From AI Slop to AI Superpower

What's in this article?

• The $9 Million Problem Nobody's Talking About
• What is AI Slop?
• The Real Cost of Bad AI Content
• How I Use Claude Projects at Sentry
• Building Your AI Superhero System
• AI Slop vs AI Superhero: The Comparison
• Stop treating AI like a vending machine and get strategic
  
  
  

The $9 Million Problem Nobody's Talking About

Here's something that should make every business leader sit up straight: 40% of desk workers in the U.S. have received what researchers are now calling "workslop"—AI-generated content that looks polished but lacks any real substance.¹ And it's not just annoying. This content creates nearly two hours of extra work for people who encounter it, costing companies approximately $186 per employee per month, which adds up to a staggering $9 million productivity hit annually for mid-sized organizations.²

Meanwhile, the AI-powered content creation market is exploding—projected to grow from $2.15 billion in 2024 to $10.59 billion by 2033.³ That's a lot of money being invested in technology that, if used incorrectly, is creating more problems than it solves.

The disconnect is real. Businesses are rushing to adopt AI tools, but many are discovering their AI-generated content is getting crushed by search engine updates, ignored by customers, or worse—damaging their brand reputation. In fact, 60% of marketers who use generative AI content worry it could harm their brand reputation due to bias, plagiarism, or values misalignment.⁴

But here's the thing: AI isn't the problem. How we're using AI is the problem.

As Sentry's Marketing Director, I've spent the past 12+ months transforming how we use AI—specifically Claude (my new best friend and model of choice)—from a "quick content generator" into what you could call an AI superhero system (for the creative sake of this article). The difference? Context, customization, and intentional design. Let me show you exactly how I did it, so you can stop getting AI slop and start creating content that actually moves your business forward.

What is AI Slop? (And Why Your Team is Probably Creating It)

Before we go further, let's be honest about what AI slop actually looks like. You've probably seen it—maybe even created it yourself:

• Generic content that could apply to literally any company in your industry
• Repetitive phrasing with the same structure in every paragraph
• Surface-level insights that don't demonstrate real expertise
• Overly formal tone that sounds like it was written by a robot (because it was)
• Factual inaccuracies or outdated information presented as current
• Keyword stuffing that prioritizes SEO over readability
• Missing your brand voice entirely

One website filled with AI-generated content saw a 95% decrease in traffic after Google's March 2024 core update specifically targeted low-quality, spammy content.⁵ That's not a typo—ninety-five percent.

The problem isn't that these businesses used AI. The problem is they used AI like a vending machine: put in a generic prompt, get out generic content, publish without thinking. No context. No customization. No human oversight.

That's AI slop. And if you're just copying and pasting ChatGPT outputs directly into your marketing materials, you're creating it too.

The Real Cost of Bad AI Content

Let's talk numbers, because this isn't just about "quality" in some abstract sense. Poor AI implementation has real business consequences:

These aren't acceptable trade-offs. These are preventable failures.

The companies avoiding these pitfalls aren't the ones who said "no" to AI. They're the ones who learned to use it correctly—with systems, structure, and strategic implementation.

How I Use Claude Projects at Sentry (Real Examples from My Actual Work)

Let me pull back the curtain and show you exactly how I transformed our AI usage at Sentry Technology Solutions- and how I try my best not to create more AI slop that's everywhere. This isn't theory—these are the actual systems I use every day.

The Old Way (AI Slop Territory)

When I first started using AI tools, my process looked like this:

1. Open AI tool (Claude or Copilot or ChatGPT at the beginning)
2. Type: "Write a blog post about cybersecurity for small businesses"
3. Copy output
4. Maybe edit it a little
5. Publish

The results? Generic, forgettable, and definitely not representing Sentry's expertise or voice- AI Slop.

The New Way (AI Superhero System)

Now, I use Claude Projects with specific, purpose-built configurations. Here's the difference and how it happens:

Step 1: Create Dedicated Projects for Specific Purposes

Instead of one generic AI tool, I have multiple Claude Projects, each configured for specific tasks:

• Blog Writing Project: Loaded with our brand voice, blog guidelines, SEO best practices, and topic cluster strategy (among other things)
• Client Communication Project: Includes our StoryBrand framework, customer pain points, and communication guidelines (among other things)
• Social Media Project: Has our tone examples, platform-specific best practices, and content themes (you got it... lots more here)
• Technical Documentation Project: Contains our technical accuracy standards and documentation style guide (again... can't give EVERYTHING away, right!?!?)

Each project is like having a specialized team member who knows exactly what they're supposed to do.

Step 2: Add Knowledge Files That Give Context

This is where the magic happens. Instead of starting from zero every time, I've uploaded documents that give Claude the context it needs to be genuinely helpful:

For our Blog Writing Project, I've added:

• Sentry Company Brief(our company overview, messaging, and positioning)
• Sentry StoryBrand Overview (our complete marketing framework and product positioning)
• Brand Voice (specific examples of how we communicate about who we are and what we do)
• Guidelines for Blogs (our editorial standards for blog posts)
• SEO/AEO Best Practices document (describes best practices for content to be seen!)
• Topic Clusters document (linking strategy for pillar content- every post is connected to a specific content pillar)
• Transcripts (from meetings and conversations with our CEO and staff that are about specific topics)

Real example: When I ask Claude to write a blog post about AI for business, it already knows:

• Our brand voice (authoritative yet approachable, solution-focused, empathetic)
• Our target audience (business leaders facing technology challenges)
• Our messaging framework (customer has a problem → Sentry is the guide → here's the plan)
• Our SEO/AEO strategy (link back to pillar pages, use specific keywords, optimize for intent)

The output isn't generic anymore—it's specifically tailored to Sentry, our audience, and our goals.

Step 3: Integrate Your Business Tools

Here's where Claude Projects become even more powerful. I've connected integrations/connectors like:

• HubSpot: So Claude can reference our actual customer data, understand our sales process, and align content with our CRM insights
• Sharepoint: To access internal strategy documents, campaign briefs, and performance reports
• Canva: To streamline visual content creation that matches our written content

Real-world example: When creating a campaign about managed IT services, Claude can:

1. Reference actual customer data from HubSpot
2. Pull performance data from previous campaigns
3. Suggest coordinating visual assets in Canva
4. Write content that aligns with our managed IT services pillar page

This isn't just faster—it's smarter. The AI has actual context from our business operations.

Step 4: Customize the Style and Instructions

In each Claude Project, I've added custom instructions that define exactly how I want the output formatted:

Example custom instruction for blog posts:

You are a professional expert copywriter for Sentry Technology Solutions. 
Write in Sentry's brand voice: authoritative yet approachable, 
solution-focused, empathetic, and partnership-oriented. Target business 
leaders facing technology challenges. Use the StoryBrand framework: 
identify the customer's problem, position Sentry as the guide, and present 
a clear plan. Include conversational elements and practical examples. 
Always link back to relevant pillar pages. Format with H2 headers every 
few paragraphs, use short paragraphs, and include a table of data when 
appropriate.

This means every output starts from the right foundation, not a blank slate. (the real prompt is much larger, but you get the idea)

Building Your AI Superhero System: A Step-by-Step Guide

Ready to build your own system? Here's exactly how to do it:

Phase 1: Identify Your Content Needs

Don't create one generic AI project. Think about the different types of content your business needs:

• Blog posts and articles
• Customer emails and proposals
• Social media content
• Technical documentation
• Internal communications
• Marketing campaigns

Each of these likely requires a different approach, tone, and format. Build separate projects for each.

Phase 2: Gather Your Knowledge Assets

For each project, collect the documents that provide context:

Essential files for most businesses:

• Brand voice and style guide
• Company overview and positioning
• Target audience descriptions
• Messaging frameworks
• Content templates and examples
• Industry-specific terminology
• Compliance or legal requirements
• Past successful content (to learn from)

Pro tip: Start with 3-5 core documents rather than dumping everything. You can always add more later. Quality of context matters more than quantity.

Phase 3: Write Clear Custom Instructions

This is where you define how the AI should behave. Be specific:

Good instruction: "You are writing for mid-level executives in manufacturing companies who are frustrated with IT downtime but don't have technical backgrounds. Use conversational language, avoid jargon, focus on business outcomes rather than technical specifications, and always include practical next steps."

Bad instruction: "Write good content for our website."

The more specific you are about tone, audience, format, and goals, the better your results will be.

Phase 4: Connect Relevant Integrations

Think about what tools your AI needs access to:

• CRM systems (HubSpot, Salesforce): For customer insights and campaign data
• Document storage (Google Drive, Sharepoint, Dropbox): For accessing strategy documents and templates
• Project management (Asana, Monday, Planner): For understanding priorities and workflows
• Analytics platforms: For performance data to inform content strategy

Not every project needs every integration—only connect what's actually useful.

Phase 5: Test, Refine, and Iterate

Your first setup won't be perfect. That's fine. Use it, pay attention to what works and what doesn't, and refine:

• Are outputs matching your brand voice? If not, add better voice examples.
• Is the AI missing important context? Add relevant documents.
• Are you getting repetitive suggestions? Adjust your instructions to encourage variety.
• Is the format wrong? Be more specific about structure in your custom instructions.

Treat your AI projects like you would train a new employee—with patience, clear feedback, and continuous improvement.

AI Slop vs AI Superhero: The Comparison

Here's what the difference actually looks like in practice:

The difference isn't subtle. It's transformative.

The Bottom Line: Stop Treating AI Like a Vending Machine

Here's what I've learned after a year of using Claude Projects at Sentry: AI is not a replacement for human expertise—it's an amplifier. But what it amplifies depends entirely on how you set it up.

If you feed it nothing (AI slop approach), it amplifies that generic mediocrity.

If you feed it your expertise, brand voice, business context, and strategic goals (AI superhero approach), it amplifies your best work and helps you scale it.

The key principles that separate superhero AI from slop AI:

1. Context is everything: Generic prompts get generic results. Rich context gets valuable output.
2. Purpose-built beats general-purpose: Different tasks need different setups. Don't use one tool for everything.
3. Human oversight is non-negotiable: AI should draft and accelerate, not publish unsupervised.
4. Continuous refinement is required: Your AI system should evolve as your business evolves.
5. Integration multiplies value: Connected AI that references your actual business data is exponentially more useful than standalone tools.

At Sentry, we've seen the difference firsthand. Our content is better, our team is more productive, and we're able to maintain quality while scaling our output. Not because we found some magic AI tool—Claude is available to everyone—but because we invested in setting it up correctly.

The AI content revolution is happening whether we're ready or not. The question isn't whether to use AI—it's whether you'll use it like everyone else (creating slop) or strategically (creating superhero-level results).

Your Next Step

If you're ready to transform your AI usage from slop to superhero, start here:

1. Audit your current AI usage: How are you using AI today? Are you just copy-pasting prompts into ChatGPT?
2. Identify one high-value use case: Don't try to fix everything at once. Pick one critical content need—maybe blog posts or customer emails.
3. Build your first proper project: Gather 3-5 key documents, write clear instructions, and set up a dedicated AI project for that specific purpose.
4. Test and refine: Use it for two weeks. Pay attention to what works and what doesn't. Adjust accordingly.
5. Scale what works: Once you've got one project dialed in, replicate the approach for other content needs.

The technology is powerful. But technology without strategy is just expensive noise. Build your AI superhero system with intention, and you'll never go back to slop.

Want to learn more about how we leverage advanced technology like AI to help businesses grow securely and efficiently? At Sentry Technology Solutions, we're not just using AI for ourselves—we're helping companies navigate the complex tech landscape and implement solutions that actually move their business forward.

Because the goal isn't just better AI content. The goal is better business outcomes.

About the Author: Jason Lee is the Sales & Marketing Director at Sentry Technology Solutions, where he helps businesses cut through technology complexity with clear strategy and expert guidance. These AI practices are pulled directly from his daily work implementing content systems that actually drive results.

References

¹ BetterUp Labs and Stanford Social Media Lab, "AI-Generated Workslop Study," 2025

² BetterUp Labs Research, "$9 Million Productivity Impact Study," 2025

³ Grand View Research, "AI-Powered Content Creation Market Report," 2024

⁴ HubSpot, "2025 AI Trends for Marketers Report," 2024

⁵ WebFX, "Bonsai Mary Case Study: Impact of Google Core Update on AI Content," 2024

⁶ AllAboutAI, "Global AI Accuracy and Hallucination Cost Report," 2025

⁷ WebFX, "Is AI Content Bad For SEO? Real-World Examples," 2025

⁸ Deloitte, "Global AI Enterprise Survey," 2025

⁹ PR Week, "Industry Survey on AI-Generated Communications," 2024