject
Notes: Need a through line to focus the images through abstraction. I think I want to tell the complex story of a midwestern, south korean orphan autobiographically through American realism—an art style I’ve never seen myself represented in. Let’s start here.
THIS IS MY FAVORITE LIGHTING REFERENCE I’VE BEEN USING
Medium: Midjourney
Focus: End up with a deliberate + semi-cohesive “batch”
Notes: Deliberately leaning into abstraction—matching thematic choices to model's limitations. Model mistakes <> creative opportunities. Fragmented faces + distorted features = fragmented identities. Asian-American experience = inherently navigating between worlds; AI's struggle with coherence = conceptually fitting? Technical weaknesses <> thematic strengths. This is starting to feel like a loosely connected but connected batch of something?
Medium: Midjourney
Focus: Trying the norm-core way of doing things
Notes: It’s obviously better, and I love bats. Redshift + diorama prompt browsing on Reddit. Imagine/ diorama ::2 taxidermy bat carved by transparent glass, glowing inside, atmospheric, 3d render, hyperrealistic, redshift render. The current focus path is definitely the one of most resistance but it’s exciting getting something “real” and less confusing / unsettling to look at (fidelity + style intentionality-wise).
Medium: Midjourney V 5.1
Focus: Make a series better than the first series
Notes: Less throwing of words into the void and more refining, remixing, and repeating. Prompting is still chaotic but it feels like I know what kind of chaos I’m looking for.
Medium: Midjourney
Focus: Playing with the easily recognizable
Notes: Kirby is culturally sticky, placing him in front of the Brooklyn Bridge yields near perfect results after 1 level of upscaling. Familiar IP is frictionless, it’s trained in the model at every level (shape, context, color, emotion). Not generating but recalling, prompt privilege. The shorthand is fun but what about forging more unique styles? Does it mean anything if a generation requires more “work” than another.
Medium: Midjourney V4
Focus: Create and remix surreal environmental scenes
Notes: Remixing visual prompts using vqgan_imagenet_f16_16384 w/ keyword blending. Painting with language—minimal control over textures/worlds but better than nothing. Joined Disco Diffusion Discord. Prompt hacking + collaboration. Prompt engineering = less science, more alchemy. Iteration, randomness, remixing = foundation of AI image generation.
NO IMAGE PROMPTING, BUT ADDING IN A LOT OF DETAILS I’M NOT WANTING HERE
Medium: DALLE 2
Focus: Create and remix surreal environmental scenes
Notes: Training data priorities showing through, styles and consumer products + text well-and better-represented, but complex forms still challenging. Everything struggles so much with mundane objects. Feels like we’re going backwards so going to leave this for now. Text better, but still a lot of bloat and generative hallucinations.
Medium: Midjourney
Focus: In achieving editorial qualities for potential professional swipe
Notes: I lead digital for a Soho agency so the stump hands and crazy eyes aren’t giving me a teachable moment. Editorial aesthetics needed. Found adding "SSENSE model" to prompts heightens the editorial style of subject (more Vogue less Better Homes & Gardens). Testing photographer names in prompts. "Tyrone Lebon" = desaturated, pose abstraction. "Petra Collins" = ethereal, Gaussian blur, reliably. Using real photographers' styles—where's the line between reference/appropriation?
Medium: Midjourney
Focus: Introducing deliberate flaws for “authenticity”
Notes: The AI perfection is becoming easy to spot, I want to push against the model’s default output and work towards something more imperfect, textured, human, recognizing reality through asymmetries + inconsistencies. Uneven lighting, lens flare, surface flaw, analog texture, “bad” compositions. Not framatic, but residual. Simple + broken context.
Medium: Midjourney, Stable Diffusion
Focus: Directional Specifity <> Generational Chaos
Notes: Pose guidance, img2img in Stable Diffusion to refine texture and light. Midjourney for vibe seeding in early stages, SD to turn images from a face to a presence.
Medium: Midjourney
Focus: Throwing things into the blender to see what happens
Notes: The tool is still making decisions and you’re just spectating with better taste than it. There’s something nice but also lazy about how /blend doesn’t really even require language.
Medium: Midjourney + Stable Diffusion
Focus: Temporary tattoos?
Notes: Last minute ask to create temporary tattoo flash sheet for friend’s birthday party, Libra Ressurection. Midjourney / SD with some quick text lockups and it’s done.
Medium: Stable Diffusion
Focus: Try and style Cartier imagery into a Neo Yokio-esque anime rip
Notes: The more prompt sensitivity, the more capitalism meets melancholy, the diffused light, soft midtone zone really gives it that anime treatment.
Medium: Multi-Platform Flow
Focus: Mini Trailer w/ integrated tools
Notes: In variance complicated but also alarmingly simple workflow using multiple platforms. SD + MJ for base images. Luma/Kling for video. Tried ElevenLabs for voiceover but sounded off— modified my own voice instead (it was giving me a South African accent through11). Animation control lacking, lean toward abstraction. First foray in video. File transfers between tools tedious. Final output on main page.
Medium: Chat-GPT 4o
Focus: Moore’s Law on Steroids + Quality Leaping
Notes: Industry and timeline hyperventilating over Totoros and considering implications of the future. Micro-asymmetries making everything look less AI. People’s Moore's Law prediction from 2023 completely wrong (mine right). Editorial models now nearly indistinguishable from stock photos, text generation finally works (even across font types).
Medium: Chat-GPT 4o
Focus: Revisiting American Realism style for my lived experience
Notes: Big difference now: model gets it. Less like prompting, more like art-directing a memory. Not just any Korean-American girl in 1950s scene, but the right one at the right time in the right place. Direct from photographs, or through reference and memory.
Medium: KreaAI
Focus: Checking in on 3D capabilities
Notes: Took betty boop screenshot, fed into Krea newly announced 3D model generated, output GLB, converted GLB to USDZ for easy access through Apple’s Quick Look. Lacks sophistication but it’s not soon before long.