1. Forget AGI Monoliths—We’re Living in a Multi-Model World

There is no single, omnipotent AGI; instead, we have a multi-model equilibrium. Powerful systems from competing labs have converged on similar capabilities rather than one pulling ahead. The future will be shaped by humans negotiating with many AIs, not by a paper-clip-maximizing singleton.

2. AI Moves Costs to the Margins

Current systems only handle the middle of the pipeline. They accelerate generation but push all remaining costs to prompt-writing on the front end and verification on the back end. End-to-end automation remains an illusion.

3. Amplified Intelligence, Not Artificial Intelligence

Today’s models lack agency. They can’t set complex goals or reliably self-audit output. The smarter the human curator, the more the AI amplifies that intelligence—hence “amplified intelligence” is the more honest label.

4. AI Won’t Take Your Job—It Lets You Do Any Job… Badly

With AI you can fake your way through UX design, VFX, copywriting, or coding—but only to a “barely acceptable” level. Final polish still requires seasoned professionals.

5. AI Replaces Older AIs, Not Humans

Midjourney cannibalized Stable Diffusion; GPT-4 obsoleted GPT-3. Budgets migrate to the newest model, not to human replacements. The cycle is perpetual model-on-model substitution.

6. Vision Beats Text

AI excels at front-end and visual tasks—UI mock-ups, storyboards, thumbnails—because humans can eyeball quality in milliseconds. Verifying 10,000 lines of generated code or prose remains a labor-intensive slog.

7. The Real Killer AI Is Already Here—It’s Called a Drone

Nation-states are racing to perfect autonomous lethal drones. Compared to that, image generators and chatbots are toys.

8. Probability Meets Determinism: Crypto as AI’s Counterweight

AI is probabilistic; cryptography is deterministic. An LLM can crack CAPTCHAs but cannot forge on-chain balances. Crypto is the formal boundary of what AI cannot do.

9. AI Is a Decentralizing Force in Practice

Open-weight models, cheap GPUs, and small teams with the right tooling level the playing field. Empirically, AI is pushing power outward, not into new monopolies.

10. The AI “Laffer Curve”: 100 % AI Is Garbage, 0 % AI Is Obsolete

Zero percent AI is too slow; 100 percent AI is too sloppy. The optimal mix lies somewhere in between—**a sliding ratio that must be tuned like tax rates**. Neither extreme is viable.

Conclusion: This Is Constrained AI

Economically, every API call has a price tag and cheaper competitors are one commit away.

Mathematically, it cannot solve chaos, turbulence, or cryptography.

Practically, it still needs human prompts and verification.

Physically, it can’t sense the world on its own.

These limits may fall one day—perhaps via a fusion of probabilistic and deterministic computing—but for now they define the sandbox we all work in.