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I saw it again yesterday.

An "AI automation expert" posted an n8n workflow. Claimed it could "create AI UGC ads in minutes" 47 nodes. Complex routing. Beautiful screenshot.

One small problem: Half the nodes had red warning triangles.

The workflow literally didn't work.

But 3,000 people liked it. 400 shared it. And probably dozens tried to implement it before realizing they'd been sold a $1,750 cup of coffee when they could've gotten the same thing for $1.75.

Here's what everyone's getting wrong about AI agents—and the exact system to spot the fakes.

The Explosion (And the Problem)

Every company is suddenly selling "AI agents" now.

Your inbox is full of them. LinkedIn is drowning in demos. Everyone's got a solution that will "10x your team" or "replace your entire customer service department."

The problem? Most of them are fake.

Not fake as in "they don't exist." Fake as in:

And here's the uncomfortable part: Most people can't tell the difference.

Because the fakes have gotten really good at looking real.

Why This Matters Now

I build AI automations. Not "I watched a YouTube tutorial" build. I mean I actually code them, deploy them, debug them at 2 AM when they break.

And I can tell you: The gap between people who know what they're talking about and people who are just repackaging ChatGPT is getting harder to spot.

That $320K position at Anthropic? That n8n workflow with broken nodes getting 3,000 likes? The "AI automation expert" who's actually just a marketer with Canva skills?

It's all connected.

The AI agent market is becoming what the cryptocurrency market was in 2017: Full of promises, light on delivery, and expensive as hell if you pick wrong.

The Coffee Metaphor That Explains Everything

Imagine two coffee shops.

Shop A: Regular coffee. $1.75. Does exactly what you expect.

Shop B: "AI Agent Coffee." Same cup. Same coffee. But they call it "military-grade" and "powered by advanced brewing algorithms." $1,750.

The second shop isn't lying, exactly. They did use AI to... I don't know, optimize bean selection or something. But you're paying 1000x more for essentially the same product.

That's the AI agent market right now.

Except instead of coffee, it's your automation budget. And instead of $1,750, it's $50K-$500K in implementation costs.

The 10-Question Test (Save This)

I built a framework. Ten questions that separate real AI agents from expensive ChatGPT wrappers.

Ask these before you sign anything:

1. "What happens when it fails?"

Fake answer: "It doesn't fail, it's AI!"

Real answer: "Here's our error handling, retry logic, and human handoff triggers."

Real systems plan for failure. Fake ones pretend it won't happen.

2. "Why did you choose this LLM over others?"

Fake answer: "It's the most advanced" or makes up capabilities.

Real answer: "GPT-4 for reasoning, Claude for long-form writing, Llama for cost optimization—here's why each fits."

(Pro tip: Use Perplexity to fact-check their claims. If they say "GPT-5-nano" exists, they're lying.)

3. "Show me it handling an edge case"

Fake answer: Shows the happy path demo again.

Real answer: Shows the actual workflow running, exceptions being caught, fallbacks kicking in, recovery happening.

4. "Show me the actual cost breakdown"

Fake answer: "Simple monthly fee covers everything."

Real answer: "API calls cost X, storage costs Y, compute costs Z—here's the math on what you're actually paying for."

5. "What's the context window?"

Fake answer: "Unlimited memory!"

Real answer: "128k tokens with vector storage for overflow" or "We use GPT-4 Turbo's 128k window with fallback to Claude's 200k for specific use cases."

If they can't give you numbers, they don't know what they're selling.

6. "How does it handle conflicting instructions?"

Fake answer: "It just figures it out."

Real answer: "Priority hierarchy: user override > context rules > defaults. Here's the decision tree."

7. "What's the actual workflow vs. what's just a ChatGPT wrapper?"

Fake answer: Gets defensive.

Real answer: Shows you the orchestration, tool calls, state management, and actual node configurations.

This is where you separate builders from marketers.

8. "Can you show me the audit log?"

Fake answer: "It's AI, it just works."

Real answer: Shows timestamped decision points, what data was accessed, what actions were taken, why.

9. "Can it work with MY internal tools?"

Fake answer: "It integrates with everything!"

Real answer: "Here's our API documentation, here's our webhook system, here's how we'd specifically integrate with your Salesforce instance."

10. "What can it do that ChatGPT Teams can't?"

Fake answer: Long pause... "Well, it's customized..."

Real answer: Specific capabilities—conditional routing, multi-step workflows, database operations, whatever—that actually require more than a chatbot.

The Red Flags Nobody Talks About

Beyond the questions, watch for these warning signs:

❌ "Military-grade AI" (meaningless marketing speak)

❌ Won't share any architecture details

❌ Everything is "proprietary" (translation: it's a wrapper)

❌ Demo only works with their sample data

❌ "It learns from your data" but can't explain how

❌ No SLA, just vibes and "powered by AI"

❌ Can't explain why they chose their LLM

❌ Pricing based on made-up metrics like "AI units"

❌ The founder's LinkedIn is 90% motivational quotes, 10% product

If you see three or more of these, run.

What's Actually Worth Paying For

Real AI agents have these characteristics:

✓ Trained on YOUR company data (not just generic web scraping)

✓ Custom decision trees you can see and modify

✓ Actual autonomous behavior, not just Q&A

✓ Works offline or on-premise (if you need it)

✓ Clear error handling with human escalation paths

✓ Transparent audit trails for every decision

✓ LLMs chosen specifically for your use cases

✓ Can show you the actual workflow running, not just slides

If they can't demonstrate most of these, you're buying coffee at 1000x markup.

The Uncomfortable Truth About AI Influencers

Here's what most people don't realize:

The majority of "AI automation experts" on LinkedIn have never deployed a production workflow.

They've:

But they've never dealt with:

I know because I've built dozens of these systems. I've debugged them at 2 AM. I've watched them fail in creative ways. I've learned what actually works vs. what just looks good in a screenshot.

And I can tell you: The gap between "looks impressive on LinkedIn" and "actually works in production" is enormous.

What You Can Do Right Now

Next time someone pitches you an AI agent:

You don't need to be technical to use this framework. You just need to be willing to ask.

The real builders will appreciate the questions. The fakers will get defensive.

That tells you everything you need to know.

The Bottom Line

The AI agent gold rush is here.

And like every gold rush, there are two types of people:

The difference is getting harder to spot because the marketing has gotten better.

But the questions above? They cut through the noise instantly.

Real AI workflows are built with thought, testing, and actual engineering.

Fake ones are just rebranded ChatGPT with a 1000x markup.

Learn to tell the difference now, before you're the one holding the $1,750 cup of regular coffee.

P.S. If you've seen an n8n workflow with red warning triangles getting thousands of likes, you know exactly what I'm talking about. The fake ones are winning the attention game. Don't let them win your budget too.

Real workflows work. Fake ones just look good in screenshots.

Choose accordingly.

P.S.S. Join my free Skool community Agent J where I teach you AI and automations for free. We’re at 750+ members, and the community will become paid once it hits 1,000. So act now to get ahead of the payway