AI Can Now Create VFX Fro YouR Game & Characters

Overview

The video explains a workflow for using recent AI models—GPT and Claude—along with related tools/agents to create VFX for game characters and gameplay events. The creator argues this approach is now faster and easier to iterate, using AI-generated concepts before implementing anything in-engine.

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What kinds of VFX the creator is building (gameplay + character)

VFX are described as one of the most visually noticeable layers in a game.

Examples of gameplay VFX

• Home/base defense aura: provides extra defense when units are near the castle.
• Level up city/units animation: helps the action feel less “flat.”
• Castle capture VFX: includes impact/“boom” effects.
• Attack impact VFX: clearly shows what changes when an attack has proper hit/impact visuals.
• Status effects: mentions stun, healing, and wounded/wound-related effects.

Test playground

The creator builds a test playground to preview how much VFX improvements affect overall game feel.

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Core method: concept → iterate → implement

1. Start with concepts (2D/image references)

• Uses GPT/Claude “recent models” to generate image/2D concept art for VFX.
• The goal is to confirm direction, timing, and visual look before implementation.
• Emphasizes that asking AI for “just an attack animation” is unreliable for precise fit; concepting helps maintain consistency.

2. Use an “agent” to generate interactive concepts/visualizations

• AI produces multiple concept variations so the creator can choose between options.

3. Implement only after concept approval

• After selecting concepts, another agent is tasked with implementation.
• The creator notes concepting saves “enormous time” by avoiding rework.

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VFX reference libraries and reference searching

• Recommends VFX libraries for examples and terminology (e.g., impact waves, barriers, dust).
• Specifically mentions “Cartoon Effects by Jean Moreno” as a reference source.
  • Uses it to describe desired outcomes to an agent (e.g., “different color,” “more extruded”).
• References also help with timing, such as comparing stun/home-defense/roar sequence ideas.

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When concepting can be skipped

• For straightforward effects, the creator sometimes skips concepting (e.g., arrow sticking + blood, simple wounds on wolves) because the description is easy and implementation is predictable.
• Maintains a personal VFX library (e.g., hit splashes, wounded arrows, healing) to reuse effects over time.

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Character-focused pipeline: creating a unique character with multi-layer VFX (Dread)

The creator demonstrates a full character + VFX approach for a character with plant/leaf abilities.

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Character concept + planning

• Built an original character concept and animated portraits.
• Abilities/identity include:
  • Roots / plant casting on enemies
  • Shield of leaves (“mother tree” defensive effect near forest/trees)
  • Multiple custom animations and VFX interactions (e.g., leaves moving as she walks, casting sequences, stun/guard mechanics)

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Asset preparation matters (optimization + separations)

• Emphasizes optimized meshes and clean UVs/textures so AI processing works better.
• AI assistance is used for:
  • Rigging roots (credited to Astra; described as “flawless” due to proper mesh separation and optimization)
• Mentions using Tripo to generate treated models:
  • Updated capability: generate four meshes at once
  • Chooses among polycount variants to select the best output
• Mentions smart UV unwrapping, enabling later workflow such as:
  • dropping color maps for AI color correction
  • adjusting metallic/roughness

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Multi-layer VFX design (3D objects + armature + additional VFX)

Leaves/branches are handled as separate objects/materials so they can be:

• animated (e.g., wind-like movement),
• color-changed later,
• rendered with transparency,
• used for special effects (e.g., folding leaves).

Key approach described:

• Use separate leaf planes with leaf textures (prepared manually for distribution).
• Keep leaves as separate material/object rather than joining into the main body.
• Use branches/rigging so roots emerge under the ground.
• Tools mentioned:
  • Nano Banana Pro for leaf textures on planes
  • Moondiff for additional texture work when AI texturing “can fail on important details”
• Leaf placement is manual/distributed rather than fully AI-driven due to limitations in placing leaves correctly.

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Rigging and animation workflow

• For humanoid parts, suggested rigging via Mixamo or AccuRig:
  • Uses skeleton + weight transfer automatically for the upper body
  • Mentions GPT-6 later/for help with lower body rigging
• Adds additional bones for VFX animation (e.g., roots/leaf motion).
• Animation process:
  • Generates or reuses motion references/animations
  • Uses GPT to improve root movement versus some video AI tools (noted as unable to replicate root movement as requested)
  • Uses iterations and feedback loops to finalize animations
  • Mentions building a small plugin/tool to set pose and edit timeline frames precisely

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Casting VFX concepting for Dread

Before final implementation, the creator again generates VFX concepts using image references showing:

• rising/moving roots,
• drifting/falling leaves,
• the spell channeling link and release timing,
• separate elements for roots linking vs releasing,
• a “leaf guard” effect sequence.

These visuals are iterated until timing/behavior is corrected (e.g., “too fast/too slow”).

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Results and claims

In-engine results shown

• Leaves move as she walks, leaving visible trails.
• Leaves hide in forest.
• The “mother tree” defense effect triggers near trees.
• Stun animation triggers on attack.
• The ability behavior continues until canceled (“infinite until someone cancel it”).

Time and next steps

• The workflow (character + VFX) reportedly took about one and a half days.
• Plans to publish/add skills into a workspace/tool (“Mr. Mark workspace” referenced).
• Also mentions posting updates to Git and sharing a video on their channel.

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Main speakers / sources

Main speaker

• The video creator (speaks in first person throughout and demonstrates their pipeline).

Named AI tools and companies

• GPT, Claude
• Additional tools mentioned: Astra, Tripo, Moondiff, Nano Banana Pro, Mixamo, AccuRig
• Mentions video AI tools/alternatives (e.g., “C dance / mini max”).

Reference source named

• Cartoon Effects by Jean Moreno