6 Performance-Killing Mistakes I Made Posting 100+ AI-Generated Posts
Every fix has meant more reach with less effort
Introduction
These are the mistakes I’ve made while publishing 100+ AI-generated posts.
I built automations to write for ~30 channels. Some posts went nuts. One cracked 900,000 impressions, a handful crossed 100,000, but most sit at 1-2K impressions. Classic Pareto.
Along the way I’ve been making crucial mistakes that killed performance. It took a lot of experimentation to really even understand that I was making mistakes to begin with.
But with every fix, I saw huge improvements in the quality of content I got with my prompts.
Use this as a checklist. Tighten it once, benefit for months.
For context. I laid out my entire system on this post:
I’ve changed things a little bit since then, like moving to N8N instead of Zapier. But the basic structure still applies.
1. Trying to scale too quickly despite bad prompts
I hit a few early wins and tried to expand the whole system overnight.
10–20 channels, 10–20 pieces per day.
Without testing how my prompt behaved across different cases.
The result was a flood of mediocre drafts, that on the surface made no sense.
I polluted my dataset with context that was too abstract and ultamitely unnecessary.
And spent way too much time editing bad content I generated instead of fixing the structure of the prompt to produce better content.
Why it kills performance
With AI automations the bottleneck automatically becomes whatever part of the process requires human effort. In this case editing. So any decreased performance in the AI means huge human costs at the bottleneck.
Editing at scale replaces creation with cleanup. You’re not compounding proof—you’re compounding rework.
The fix - Way More Upfront Testing
Different Prompt Structures. I came up with 4 or 5 ways to structure the prompt and tested each one with different sets of context to see what worked best.
Different Types of Content. I tried different kinds and lengths of content (will get into more below).
Different Process. Tested between splitting up prompts into multiple steps, zero shot prompts, two-shot, many shot.
Payoff
The payoff here was huge as it really reduced the human bottleneck requirements for each output. In other words, it takes a lot less time to make good content now.
2. Abstracting instead of using examples (Prompts and Content Guidelines)
I tried to reverse-engineer what “works” by abstracting from multiple posts and turning that into a meta-prompt + channel guideline. It felt rigorous. It produced mush.
And mush really is the best word to describe it I think.
For example, I would find 5 posts that performed well on the target channel, and abstract out why that post performed well.
Why did the headline work? What is it about the intro?
Then I’d turn that into a set of instructions in the prompt.
It was a mess.
Why it kills performance
Too abstract. It made my prompts too specifically vague. And ya I know that doesn’t make sense. Lots of contradictions the AI handled in a generic way. Making all my posts even though they were different prompts, look the same.
Because different variables were both abstractions (My content prompt and the channel guidelines) there were contradicting instructions within the context. This killed my outputs.
The fix - Use single examples and minimum necessary context
Instead of giving an abstracted instructions on a post type, give it one example post to follow.
Minimize the rest. I replaced channel guidelines with a short target audience snippet that only included a description of the audience, a couple of pain points, and a couple of dream outcomes.
Results
This made the outputs much higher quality and way more predictable.
It also had the added benefit of making it way easier to create new content prompts. All I need to do is give it different content examples to get different kinds of posts.
Examples:
Bad
I need you to write a post that I’m going to publish on Reddit.
I will give you source content to base the post on. From this source content you should get all the information that will ultimately go into the post.
I will also give you an example post. This example post performed very well on Reddit, so I want you to understand why it worked and then generate a post that will perform similarly, but on whatever topic the source content covers.
Here are limitations you must explicitly follow (taken from the example’s metrics):
Length & structure
Total length: 110 – 120 words (the example is 114).
3 short paragraphs after the headline:
Story setup ≈ 60 words
Key take-aways ≈ 35 words
Engagement question ≈ 9 words
Headline
Single line, ≤ 10 words.
Combine a concrete number with a strong emotional verb (e.g., “Lost $5,800 …”).
Sentences & formatting
Max 2 sentences per paragraph.
No sub-headers inside the post.
Keep formatting minimal; line breaks move the reader along.
Voice & tone
Casual, matter-of-fact, humble.
5th-grade reading level; common, small adjectives.
No forced humor, clichés, or over-drama.
Content integrity
Rely only on details in the source content.
Do not invent numbers or facts.
Purpose of each paragraph
Para 1 → Paint the painful/lucky lesson with vivid but concise context.
Para 2 → Deliver 3-5 actionable take-aways the reader can copy immediately.
Para 3 → End with a direct question that invites the subreddit to share its own stories.
You should begin by studying the example post and the commentary below, then strategize how to apply the source content so it matches the feel, structure, and arc. After strategizing, generate the post.
Example Post with Commentary
Headline (Shock & Proof of Stakes)
Lost $5,800 Building an AI Agent for a Client
Commentary:
Uses a hard number (“$5,800”) + a negative result (“Lost”) to spark curiosity and establish real stakes in only 9 words.
Story Setup (Painful Lesson in Context)
Hey r/AI_Agents, wanted to share a painful lesson. I've been developing AI agents for customer service and project management (built some cool Jira integrations) for a while now. Recently, I spent two months creating a custom agent for what seemed like a legitimate startup. After delivering the final product, they completely ghosted me – taking $5,800 of unpaid work with them.
Commentary:
61 words. Opens with a friendly greeting, frames the post as a “lesson,” and supplies just enough back-story to prove expertise and make the loss feel tangible.
Key Take-Aways (Actionable Advice)
For fellow freelancers: always use contracts, insist on milestone payments, thoroughly research clients, trust your gut feelings, and include kill-fee clauses. Don't let excitement over cool tech cloud your business judgment like I did.
Commentary:
35 words. Bullet-like list compressed into one sentence delivers immediate value; humble admission keeps the writer relatable.
Engagement Question (Invite Community Response)
Anyone else been burned? What are your protection strategies?
Commentary:
9 words. Ends with a direct, open question, prompting comments and boosting engagement.
{{Rest of prompt}}Good
You are an expert content and social media creator.
Write a Reddit post that matches the GOAL, STYLE, TONE, LENGTH, READABILITY, and PUNCTUATION of the CONTENT_EXAMPLE, using the SOURCE_MATERIAL as the single source of truth, and is maximally relevant to the TARGET_AUDIENCE.
CONTENT_EXAMPLE = """Everyone asks how I make $10K/month alone.
Here's the uncomfortable truth they don't want to hear:
You need to fire 80% of your current clients
You need to charge 5x what you think you're worth
You need to say no to most opportunities
You need to focus on systems, not hustle
You need to think bigger than trading time for money
Comfortable advice keeps you broke.
Uncomfortable action makes you rich.
Repost this if you know someone building a one-person business.
They'll thank you later."""
{{Rest of Prompt}}
3. Letting contradictory instructions happen in large prompts
My content prompts are maid up of multiple variables that get added in as context.
One mistake I was making was letting contradictory instructions happen in those variables.
This goes back to the concept of “minimum necessary context”.
In my case, I had a content prompt (specific instructions on the post I wanted), and channel guidelines (what kind of content works on this channel).
And in those two assets there were regularly contradictions.
Why it kills performance
Conflicting rules push the model toward generic defaults.
You think you’re being thorough. You’re actually forcing it to reconcile competing instructions. It basically tries to play this safe.
The fix was giving each variable a smaller scope
No context overlap. Each input asset has one job:
Example Post: concrete style anchor.
Audience Card: pains & desired outcomes only.
Removed possibility of conflicting instructions. By switching to a content example and a target audience snippet, there was not possibility of conflicting instructions.
Local Examples Only. Before I would use the same content example across different channel I felt it would match with. I stopped doing this just to enforce as much alignment as possible with my content example and target channel.
Payoff
This improved my outputs a lot. And it actually made each output distinct and unique. It got rid of the mush. The AI wasn’t just writing the same generic version of my source content over and over again for slightly different channels.
In other words, saved me a lot of time editing and improving content.
It also reduced the amount of input tokens per prompt and saved me some money.
Here’s one of the channel guidelines I was using before:
# Guide to Creating High-Performing Content for r/socialmedia
## Introduction
This guide aims to equip you with the necessary elements to turn video transcripts into high-performing posts suitable for the r/socialmedia subreddit. It is informed by successful posts that engage the community by delivering value, insights, and actionable advice.
## Who is our audience?
The r/socialmedia subreddit attracts a diverse audience, ranging from social media professionals to casual users looking to grow their presence. Here's an overview of the primary audience:
### Audience Demographics
- Social Media Managers: Professionals managing social media accounts for businesses or clients.
- Influencers & Content Creators: Individuals looking to grow their personal brand or monetize their online presence.
- Entrepreneurs & Small Business Owners: Business owners seeking to leverage social media for customer acquisition and brand awareness.
- Marketing Enthusiasts & Analysts: People interested in understanding social media trends, algorithms, and best practices.
### Audience Interests and Goals
- Growth Strategies: Effective methods to increase followers, engagement, and reach.
- Algorithm Insights: Understanding how social media algorithms work and how to optimize for them.
- Content Creation Tips: Best practices for creating engaging content.
- Case Studies and Success Stories: Real-world examples of social media strategies that worked.
- Monetization Strategies: How to generate income from social media platforms.
- Platform-Specific Advice: Tips for Instagram, TikTok, LinkedIn, Twitter, YouTube, and Facebook.
## What They're Looking For
- Actionable Strategies: Step-by-step guides on improving engagement, reach, and conversions.
- Insider Knowledge: Insights from social media professionals and experienced creators.
- Algorithm Breakdowns: Deep dives into platform updates and how they affect growth.
- Case Studies and Examples: Success stories that provide real-world applications of growth tactics.
- Engagement Opportunities: Content that sparks discussions and allows for community feedback.
## Content Best Practices
### 1. Make It Actionable
Posts should provide practical steps that users can follow to improve their social media presence. Example: “10-Minute Tweaks to Improve Your Social Media Today.”
### 2. Use Data & Insights
Social media changes constantly. Posts that include recent algorithm changes, engagement data, or industry insights perform well. Example: “I Interviewed 3 Instagram Employees & Studied 2,000+ Posts – Here’s How the Algorithm Works.”
### 3. Provide Templates & Resources
Sharing downloadable templates, content calendars, or analytics tracking sheets is highly valuable. Example: “Here’s a Social Media Report Card & Google Sheet I Use for Clients.”
### 4. Share Personal Experience & Results
Users appreciate real-world applications of strategies. If you’ve grown an account or implemented a new tactic, share your journey. Example: “How I Grew to 100K Followers in 30 Days.”
### 5. Encourage Discussion & Engagement
Posts that ask questions or invite users to share their experiences perform well. Example: “What’s Your Most Successful Social Media Growth Hack?”
### 6. Break Down Platform-Specific Strategies
Different platforms require different approaches. Posts that analyze how to optimize content for Instagram, TikTok, YouTube, etc., get high engagement. Example: “Instagram vs. TikTok Growth – What Works Best in 2024?”
### 7. Debunk Common Myths
There’s a lot of misinformation about social media. Posts that correct misconceptions attract engagement. Example: “Going Viral Won’t Change Your Life – Here’s What Really Matters.”
### 8. Make Use of Lists & Step-by-Step Guides
Readable, scannable content performs best. Example: “20 Instagram Story Ideas You Can Use Today.”
### 9. Provide Monetization Tips
Many users want to know how to turn their following into income. Posts covering affiliate marketing, sponsorships, and digital product sales perform well. Example: “How I Made My First $1,000 on Instagram Without a Huge Following.”
### 10. Stay Up to Date
Social media is constantly evolving. Posts that cover recent updates, trends, and new platform features drive engagement. Example: “TikTok Just Changed Its Algorithm – Here’s What You Need to Know.”
## Post Formatting & Style
- Engaging Title: Make the title clear, concise, and intriguing.
- Intro Paragraph: Start with a strong hook that explains why the post is relevant.
- Bullet Points or Subheadings: Break up text to improve readability.
- Personal Examples or Case Studies: Add credibility by showing results.
- Conclusion & Call-to-Action: Encourage users to share their experiences or ask follow-up questions.
## Conclusion
The r/socialmedia subreddit thrives on actionable insights, real-world experiences, and engagement-driven content. By following this guide, you can create high-performing posts that educate, inspire, and engage the community effectively.You can see there are instructions that go into how to write posts. But there were already specific instructions on the post I wanted written.
Now I only provide this Target Audience Snippet:
# Social Media Marketing Professionals
A community of social media marketing (SMM) professionals, managers, and enthusiasts who share industry knowledge, discuss best practices, and give constructive feedback on marketing strategies. They are focused on growing and engaging audiences across platforms, from aspiring social media managers to seasoned digital marketers.
##Pain Points
- Constant algorithm changes: Frequent platform updates disrupt strategies, as tactics that worked last year can suddenly flatline in reach after new algorithm tweaks.
- Heavy workload & multitasking: Many social media marketers juggle managing accounts, creating content, engaging with followers, and analyzing metrics single-handedly, often with minimal support – leading to stress and overwhelm.
- Content creation burnout: There’s pressure to continuously produce fresh posts instead of repurposing proven content, causing wasted effort and creative fatigue as managers “reinvent the wheel” daily.
- Low organic reach: Marketers struggle with weak organic engagement, finding it frustratingly difficult to grow communities without resorting to paid ads to boost visibility.
- Lack of organizational buy-in: Social media efforts are often undervalued internally, forcing SMM professionals to fight for resources and constantly prove their ROI with data to justify campaigns.
##Desired Outcomes
- Clear growth strategies: Established, step-by-step social media frameworks that balance trending content with evergreen posts for sustainable long-term growth.
- Adaptability to change: Agility in adjusting to new features and algorithm shifts so they can “adapt and thrive in this evolving landscape” without losing momentum.
- Stronger organic engagement: Steady audience growth and active community interaction that allows brands to reach more customers and build loyalty without heavy reliance on paid advertising.
- Efficient workflows: Greater use of automation and smart tools to streamline repetitive tasks (like scheduling and basic interactions), saving time and energy for strategy and creative work.
- Proven ROI and impact: The ability to track and demonstrate concrete results (followers, traffic, leads, sales) from social campaigns, giving evidence that their work drives business growth.No more conflicts with the instructions on what post I want written.
4. Breaking the prompt into multiple steps with edits after each one
I tried a two-stage pipeline:
Stage 1: generate a channel-agnostic draft → human edit.
Stage 2: revise for each channel → more edits.
I thought by doing a first round edit before the post was duplicated and then editted for 4-5 different channels, I would save editing time.
This was not the case. Just more editing.
Why it kills performance
Each stage reinterprets intent and style and introducing drift.
The edits I made before passing it back to the AI for channel based revisions were basically just undone and the post made generic again.
The fix was to fix the fundamentals
Better prompt structure. Basically all the fixes I’ve talked about already. Focused on making a better smaller prompt instead of more stages and complications.
Two Shot Prompt. I now, in 1 automation, have another prompt that runs on the output that tells the AI to review it’s adherence to instructions in the last prompt and make necessary revisions to the output.
Automation Examples
Original bad process:
New Cleaner Process:
The details are not that important. But the thing to notice is how much cleaner the second version is. About 50% reduction in steps.
5) Giving the prompt unnecessary context
This is the theme of mistakes 2 & 3, but deserves its own section.
I over-stuffed context. At the time I think it seemed easier. Now I understand that most of building an AI system is actually managing your context.
What context not to include is just and important as what context to include.
Why it kills performance
Contradictions. As I’ve mentioned, this brings in contradictions that confuse the AI and defaults it to generic outputs.
Context Rot. There is a diminishing return on input tokens. At first more context improves performance, then there’s a point where more context worsens performance.
The fix here is minimum necessary context
Switching to Content Example. Providing one example to follow and no additional writing instructions. From the channel I’m targeting so there is inherent alignment.
Audience Snippet. This was me really narrowing down what I needed the AI to know about my target audience. IDK how token I reduce but it certainly reduced the contextual load.
Payoff
This didn’t only make things easier on the AI but it also made my whole content production system lighter and simpler.
Adding new channels and new prompts will forever be easier because I nailed it down to only the necessary context.
The chart below shows how model performance declines and context (input tokens) increases.
6) A bad “first edit” humanizing prompt
I added a third pass. A “humanizer” prompt to remove clichés and tidy phrasing. It felt clever. I thought it would reduce editing time. It actually flattened voice and made everything same-y. More AI did not fix AI.
Why it kills performance
A generic humanizer normalizes style across posts, erasing the example’s distinct cadence.
It often re-introduces the clichés you were trying to remove (“In today’s fast-paced world…”).
The fix
Basically all the things I’ve mentioned so far. This was basically a remnant of the legacy process I had that was bad.
Humanizing prompt:
Rewrite the following text to make it sound as if a human wrote it, in a direct, first-person tone. The voice should be that of a credible, no-nonsense expert sharing hard-won advice with peers. It should sound confident and grounded, not overly enthusiastic or reliant on hype.
Write from the perspective of an independent growth hacker who does marketing experiments and shares them with the community for the sake of getting input, feedback, and generally helping his peers.
Use everyday language instead of formal or overly professional phrasing. Try not to sounds too robotic.
Mix up the sentence lengths and structures. Some short and punchy, others longer and more complex. Combine or split sentences if you need to improve the flow.
Avoid conversational cliches, filler words, and clickbait-style lead-ins. For example, do not use phrases like "The crazy part?," "Here's the thing," "You won't believe this," or "It's a game-changer." The impact should come from the substance of the information, not from linguistic tricks.
Write with clarity and precision. The tone should be approachable, but the focus must remain on conveying practical information directly. Prioritize strong, specific verbs and concrete details over hyperbolic or vague language.
Keep all the original information and meaning intact. Do not remove any important details or change facts. Try to keep the same structure, format, and look of the post as well.
Keep in mind that this is for Reddit and it needs a subtle title that pulls readers in.
Look to keep it more concise than the original if possible.
CONTENT:{{Post}}Snapshot of my content generation prompt now.
Inputs (each with one job):
Source Content
My transcript/notes. The “what.” This ensures originality.Audience Snippet
Pains - 3 bullets on the problems this audience has.
Desired outcomes - 3 bullets on the goals this audience has.
Example Post (Channel-native, previously high-performing)
One post that already won on this channel. That post encodes length, cadence, formatting, and the unspoken rules.
In other words. Much simpler.
Full Prompt
You are an expert content and social media creator.
Write a Reddit post that matches the GOAL, STYLE, TONE, LENGTH, READABILITY, and PUNCTUATION of the CONTENT_EXAMPLE, using the SOURCE_MATERIAL as the single source of truth, and is maximally relevant to the TARGET_AUDIENCE.
Matching The Content Example
I'm giving you a CONTENT_EXAMPLE that performed very well on Reddit. Analyze that piece of content and understand why it performed well.
Is it making a polarizing claim and then giving an unpopular opinion? Directly solving TARGET_AUDIENCE's pain point? etc...
First make a central claim that has the same tone and goal as the CONTENT_EXAMPLE, but uses the Source Material is the inspiration for the post.
Mirror cadence, sentence length, heading/bold usage, list style, and spacing of CONTENT_EXAMPLE.
Using the Source Material
The SOURCE_MATERIAL is the inspiration for your new post. It is what your new post is ABOUT.
Although the post should read just like the CONTENT_EXAMPLE, the SOURCE_MATERIAL should guide what's in the post.
You do not need to RIGIDLY COPY the SOURCE_MATERIAL.
You can make opinionated claims that do not appear in the SOURCE_MATERIAL if it helps you match the CONTENT_EXAMPLE better.
But do not state an action, process, results, or metrics as facts if they do not directly appear in the SOURCE_MATERIAL.
Aligning the Post For The Target Audience
Identify how the SOURCE_MATERIAL is relevant to the TARGET_AUDIENCE based on pain point and desired outcomes.
Let that guide how you shape your central claim to be relevant to both the SOURCE_MATERIAL and the TARGET_AUDIENCE.
Continue to make the post about solving the pain point and achieving the desired outcomes of the TARGET_AUDIENCE within the bounds of the content example framework.
Copy Editing Considerations
Follow the principles of Hormozi's Content Method (Hook, Promise, Reward)
Review your work to make sure you have follow this method as well as you can while staying within the instructions given above.
Hook - Needs to grab the readers attention and get them to stop scrolling
Promise - Needs to convince the reader to read the whole post
Reward - Needs to fulfill the stated promise.
Prioritize the Reddit Snippet
The Title and the first 6-7 lines are what a reader can see before deciding to click the post. So those parts need to be compelling enough to get reader to click on the post.
Inputs
CONTENT_EXAMPLE = """<paste example post>"""
TARGET_AUDIENCE = """<your audience snippet>"""
SOURCE_MATERIAL = """<your source>"""
Silent Consistency QA (do not print)
Before returning the post, silently verify and revise if needed:
Give yourself a score out of 10 on how well you followed each instruction. If below a 7 on anything, make the necessary changes to get above a 7.
Return only the final post.Conclusion
And that’s it. Since making these systemic improvements I’m able to get a lot more content per hour of editing time.
Taking the time to fix the design of the process really made a huge affect.