24 months. Countless cringe-worthy tech meetings. 7 confused clients who walked away to competitors—all because someone used "AI" as a buzzword blanket.
I’ve trained 100+ professionals on AI fundamentals—from various domains. No doomsday "AI will steal your job" nonsense. Just the uncomfortable truth: misused jargon loses trust, deals, and momentum.
Here’s what works (and what doesn’t):
1. Assume Everyone’s Faking It (Including You)
Next time a project manager declares, “Let’s RAG-ify our LLM pipeline!”, pause. Ask:
“Can you walk me through the data flow?”
Most can’t. They’re regurgitating terms they heard in a webinar.
“Buzzwords are the duct tape of insecure strategies.”
2. Deep Learning ≠ Machine Learning
- Machine Learning (ML): Algorithms that find patterns (e.g., spam filters, recommendation engines).
- Deep Learning (DL): A subset of ML using neural networks with multiple layers (e.g., ChatGPT, image recognition).
Rule of thumb: If it requires a GPU cluster and a PhD to debug, it’s probably DL.
3. “Prompt Engineering” Is Just Structured Guesswork
Treat it like searching Google:
- 10% technique (clear prompts, few-shot examples).
- 90% iterative swearing (tweaking, retrying, and muttering “why won’t you just work?”).
“AI doesn’t ‘understand’—it’s autocomplete with a god complex.”
The Full AI Jargon Decoder
Free cheat sheets for your next meeting:
- Buzzword-to-English dictionary
- Scripts to politely call out BS
- Flowcharts to explain AI concepts to non-tech stakeholders
→ Get the Guide Here
No theoretical fluff. Just actionable scripts to sound competent by your next standup.
P.S. I tear apart tech jargon with empathy (and memes) in Corecraft. No gatekeeping—just clarity, GIFs, and the occasional existential crisis about GPT-5.
