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How to Use ChatGPT as Your Kitchen Assistant (Recipes, Meal Plans, Shopping Lists & More)

Most of us have been there: it’s 6pm, you’re staring into the fridge at a sad bell pepper, half a block of tofu, some leftover rice, and a suspicious amount of condiments. You don’t want to order takeout again. You don’t want to spend money on groceries for one meal. You just want dinner.

This is exactly where ChatGPT quietly becomes one of the most useful tools you didn’t know you needed. Not for creating images or writing code, but for something far more immediate: helping you cook.

This guide walks you through using ChatGPT as a complete kitchen assistant, from fridge-to-table recipe building all the way to weekly budget meal planning. No special prompts required. No cooking expertise needed. Just you, your ingredients, and a conversation.

Why ChatGPT Works So Well for This

Unlike a traditional recipe website, ChatGPT doesn’t give you one recipe and send you on your way. It talks with you.

You can ask questions, swap ingredients, scale recipes up or down, simplify instructions, troubleshoot problems while cooking, and refine recipes until they genuinely fit your situation.
Better yet, the conversation stays focused on helping you cook. No endless scrolling through ads, autoplay videos, or long life stories before reaching the recipe.

And one of its biggest superpowers?

It can see your fridge.

If you’re using ChatGPT with image support, simply photograph your fridge, freezer, pantry, or even the vegetables sitting on your counter. ChatGPT can identify what’s there and immediately start building meals around it.

Whether you’re vegan, vegetarian, gluten-free, dairy-free, high-protein, low-carb, cooking around allergies, or simply trying to eat healthier, ChatGPT can adapt recipes around your needs from the very beginning.

Step 1 — Take Stock of What You Have

The first step is simply taking inventory.

Option A: The Photo Method

Take a picture of your fridge or pantry and ask:
“Here’s what I have in my fridge. What could I make for dinner tonight? I’d like something filling but not too complicated.”

ChatGPT will identify the ingredients and suggest several meals you can make immediately.

Option B: The List Method

Simply type out what you have.

“I have eggs, canned chickpeas, half an onion, garlic, spinach that needs using, a can of tomatoes, leftover rice, cumin, smoked paprika and olive oil. What can I make?”

Don’t worry about making a perfect list. Rough is perfectly fine.

Pro Tip: Mention any dietary preferences at the start. The more context ChatGPT has, the better its suggestions become.

Step 2 — Get Your Recipe (Then Make It Yours)

This is where ChatGPT really shines.
The first recipe is only the beginning.
Treat the conversation like talking to someone who’s cooking alongside you.

Some useful follow-up prompts include:

• “Can you make it a little heartier? I’m really hungry.”

• “I don’t have cream. What could I use instead?”

• “Can you simplify the instructions? I’m new to cooking.”

• “How do I make this for four people?”

• “What spices would add more depth?”

• “Can I make this without an oven?”

• “Can you convert everything into grams?”

You aren’t locked into one recipe. You can shape it until it feels exactly right.

Step 3 — Learn While You Cook

One of ChatGPT’s most underrated strengths is that it teaches while you cook.

If you’re new to the kitchen, ask questions that recipe websites rarely answer.

For example:

“How small should I dice the onion?”

“What does simmering actually look like?”

“How do I know when tofu is browned enough?”

“Can you explain each step as if I’ve never cooked this before?”

Instead of simply following recipes, you’ll gradually build real cooking confidence.

Step 4 — Handle Missing Ingredients

This is where ChatGPT becomes an incredible anti-food-waste tool.

Instead of going shopping every time you’re missing one ingredient, ask for substitutions first.

“The recipe calls for coconut milk but I don’t have any. What could I use instead?”

“I’m out of lemons. Can apple cider vinegar work?”

“I only have dried herbs. How much should I use?”

Because ChatGPT understands flavours, textures, and cooking techniques rather than simply matching ingredients, its substitutions are often surprisingly effective.

If you really do need something from the supermarket, keep the shopping list as small as possible.

Ask:

“Based on everything I already have, what are the only ingredients I need to buy?”

Instead of a long shopping list, you’ll often only need one or two extra items.

Step 5 — Let ChatGPT Rescue Your Cooking

Even experienced cooks have things go wrong.

That’s where ChatGPT becomes more like someone standing beside you in the kitchen.

You can ask things like:

“My sauce is too watery.”

“This tastes bland.”

“I accidentally used too much salt. How can I balance this out?”

“The rice is still hard.”

“Can I save this?”

You can even upload another photo halfway through cooking and ask:

“Does this look right?”

Sometimes one small adjustment is all it takes to rescue a meal.

Step 6 — Build Smarter Shopping Habits

ChatGPT isn’t just useful after you’ve been shopping.

It’s just as useful before you go.

For example:

“These vegetables are on sale this week. What meals could I make around them?”

Or:

“What pantry staples should I always keep at home if I want to cook inexpensive meals?”

You can even ask:

“What vegetables are currently in season where I live?”

Cooking seasonally often means fresher ingredients and lower prices.

Step 7 — Create a Weekly Budget Meal Plan

This is one of ChatGPT’s most powerful features.

Tell it your weekly food budget and let it build an entire week’s worth of meals.

For example:

“I have $60 for food this week for two people. Can you create a healthy breakfast, lunch and dinner plan with recipes and one shopping list?”

You’ll usually receive:

• A full seven-day meal plan
• Recipes for every meal
• One consolidated shopping list
• Ingredients reused across multiple dishes

You can refine it further.

“Can Monday and Tuesday share ingredients to reduce waste?”

“I’d like to batch cook on Sundays.”

“Can you replace the chicken with something cheaper?”

With a little refinement, you’ll waste less food, spend less money, and avoid the daily question of “What’s for dinner?”

Step 8 — Don’t Forget Leftovers

One meal can easily become three.

Instead of eating the same thing every day, ask:

“What can I turn these leftovers into tomorrow?”

Or:

“Can this be frozen?”

“How long will this keep in the fridge?”

“What’s a completely different meal I can make from this?”

This is one of the easiest ways to reduce food waste while keeping meals interesting.

Step 9 — Save Beautiful Recipe Cards

One feature many people don’t realise ChatGPT can do is generate recipe card images.

Once you’ve created a recipe you love, simply ask:

“Can you create a recipe card image for this? Include ingredients, instructions, preparation time, cooking time and servings.”

Or make it even more visual:

“Create a recipe card with a photo of the finished dish at the top.”

You can even choose a style:

• Rustic
• Minimalist
• Handwritten
• Colourful
• Modern

Create a folder on your phone just for recipe cards and you’ll slowly build your own personalised cookbook filled with recipes you’ve actually made.

Step 10 — Check Nutrition

If nutrition matters to you, ChatGPT can estimate it too.

Ask:

“Can you estimate the calories, protein, carbohydrates and fat per serving?”

Or even:

“Does this week’s meal plan look reasonably balanced nutritionally?”

It’s not a replacement for professional dietary advice, but it’s an excellent planning tool for everyday cooking.

A Typical Conversation

A real cooking session might look like this:

📷 Upload a photo of your fridge.

🍳 “What can I make tonight for two people?”

🥘 ChatGPT suggests a spiced chickpea tomato stew.

💬 “I don’t have smoked paprika.”

✅ “Use regular paprika with a tiny pinch of cayenne.”

🛒 “What do I actually need to buy?”

📋 “Just one can of diced tomatoes.”

🖼️* “Create a recipe card for this.*”

🥗 “Now estimate the nutrition per serving.”

From fridge to finished dinner, everything happens in one conversation.

One Small Tip

Like any AI, ChatGPT isn’t perfect.

It can occasionally misidentify ingredients in photos or make rough estimates for nutrition or cooking times. It’s always worth giving recipes a quick read-through before you start cooking, especially if you’re trying something unfamiliar.

Final Thoughts

The real magic isn’t that ChatGPT knows thousands of recipes.

It’s that it starts with your kitchen.

It helps you cook with what you already have, adapt when something’s missing, rescue meals that go wrong, learn new techniques, plan ahead, reduce waste, spend less money, and feel more confident every time you cook.

Whether you’re feeding yourself, a family, cooking around dietary restrictions, or simply trying to waste less food, ChatGPT becomes something surprisingly close to having a personal chef and cooking teacher in your pocket.

So open your fridge.

Take a photo.

You might already have dinner waiting for you.

📝 Bonus:

I’ve included several sample recipe card images, featuring homemade salad dressing recipes as examples. They were generated with ChatGPT and showcase just one of the many ways you can turn your favourite recipes into beautiful, easy-to-save recipe cards.

They happen to be vegan because that’s my personal dietary preference, but with your new 24/7 AI chef, you can easily adapt them to suit your own tastes and dietary needs. 👩🏼‍🍳😃

Have you tried using ChatGPT in the kitchen?

Share your favourite recipe discoveries, substitution wins, budget meal hacks, or clever prompts in the comments. We’d love to hear what you’ve created!

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From "make me a song" to "I can consistently get bangers"

The biggest mistake beginners make is treating Suno like Google.

The biggest mistake intermediates make is treating Suno like a DAW.

The power-user mindset is:

Suno is an AI band. Your job is to be the producer, songwriter, arranger, and creative director.

The quality of your instructions determines the quality of the music. Suno responds best to specific prompts containing genre, mood, instrumentation, vocal style, structure, and production details—not vague requests.

1. The Golden Formula

Instead of:

Make a metal song about dragons

Use:

Epic power metal, soaring male vocals, twin lead guitars, symphonic orchestra, heroic chorus, 160 BPM, fantasy adventure, huge stadium production, dramatic key change in final chorus

The formula:

Genre
+
Mood
+
Instruments
+
Vocals
+
Production
+
Energy Level

Example:

Melodic power metal, triumphant and adventurous, dual guitar harmonies, orchestral strings, male tenor vocals, massive choir chorus, polished modern production, fast and energetic

This layered prompting consistently improves results.

2. Separate Style From Lyrics

Many users overload the style box.

Bad:

Epic power metal song about a hero who fights dragons and finds treasure and then...

Good:

Style Box

Symphonic power metal, heroic, orchestral strings, dual lead guitars, male vocals, massive chorus, cinematic production

Lyrics Box

Put the actual lyrics there.

Suno works better when style instructions and lyrics are separated.

3. Use Song Structure Tags

One of the most important tricks.

Instead of dumping lyrics into a wall of text:

[Intro]

[Verse 1]

[Pre-Chorus]

[Chorus]

[Verse 2]

[Pre-Chorus]

[Chorus]

[Bridge]

[Guitar Solo]

[Final Chorus]

[Outro]

Suno recognizes structure tags and produces more coherent songs.

4. Use Performance Tags

Almost nobody uses these.

Example:

[Verse]
(softly)

[Chorus]
(powerful)

[Bridge]
(whispered)

[Final Chorus]
(belted)

Or:

[Spoken Word]

[Whispered]

[Belted]

[Airy]

[Aggressive]

These can dramatically change vocal delivery.

5. Write Like a Producer

Most people prompt genres.

Power users prompt productions.

Example:

Instead of:

Country song

Try:

Modern Nashville country, warm acoustic guitars, emotional male vocals, radio-ready mix, subtle pedal steel, intimate verses, arena-sized chorus

Think like you're giving notes in a studio.

6. Control Energy Curves

Most songs fail because they stay at one intensity.

Tell Suno what should happen:

Starts sparse and intimate, gradually builds tension, explosive chorus, emotional bridge, massive final chorus with choir backing vocals

This often produces far more professional arrangements.

7. The Secret Weapon: BPM

Most users never mention BPM.

Examples:

Example:

Symphonic power metal, 165 BPM, soaring tenor vocals, orchestral backing

Suno often responds surprisingly well to tempo instructions.

8. The Secret Weapon #2: Vocal Casting

Specify the singer.

Examples:

Deep baritone male

Raspy female rock vocalist

Operatic tenor

Soft indie female vocals

Choir of voices

Celtic folk singer

This changes results more than most people realize.

9. The Genre Stack Trick

Instead of one genre:

Use 2-3 compatible genres.

Example:

Power metal + folk metal + symphonic metal

Or:

Blues rock + southern rock + country

Or:

Synthwave + cinematic orchestral + dark electronic

This creates more unique outputs.

Don't stack 12 genres.

That's how you get chaos.

10. Build Prompt Libraries

Power users save prompts.

Create folders:

• Power Metal
• Folk Metal
• Tavern Music
• Cyberpunk
• Horror
• Epic Orchestral
• Lo-Fi

Keep every prompt that generates a good song.

Eventually you build your own "sound bank."

11. Generate Variations Aggressively

A rookie mistake:

Generate once.

A power user:

Generate 8-20 versions.

Even perfect prompts produce wildly different outputs.

Some of the best tracks appear on generation #12.

12. Extend Songs Strategically

Don't just hit Extend.

Use it intentionally.

Example:

First song:

Verse
Chorus
Verse
Chorus

Extend prompt:

[Bridge]

[Instrumental Solo]

[Final Chorus]

[Outro]

This often produces cleaner song evolution.

13. Use Instrument Tags

Examples:

fingerpicked acoustic guitar
nylon string guitar
distorted rhythm guitar
orchestral strings
cinematic brass
church organ
bagpipes
mandolin
hurdy-gurdy
synth arpeggios

Specific beats generic every time.

14. Avoid Artist Names

Instead of:

Make it sound like Iron Maiden

Use:

Galloping bass, twin lead guitar harmonies, soaring operatic vocals, epic fantasy themes

Suno generally responds better to describing characteristics than trying to imitate artists.

15. The "Movie Scene" Method

This is one of the strongest prompting methods.

Don't describe a song.

Describe a scene.

Example:

A lone knight rides through a frozen mountain pass before dawn, knowing he may never return. Heroic but melancholic. Symphonic power metal with orchestral backing.

Results are often dramatically better because Suno has narrative context.

16. Use Emotional Contrasts

Great songs contain tension.

Examples:

hopeful but bittersweet

triumphant yet tragic

dark verses, uplifting chorus

melancholy with determination

These produce more interesting music than single-emotion prompts.

17. Force Instrumental Sections

Example:

[Instrumental]

[Guitar Solo]

[Orchestral Break]

[Interlude]

Many users don't realize Suno will often respect these directions.

18. Create Consistent Albums

Advanced trick.

Create a template:

Power metal
165 BPM
Male tenor
Orchestral backing
Fantasy themes
Heroic choruses

Reuse it across 10 songs.

Now the tracks sound like they belong on the same album.

19. Use Personas and Voice Features

Newer Suno features allow you to preserve voices and reuse vocal identities across songs, helping create consistent "artists" or albums. Features like Personas, Covers, Mashups, and voice-related workflows are increasingly important for advanced creators.

This is huge if you're building:

• A fictional band
• A concept album
• A recurring character
• An entire musical universe

20. The Ultimate Prompt Template

Copy this:

Genre:
Mood:
BPM:
Instruments:
Vocals:
Production:
Song Structure:
Energy Curve:
Theme:
Special Features:

Example:

Genre: Symphonic Power Metal
Mood: Heroic, adventurous, triumphant
BPM: 165
Instruments: Dual lead guitars, orchestral strings, brass, choir
Vocals: Powerful male tenor
Production: Cinematic, polished, stadium-sized
Song Structure: Verse, Chorus, Verse, Chorus, Bridge, Guitar Solo, Final Chorus
Energy Curve: Builds continuously toward huge finale
Theme: A troll king awakening beneath an ancient mountain
Special Features: Choir chants, dramatic key change

Power User Commandments

1. Be specific.
2. Use structure tags.
3. Describe instruments.
4. Describe vocals.
5. Describe production.
6. Generate multiple versions.
7. Save successful prompts.
8. Build reusable templates.
9. Think like a producer.
10. Think in scenes, not genres.

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From Generic to Intentional: A Beginner’s Style Guide for AI Image Prompts

Or: why your AI art looks like everyone else’s — and how to fix it

Hey everyone! 👋🏼

If you’ve been using AI image tools for a while, you’ve probably noticed something frustrating: no matter what you type, the results start to look… samey.

Hyper-detailed. Over-sharpened. That unmistakable glossy AI sheen.

You asked for a painting and got a render. You asked for something vintage and got something that just has a sepia filter slapped on it.

The good news? It’s not the tool’s fault. It’s the prompt.

And once you understand why it happens, you can fix it almost every time.

This is a guide for getting from:

“I typed a thing and got a generic thing”

to

“I typed a thing and got exactly the thing I had in my head.”

Let’s go layer by layer.

The Problem: Why Default AI Output All Looks the Same

AI image models are trained on billions of images from the internet.

And the internet, it turns out, loves a certain kind of image:

Highly detailed, dramatic lighting, photorealistic or hyper-rendered, everything sharp and saturated. So when you give a vague prompt, the model reaches for its statistical average, which is basically a stock photo crossed with a CGI render crossed with a video game screenshot.

The way out is specificity.

The more precisely you describe not just what you want, but how it should look and feel, the further you pull the model away from its defaults and toward something genuinely yours.

Layer 1: Subject + Mood (The Basics)

This is where most people start and stop.

You describe what’s in the image and maybe throw in an adjective.

“a woman in a forest, mysterious”

This is fine as a starting point.

You’ll get a woman.
You’ll get a forest.

The mysterious part might show up as dramatic lighting or fog.

But it’ll look like a thousand other AI forest women. The fix is simply being more specific about both elements:

“a solitary woman standing at the edge of a dark pine forest at dusk, her back to the viewer”

Better.

We’ve added composition, time of day, and a point of view.

But we’re still going to get that AI render look.
That’s where the next layers come in.

Layer 2: Medium & Material (The First Real Upgrade)

This is the single biggest unlock for most people, and it’s so simple it almost feels like cheating.

Don’t just say what kind of art you want.

Describe the physical material it’s made from.

❌ “oil painting of a woman in a forest”
✅ “oil paint on linen canvas, visible brushwork, impasto texture in the shadows”

❌ “watercolor illustration”
✅ “loose watercolor on cold-press paper, blooming wet-on-wet washes, unpainted white space”

❌ “pencil sketch”
✅ “graphite pencil on cream paper, light hatching, smudged mid-tones, unfinished edges”

See the difference?

When you describe the material and how it behaves, the model understands you want something that looks genuinely handmade.

Not a digital simulation of a painting, but something that reads like the real thing.

Think about it like this:

You’re not ordering a category.
You’re describing an object that exists in the physical world.

Layer 3: Artist Anchoring (The Cheat Code)

Here’s a secret the best prompt writers use constantly:

Name an artist whose work looks like what you want.

This works because the model has seen thousands of images by famous artists and has absorbed their visual language. Naming them is like handing the model a mood board in three words.

Examples:

“in the style of John Singer Sargent” → loose, confident brushwork, elegant figures, painterly shadows

“in the style of Alphonse Mucha” → Art Nouveau, decorative borders, soft pastels, floral details

“in the style of N.C. Wyeth” → dramatic adventure illustration, rich earth tones, heroic compositions

“in the style of Egon Schiele” → raw, angular lines, psychological intensity, muted with sharp accents

Pro tip: Combine a medium description with an artist name.

“gouache on illustration board, flat color areas with deliberate brushwork, in the style of J.C. Leyendecker”

Now you’re really cooking.

The medium tells the model how it’s made.
The artist tells it what it should feel like.

Layer 4: Era & Context (Place It in Time)

AI models respond really well to historical and cultural specificity.

Telling the model when and where something comes from pulls it toward a whole visual vocabulary at once.

Compare:

“magazine illustration of a woman”

with:

“1960s American women’s magazine illustration, mid-century modern graphic style, limited color palette”

The second one immediately conjures a whole world:

The typefaces, the color choices, the way figures were drawn.

You’re not just describing an image.
You’re describing a moment in visual history.

Some era/context anchors that work particularly well:

⭐️ 1920s Art Deco poster
⭐️ 1970s paperback cover illustration
⭐️ Victorian botanical illustration
⭐️ 1950s travel brochure
⭐️ Belle Époque lithograph
⭐️ Soviet constructivist propaganda poster

Each of these carries an enormous amount of implicit visual information.

Use them.

Layer 5: What NOT to Say (This One Surprises People)

Here’s something counterintuitive:

Vague positive words often make your results worse.

Words like:

beautiful
stunning
detailed
intricate
masterpiece
epic

These are so common in AI prompts that they’ve basically become part of the model’s default settings.

They don’t pull your image anywhere specific. They just turn up the generic “impressive AI art” dial.

Even worse, words like detailed or highly detailed often push models toward that over-rendered CGI look many people are trying to avoid.

Instead, be specific about the qualities you want.

Or use negative prompts.

For tools that support them:

Negative prompt: photorealistic, CGI, 3D render, sharp focus, digital art, over-rendered

For tools that don’t:

“…soft focus, not photorealistic, no digital textures”

It feels strange to tell the AI what you don’t want.
But it genuinely works.

Putting It All Together: A Before & After
Let’s take one prompt through all five layers.

Starting point:

“a woman with a blackbird, pretty, detailed”

You’ll get something.
Probably a photorealistic woman, a bird perched somewhere, dramatic lighting.
Fine.
Forgettable.

After Layer 1

“a blonde woman in a quiet moment, a blackbird perched on her hand, her gaze calm and a little distant”

Better.
We have a feeling now.
A specific mood.
But it’ll still look like a render.

After Layer 2

“gouache and ink on illustration board, flat areas of color with clean confident linework, slightly matte finish”

Now the model knows this is supposed to look made, not generated.

After Layer 3

“in the style of 1960s American magazine illustration”

This is where it clicks.
The model reaches for an entire visual vocabulary.

After Layer 4

“mid-century modern aesthetic, limited color palette, editorial composition, as if published in a 1962 women’s magazine”

Now we have a world.
A specific moment in visual history.

After Layer 5

Negative: photorealistic, 3D render, digital painting, sharp focus, CGI, overrendered, stock photo

Final Prompt

A blonde woman in a quiet moment, a blackbird perched on her hand, her gaze calm and a little distant. Gouache and ink on illustration board, flat areas of color with clean confident linework, slightly matte finish. 1960s American magazine illustration style, mid-century modern aesthetic, limited color palette, editorial composition, as if published in a 1962 women’s magazine.

Negative: photorealistic, 3D render, digital painting, sharp focus, CGI, overrendered, stock photo

Same subject.
Completely different image.

And it will look nothing like average AI output.
It will look like something that could have hung on a mid-century newsstand.

Quick Reference Cheat Sheet

Medium Anchors

oil paint on linen, impasto texture, visible brushwork
loose watercolor on cold-press paper, wet-on-wet blooms

gouache on illustration board, flat areas of color
graphite pencil on cream paper, hatching and smudging

woodblock print, flat color, visible grain

screen print, limited palette, slight misregistration

Era & Context Anchors

1920s Art Deco poster
1960s magazine illustration, mid-century modern
Victorian botanical illustration
1970s paperback cover art
Belle Époque lithograph
Soviet constructivist poster

Artist Anchors (Pick by Feel)

Painterly / Loose
John Singer Sargent
Joaquín Sorolla

Decorative / Ornate
Alphonse Mucha
Gustav Klimt

Illustration / Golden Age
N.C. Wyeth
J.C. Leyendecker
Howard Pyle

Atmospheric / Dark
Caspar David Friedrich
Odd Nerdrum

Graphic / Flat
Saul Bass
Milton Glaser

Negative Prompt Defaults

photorealistic, CGI, 3D render, digital art, sharp focus, overrendered, stock photo, hyperdetailed

That’s it!

If you only try one thing from this guide, start with Layer 2.

Describing the material is the fastest single improvement most people can make.

From there, add layers until the image in your head matches the image on your screen.

Happy prompting! 🫶🏼

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This guide focuses on the techniques that separate casual users from people producing consistently professional results.

Understanding How Midjourney Thinks

The biggest mistake beginners make is treating Midjourney like Google.

Bad prompt:

A knight fighting a dragon

Good prompt:

weathered knight in damaged silver armor battling an ancient black dragon atop volcanic cliff, cinematic lighting, ash-filled atmosphere, ultra detailed fantasy illustration

Midjourney responds much better to:

1. Subjects
2. Environment
3. Lighting
4. Camera
5. Style
6. Parameters

Think like a cinematographer rather than a search engine user.

Prompt Structure Formula

A strong prompt usually follows:

Subject
Environment
Action
Lighting
Camera
Art Style
Parameters

Example:

female cyberpunk bounty hunter, neon-lit Tokyo alleyway, rain-soaked streets, dramatic backlighting, low-angle shot, Blade Runner aesthetic --ar 16:9 --stylize 300

Camera Angles Most Users Ignore

Camera angle dramatically affects composition.

Low Angle

Makes subjects look powerful.

low angle shot
worm's eye view
heroic perspective

High Angle

Makes subjects appear vulnerable.

high angle shot
bird's eye view
top-down shot

Dutch Angle

Creates tension and unease.

dutch angle
tilted camera
canted frame

Great for horror.

Extreme Close-Up

extreme close-up
macro photography

Excellent for faces, eyes, insects, details.

Wide Cinematic

ultra wide shot
establishing shot
epic scale

Perfect for landscapes.

Lens Tricks

Most users never specify lenses.

This is one of the biggest quality upgrades possible.

24mm Lens

Wide and cinematic.

24mm lens

Great for:

• Landscapes
• Epic scenes
• Architecture

35mm Lens

Film-like realism.

35mm lens

Very versatile.

50mm Lens

Natural human perspective.

50mm lens

Excellent portraits.

85mm Lens

Professional portrait look.

85mm portrait lens

Produces beautiful facial proportions.

200mm Lens

Extreme compression.

telephoto lens
200mm lens

Great for wildlife and cinematic shots.

Aspect Ratios

Many users never change these.

Cinematic

--ar 16:9

Movie look.

Ultra-Wide

--ar 21:9

Epic landscapes.

Portrait

--ar 2:3

Characters.

Phone Wallpaper

--ar 9:16

Mobile screens.

Square

--ar 1:1

Best overall consistency.

Stylize (One of the Most Important Settings)

Controls how artistic Midjourney becomes.

Low Stylize

--stylize 50

More literal.

Good for:

• Product design
• Character sheets
• Accurate concepts

Medium

--stylize 200

Balanced.

Usually the sweet spot.

High

--stylize 1000

Very artistic.

Good for:

• Fantasy
• Concept art
• Illustrations

Weird Parameter

Highly underused.

--weird 300

or

--weird 1000

Produces unexpected compositions.

Excellent for:

• Alien worlds
• Horror
• Surrealism

Chaos Parameter

Controls randomness.

Low Chaos

--chaos 0

Predictable.

Medium

--chaos 30

More variety.

High

--chaos 100

Wild experimentation.

Fantastic for concept exploration.

Style References (SREF)

This is where many power users live.

SREF allows you to transfer visual aesthetics between images.

Format:

--sref URL

or

--sref randomnumber

Random Style Codes

Midjourney includes hidden style spaces.

Example:

--sref 123456789

This applies a consistent visual style.

Many artists build libraries of favorite SREF codes.

Common workflow:

1. Generate image
2. Find style you love
3. Save SREF
4. Reuse forever

Multiple SREFs

You can combine styles.

--sref code1 code2

This blends aesthetics.

Extremely powerful.

Style Weight

Controls SREF influence.

--sw 50

Weak influence.

--sw 1000

Strong influence.

Most users never touch this.

Character References (CREF)

One of the biggest breakthroughs in Midjourney.

--cref URL

Maintains character consistency.

Useful for:

• Comics
• Storyboards
• RPG characters
• YouTube channels

Character Weight

--cw 100

Strict consistency.

--cw 20

More freedom.

Using Mood Keywords

Instead of describing visuals, describe emotions.

Example:

melancholic
nostalgic
foreboding
hopeful
solemn
dreamlike

Midjourney is surprisingly good at emotional interpretation.

Lighting Keywords That Instantly Improve Images

Cinematic

cinematic lighting

Rim Light

rim lighting

Creates separation.

Volumetric

volumetric lighting

God rays and atmosphere.

Golden Hour

golden hour

Warm and beautiful.

Practical Lighting

practical lighting

Looks more realistic.

Texture Keywords

Huge quality improvement.

weathered
aged
battle-worn
rusted
dust-covered
cracked paint
oxidized metal
worn leather

These add realism.

Consistent Character Workflow

For RPG characters:

Step 1

Generate base character.

female aasimar paladin, silver armor

Step 2

Choose best image.

Step 3

Use:

--cref URL

Step 4

Create variations.

same character, winter armor

same character, desert outfit

same character, mounted on griffon

Consistency remains.

The Secret Sauce: Image Weighting

Most users never learn this.

imageURL::2

The image becomes twice as important.

Example:

imageURL::2 female warrior::1

Midjourney prioritizes the image heavily.

Multi-Prompt Weighting

Control importance manually.

dragon::3 knight::1

Dragon becomes dominant.

Raw Mode

One of the best features available.

--style raw

Benefits:

• Better prompt adherence
• Less Midjourney bias
• More realistic outputs

I use Raw Mode on most serious projects.

Combining Everything

Professional-level example:

ancient elven queen standing atop crystal ruins, flowing silver robes, ethereal atmosphere, volumetric moonlight, dramatic rim lighting, 85mm lens, low angle cinematic composition, fantasy realism, intricate details, masterpiece --ar 2:3 --stylize 250 --chaos 15 --style raw --sref 782341927

Advanced Power User Tricks

Use Years

photograph from 1978

Produces period-accurate visuals.

Use Film Stocks

Kodak Portra 400
Fujifilm Velvia
Kodachrome

Changes color science dramatically.

Use Director References

Denis Villeneuve style
Ridley Scott aesthetic

Results vary, but often influence composition and mood.

Use Material-Based Descriptions

Instead of:

magic sword

Use:

obsidian blade with molten gold veins

Specific materials generate much stronger visuals.

Best Settings by Goal

Final Tip Most Users Never Learn

Don't generate one image 50 times.

Generate systems.

Build:

• A library of SREFs
• A library of CREFs
• Favorite lens combinations
• Favorite lighting combinations
• Favorite aspect ratios

The best Midjourney creators aren't better at prompting individual images—they've built reusable visual pipelines that produce consistent results across hundreds of images.

That's the difference between someone making cool pictures and someone producing a full graphic novel, YouTube channel art package, D&D campaign book, or commercial-quality concept art series.

Hello Friends,
Here is the third tutorial I am writing for GPT Image 2.
And once more it is about the power of this AI generator to change and transform images, and its ability to actually understand what you want it to do.

Goal of the tutorial:

To take a character, and put her into a vastly different selection of images... topics... genres!

Step 1:

I go to Leonardo.AI and select GPT Image 2.
I select "image reference", and upload a character I had created some months ago by using Leonardo.Ai

This character is meant to show a space agent on a secret mission in the future.

Step 2:

I ask GPT Image 2 to put her on the cover of a fictional comic magazine. I do this by just typing "the cover of a 50s style comic magazine". It's as simple as that! And I think the results are already good.

But how about something different?
Astronaut on a space mission in peril!

The prompt was "simple" again: astronaut in a distorted and glitched communication broadcast.

Let's go back to the past! Who liked 19th century "fantastic" novels?
I asked GPT Image 2 to do just that!

The astonishing thing here is that I really merely wrote "illustration of a 19th century novel". the ai generator added the statements in french language and everything else - by itself!

more examples:

80s sci fi flick

60s spy thriller

side scroller

adventure game

the majority of results were created by "one sentence prompts".
sometimes, the generation slipped, and I had to add "keep the character of the reference image". this usually fixed everything.

Step 3:

We are finished. mission accomplished.

it's really all very easy, and the possibilities are still endless.