1. They slap “AI” on basic automation
If it’s:
- If-else rules
- Excel macros
- Simple scripts
- Static dashboards
…they call it AI.
Reality: That’s automation wearing a Halloween costume 🤡
2. They hide behind the buzzword salad
Listen for:
- “Proprietary LLM stack”
- “Deep neural reasoning engine”
- “Agentic workflows”
- “Self-healing architecture”
- “Enterprise-grade AI”
- “Patent-pending ML”
If they can’t explain it to a teenager,
it doesn’t exist.
3. “Our model is better than GPT”
(But they never show numbers)
Real AI companies publish:
- Benchmarks
- Accuracy
- Error rates
- False positives
- Model drift stats
Fake AI companies:
- Show demos
- Give anecdotes
- Cherry-pick use cases
- Avoid metrics like tax audits
Rule:
If it’s not measured, it’s marketing.
4. It’s just an API wrapper in disguise
If their moat is:
OpenAI API + UI + Pitch deck
you’re not buying a company.
You’re buying:
- Prompt engineering
- Branding
- Burn rate
Value = 0 when the API pricing changes.
5. The demo is glued together with prayers
Classic demo tricks:
- Scripted input
- Cached output
- Internet-on laptop, offline-by accident
- Founder controlling backend silently
- “Live demo… oops WiFi glitch”
Fake AI dies when the keyboard slips.
6. They confuse “training” with “fine-tuning”
Claim:
“We’ve trained our own model.”
Reality:
They fine-tuned 500 examples on HuggingFace.
Big difference:
- Training = Infrastructure + data + years
- Fine-tuning = Weekend + GPU + hope
Calling this “our model” is like:
Buying a T-shirt and claiming you own a textile mill.
7. They fake enterprise readiness
If deployment involves:
- One Slack channel
- One engineer
- Zero SLA
- No audits
- No compliance
…it’s not enterprise-grade.
It’s beta cosplay.
8. No AI product manager = no AI product
Ask:
“Who owns data strategy?”
If they say:
- “CTO”
- “Dev team”
- “Everyone”
Translation:
“No one is accountable.”
Deep AI requires:
- Data pipelines
- Labeling strategy
- Monitoring
- Retraining plans
- Drift detection
No structure = no depth.
9. They promise autonomy… but sell chatbots
Claim:
“Autonomous AI agents”
Reality:
Prompt + API + CRON job
That’s not intelligence.
That’s software doing chores.
10. They mistake complexity for competence
You’ll see:
- Huge diagrams
- Fancy dashboards
- Jargon-heavy docs
- Minimal error handling
Look underneath:
- Poor data hygiene
- No testing
- No governance
- No safety layers
Fancy ≠ Functional.
The Nuclear Test (use this one question):
“What breaks when your AI is wrong?”
Real startups answer with:
- Error modes
- Risk scenarios
- Safeguards
Fake ones say:
- “We’re very accurate”
- “Rare edge cases”
- “Still improving”
If they can’t describe failure,
they don’t understand their product.
Brutal Summary Table
| Claim | Reality |
| Proprietary AI | API wrapper |
| Self-learning | Static model |
| Enterprise-grade | Startup duct tape |
| Agentic | Task list |
| Scalable | Server panic |
| Trustworthy | Untested |
Final Truth:
Fake AI companies sell confidence.
Real AI companies sell control.
If you want, I can also give you:
✅ An investor checklist for AI startups
✅ A technical depth interview guide
✅ Questions to expose fake innovation
✅ How to spot API wrappers instantly
✅ A litmus test for model builders
✅ What real AI architecture looks like
Tell me which one you want — and I’ll sharpen the knife 😄