Ashwin Aravind

The first time I saw a creator use ChatGPT to write their entire video script, I knew they were making a mistake. The script was fine—grammatically correct, well-structured, hitting all the right beats. It was also completely soulless.

Three videos later, their engagement dropped 40%. Comments said "this doesn't sound like you anymore."

AI is incredible leverage for creators, but most people use it wrong. After building AI tools for creators and watching hundreds of use cases, I've learned this: AI should amplify your voice, not replace it.

Here are 5 automations that actually work, with specific examples of how to implement them without losing what makes your content yours.

1. Idea Generation and Validation

The hardest part of creating isn't making the content—it's knowing what to make. AI can compress weeks of brainstorming into hours.

What Works

Use AI to generate 50 ideas, then YOU pick the 5 that resonate.

Prompt I use:

I'm a [your niche] creator. My last 5 successful videos were:
1. [title, topic, key angle]
2. [title, topic, key angle]
3. [title, topic, key angle]
4. [title, topic, key angle]
5. [title, topic, key angle]

Generate 50 new video ideas that follow similar patterns but with fresh angles. 
Include: hook angle, core insight, and why it would resonate with my audience.

The key is feeding it YOUR successful content, not generic prompts. The AI learns your style by example.

What Doesn't Work

Asking "give me 10 video ideas about [topic]" produces generic garbage that 10,000 other creators will also post this week.

Real Example

A tech creator I work with used this to go from posting 2x/week to 5x/week. Engagement didn't drop because the ideas still came from patterns that worked for her audience—AI just accelerated the ideation process.

She spends 30 minutes Monday morning generating 50 ideas, then 15 minutes picking the 5 that excite her. Those 45 minutes replaced 5+ hours of staring at a blank doc.

2. Script Outlining (Not Script Writing)

This is the most misunderstood use case. AI is great at structure, terrible at voice.

What Works

Use AI to create the skeleton, then write the meat yourself.

My process:

Tell AI the goal: "I want to explain [concept] to [audience] in under 60 seconds."
Get the structure: AI generates 5-7 bullet points for what to cover.
Write it in your voice: You turn each bullet into 1-2 sentences using YOUR words, YOUR examples, YOUR personality.

Example:

AI suggests: "Start with a relatable problem your audience faces"

You write: "I wasted 6 hours last week doing this the dumb way, so let me save you the pain"

The structure is AI-generated, the voice is 100% you.

What Doesn't Work

Taking AI-written scripts verbatim. Even if you edit them, they sound like "edited AI" not "your voice."

Code Example: Script Outliner Tool

from openai import OpenAI

def generate_outline(topic, audience, duration, your_style_examples):
    client = OpenAI()
    
    prompt = f"""
    Create a {duration}-second video outline about {topic} for {audience}.
    
    Base the structure on these examples of my style:
    {your_style_examples}
    
    Return ONLY bullet points for structure, not full sentences.
    Each bullet should be a topic/beat to cover.
    """
    
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.7
    )
    
    return response.choices[0].message.content

# Use it
outline = generate_outline(
    topic="using Python to automate video editing",
    audience="non-technical creators",
    duration=60,
    your_style_examples="""
    - I always start with a personal pain point
    - I use concrete examples, not abstract explanations
    - I end with one actionable step
    """
)

print(outline)
# Now YOU write the actual script following this outline

The AI handles structure, you handle personality. That's the split that works.

3. Thumbnail Text and Hook Testing

At Meta, we A/B tested everything. Most creators can't A/B test at scale, but AI can help simulate it.

What Works

Generate 10-15 variations of thumbnail text and opening hooks, then pick the best 3 to actually test.

Prompt pattern:

My video is about: [topic]
My audience cares about: [pain point/desire]
My style is: [conversational/technical/entertaining/etc]

Generate 15 different opening hooks that:
- Grab attention in first 2 seconds
- Promise a specific outcome
- Match my tone

Also generate 15 thumbnail text options (max 5 words each).

You get variety without losing your voice because you're setting the constraints.

Real Example

I built a tool that does this automatically. A creator pastes their video idea, gets 15 hooks and 15 thumbnail options, then:

Picks top 3 of each
Posts to their Close Friends story
Asks which hook would make them stop scrolling

The AI generates options, humans validate what works. That's the key.

What Doesn't Work

Using the first AI-generated hook without testing or validation. AI doesn't know your audience—it's guessing based on patterns.

4. Content Repurposing Across Platforms

I see creators record a 10-minute YouTube video, then stress about making a TikTok version. This is perfect for AI.

What Works

Use AI to identify the 3-5 "best moments" from long-form content, then YOU decide which to actually cut.

Workflow:

Upload transcript of your video to AI
Ask: "Identify the 5 most engaging 15-30 second segments that would work as standalone clips. Include timestamp, topic, and why it's engaging."
Review AI suggestions
Pick the 2-3 that best represent your content
Cut and post those

The AI does the heavy lifting (reading the 10-minute transcript), you do the creative judgment (which clips actually work).

Code Example: Clip Finder

def find_viral_clips(transcript, video_length, target_clip_length=30):
    client = OpenAI()
    
    prompt = f"""
    Analyze this {video_length}-second video transcript.
    Find 5 segments that would work as {target_clip_length}-second standalone clips.
    
    Criteria for good clips:
    - Self-contained idea (makes sense without context)
    - Strong hook or surprising insight
    - Clear beginning and end
    
    Transcript:
    {transcript}
    
    Return: timestamp, duration, topic, why it works
    """
    
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.5
    )
    
    return response.choices[0].message.content

# Now YOU review these suggestions and pick winners

One 10-minute video can become 5-10 short-form clips. AI finds them, you curate them.

What Doesn't Work

Letting AI automatically cut and post clips. Context matters—sometimes AI suggests clips that work on paper but don't land in your feed.

5. Comment Response Drafting

Responding to comments builds community, but it's time-consuming. AI can draft responses; you add personality.

What Works

Use AI to generate draft responses to common comment types, then customize before posting.

Categories to automate:

Questions: AI drafts factual answer, you add your spin
Feedback: AI drafts thank you, you personalize it
Criticism: AI drafts professional response, you decide if it's worth engaging

Example tool:

def draft_comment_response(comment_text, comment_type, your_tone):
    client = OpenAI()
    
    prompt = f"""
    Draft a response to this {comment_type} comment.
    Comment: "{comment_text}"
    
    Tone: {your_tone}
    Length: 1-2 sentences max
    
    Make it helpful but authentic. No corporate speak.
    """
    
    response = client.chat.completions.create(
        model="gpt-4",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.7
    )
    
    return response.choices[0].message.content

# Example
comment = "This didn't work for me, what am I doing wrong?"
draft = draft_comment_response(
    comment, 
    "question", 
    "helpful and conversational, not overly formal"
)

print(draft)
# You review, edit, and post

The AI saves you from blank-page syndrome. You save your personality by editing before posting.

What Doesn't Work

Auto-posting AI responses without review. People can tell, and it feels fake.

The Framework: AI for Speed, You for Soul

Here's the pattern across all 5 automations:

AI generates options → You curate and customize → Publish

Never skip the middle step. AI is a 0-to-1 tool (blank page to first draft), not a 1-to-10 tool (first draft to final product).

When to Use AI

Brainstorming (generate 50 ideas in 5 minutes)
Structuring (outline before you write)
Variation testing (create 15 options to test 3)
Pattern recognition (find clips in long content)
Repetitive tasks (draft responses to common comments)

When NOT to Use AI

Writing your actual voice (scripts, posts, captions)
Making creative decisions (which idea to pursue)
Engaging emotionally (replying to meaningful comments)
Building relationships (DM conversations)
Anything that defines your brand

What This Looks Like in Practice

A creator I work with uses AI for all 5 automations. Here's her workflow:

Monday Morning (45 min):

Generate 50 content ideas with AI
Pick 5 that excite her
Get AI outlines for each

Daily (2 hours):

Write scripts based on AI outlines (in her voice)
Record content
Use AI to suggest thumbnail text, pick favorites

End of Day (20 min):

AI drafts comment responses
She customizes and posts

Weekly (1 hour):

AI identifies best clips from long-form content
She picks 3-5 to cut and post

Result: She went from 3 videos/week to 5, plus daily stories and reposts. Engagement is UP 20% because she's spending more time on the parts that matter (her voice, her creative choices) and less time on the parts that don't (structuring, brainstorming, grunt work).

AI gave her leverage, not replacement.

The Tools I Actually Use

You don't need fancy custom tools. Here's my stack:

Ideation: ChatGPT with good prompts
Outlining: Claude (better at structure than GPT)
Thumbnail/Hook testing: Custom tool (but you can do it with ChatGPT)
Repurposing: ChatGPT for transcript analysis
Comment drafting: ChatGPT API in a simple script

Total cost: ~$20/month for API usage.

The tools don't matter much. The workflow matters. AI handles volume, you handle voice.

What to Try This Week

Pick ONE automation to test:

If you struggle with ideas: Use AI to generate 50, pick your top 5
If scripts take forever: Try AI outlining, then write in your voice
If you're inconsistent: Use AI to batch content ideas so you're never starting from zero
If you only do long-form: Use AI to find clips, then cut the best ones
If comments overwhelm you: Draft responses with AI, customize before posting

Start with one. See if it feels like leverage (faster without losing quality) or replacement (faster but soulless).

The goal isn't to automate creativity. It's to automate the stuff that gets in the way of creativity.

That's how AI works for creators who grow. Not as a replacement, but as a force multiplier for the parts that already work.

AI for Creators: 5 Automations That Give You Leverage Without Killing Your Voice

1. Idea Generation and Validation

What Works

What Doesn't Work

Real Example

2. Script Outlining (Not Script Writing)

What Works

What Doesn't Work

Code Example: Script Outliner Tool

3. Thumbnail Text and Hook Testing

What Works

Real Example

What Doesn't Work

4. Content Repurposing Across Platforms

What Works

Code Example: Clip Finder

What Doesn't Work

5. Comment Response Drafting

What Works

What Doesn't Work

The Framework: AI for Speed, You for Soul

When to Use AI

When NOT to Use AI

What This Looks Like in Practice

The Tools I Actually Use

What to Try This Week