What's in this article?
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.
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:
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.
Let's talk numbers, because this isn't just about "quality" in some abstract sense. Poor AI implementation has real business consequences:
| Impact Area | Cost/Effect | Source |
|---|---|---|
| Revenue Loss | Global losses from AI inaccuracies reached $67.4 billion in 2024 | AllAboutAI, 2025⁶ |
| Traffic Decline | Websites with AI slop saw up to 95% traffic decrease | WebFX, 2024⁷ |
| Productivity Loss | 40% of workers receive "workslop" costing $186/month per employee | BetterUp Labs, 2025² |
| Decision Quality | 47% of enterprise AI users made major decisions based on potentially inaccurate AI content | Deloitte, 2025⁸ |
| Brand Corrections | 27% of communications teams issued corrections after publishing AI content with false claims | PR Week, 2024⁹ |
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.
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.
When I first started using AI tools, my process looked like this:
The results? Generic, forgettable, and definitely not representing Sentry's expertise or voice- AI Slop.
Now, I use Claude Projects with specific, purpose-built configurations. Here's the difference and how it happens:
Instead of one generic AI tool, I have multiple Claude Projects, each configured for specific tasks:
Each project is like having a specialized team member who knows exactly what they're supposed to do.
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:
Real example: When I ask Claude to write a blog post about AI for business, it already knows:
The output isn't generic anymore—it's specifically tailored to Sentry, our audience, and our goals.
Here's where Claude Projects become even more powerful. I've connected integrations/connectors like:
Real-world example: When creating a campaign about managed IT services, Claude can:
This isn't just faster—it's smarter. The AI has actual context from our business operations.
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)
Ready to build your own system? Here's exactly how to do it:
Don't create one generic AI project. Think about the different types of content your business needs:
Each of these likely requires a different approach, tone, and format. Build separate projects for each.
For each project, collect the documents that provide context:
Essential files for most businesses:
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.
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.
Think about what tools your AI needs access to:
Not every project needs every integration—only connect what's actually useful.
Your first setup won't be perfect. That's fine. Use it, pay attention to what works and what doesn't, and refine:
Treat your AI projects like you would train a new employee—with patience, clear feedback, and continuous improvement.
Here's what the difference actually looks like in practice:
| Characteristic | AI Slop 🗑️ | AI Superhero 🦸 |
|---|---|---|
| Setup | Open generic AI, type random prompt | Purpose-built projects with custom instructions |
| Context | None—every request starts from zero | Rich knowledge base of brand docs, guidelines, examples |
| Voice | Generic, robotic, could be anyone | Distinctly yours, matches your brand personality |
| Accuracy | Frequent errors, outdated info, hallucinations | Grounded in your actual business data and verified sources |
| Integration | Standalone tool disconnected from workflow | Connected to CRM, documents, and business tools |
| Output Quality | Surface-level, generic, needs heavy editing | Substantive, specific, requires light refinement |
| Consistency | Wildly variable depending on prompt | Reliable quality aligned with standards |
| Strategy Alignment | Random content with no connection to goals | Directly supports business objectives and campaigns |
| Time Investment | Quick to start, expensive to fix later | Initial setup required, massive time savings ongoing |
| Business Impact | Damages SEO, wastes time, harms brand | Accelerates growth, maintains quality, scales expertise |
| Human Role | Copy-paste operator | Strategic director and quality controller |
| Results | Traffic drops, corrections, productivity loss | Enhanced output, protected brand, measurable ROI |
The difference isn't subtle. It's transformative.
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:
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).
If you're ready to transform your AI usage from slop to superhero, start here:
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.
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