Your smartwatch has more computing power than NASA used to put a man on the moon.
Let that sink in.
This episode is about what happens when computing power becomes essentially free—and why that's both terrifying and liberating.
THE JEVONS PARADOX (1865):
British economist William Stanley Jevons observed something counterintuitive: When steam engines became MORE efficient, Britain's coal consumption TRIPLED (not decreased).
Why? Efficiency makes a resource cheaper → more applications become viable → total consumption increases.
The AI parallel: As AI becomes more efficient, we don't use it less. We use it MORE. Three years ago, nobody used AI. Today? Every listener probably uses it daily.
THE FOUR-LAYER AI VALUE CHAIN:
Layer 1 - Infrastructure (Chips): NO differentiation. Chips are so cheap your smartwatch > NASA moon computer.
Layer 2 - Foundation Models (LLMs): Anthropic, OpenAI, Perplexity, etc. Not differentiating on quality anymore—now it's politics & branding. Example: Anthropic set conditions for U.S. Defense Dept work; OpenAI accepted all conditions. Branding matters: "I love Claude" vs. "Have you heard someone say 'I'm chet-chi-pting'?" (Like "Googling"—but it'll never catch on.)
Layer 3 - Applications: NOT a differentiation. Why? Building is too easy now. Bernhard built RolePlays.AI in 4 months, part-time, 50,000 lines of code. He's not a coder—AI helped him build it.
Layer 4 - Context & Orchestration: ⭐ THE DIFFERENTIATION
- Proprietary data
- Domain-specific workflows
- Deep integration into user behavior
- Specialized knowledge orchestration
McKinsey and Bain agree: Context & orchestration is where human intelligence wins.
THE UNCOMFORTABLE TRUTH ABOUT AI COACHING:
How do AI coaching apps compare to human coaches?
Answer: AI compares well to AVERAGE coaches.
If a coach goes by the book, uses tools correctly, follows frameworks—AI will match them.
This is fortunate: It frees humans to focus on what REALLY matters. Not just standard work. Not "good standard coaching."
Anything "good standard," AI will do better.
That sets us free to be creative. To focus on problems AI can't solve.
MUSICIANS ARE SAFE:
Many musicians fear AI. Bernhard's answer: You're in one of the SAFEST spots—as long as you make GREAT music.
Why? Great music requires:
- Life understanding of your audience
- Understanding what lays behind the music
- Human depth AI won't reach anytime soon
THE PATTERN:
Wherever you have:
- Specific expertise
- Specialized knowledge
- The wish to learn and develop
Use AI for:
- Tasks you hate
- Administrative work
- Simple things that take time but don't add value
That's brilliant use of AI.
THE LEARNING IMPERATIVE:
We need to continue learning. Otherwise, AI will enter our domain quickly.
But this is great: We can use our brains in ways AI never will.
THIS WEEK'S CHALLENGE:
- Identify your Layer 4: What's YOUR context AI doesn't have? Your proprietary knowledge? Your domain workflows?
- Audit your AI use: Using it for tasks you hate? (Good.) Avoiding deep work, AI can't do? (Warning sign.)
- Invest in learning: What specialized knowledge keeps you ahead?
- Try RolePlays.AI: Practice difficult conversations. See how AI helps you prepare for human moments.
FOR COACHES: If you're "going by the book," AI will match you. Your differentiation: Context, orchestration, human depth. Be extraordinary, not average.
FOR MUSICIANS: Focus on GREAT music. Use AI for admin, not the creative core.
SELF-AWARE ENDING:
"Yes, this AI episode was not generated by AI; it was generated purely by me." - Bernhard
www.roleplays.ai | www.bernhardkerres.com
#AI #HumanIntelligence #Context #Coaching #JevonsParadox #FutureOfWork