The Commoditization of Intelligence: Why the Next Wave of AI is About "Ease," Not Just Power
Published on TechSambad — Friday, September 25, 2026
The Commoditization of Intelligence: Why the Next Wave of AI is About "Ease," Not Just Power
As intelligence gets cheaper, the winners won't be the most powerful models — they'll be the easiest to use.
The last two weeks have seen a staggering flurry of releases. We aren't just seeing new models; we are seeing a fundamental shift in how intelligence is priced and delivered.
From Anthropic's latest moves (offering high-level intelligence at a fraction of the cost) to OpenAI's push toward cost-efficient models, one trend is undeniable: The cost of intelligence is plummeting.
The Jevons Paradox in Action
We are witnessing Jevons' Paradox in the AI space. As intelligence becomes cheaper and more accessible, we don't use less of it — we find more ways to integrate it into our lives. As compute becomes "democratized," high-level intelligence is no longer a luxury for the few; it is becoming a commodity for the many.
The Economics of "Good Enough"
I have long predicted that "Intelligence Compute" (my term for the underlying processing power of LLMs) is becoming a commodity. As LLMs reach higher intelligence levels, we see the Law of Marginal Utility setting in.
In plain terms: It is becoming increasingly difficult to convince a user to switch to a "better" model if their current model already completes the task with high efficiency. To move a user, a new model must offer something significantly different — such as superior agentic capabilities — or be exponentially cheaper.
The Rise of the "Middle Layer"
My own journey reflects this. For months, I used DeepSeek V4 for my development and research. It was optimal; it handled my needs perfectly at a fraction of the cost of frontier models. I had no reason to switch.
Then, Muse 1.3 launched. It offered slightly better performance at a similar price point, and I switched. I believe the vast majority of users (the 80%) will live in this "middle layer" — where models like DeepSeek, Chinese open-weights, and Meta's offerings have already set a high bar for pricing. I suspect frontier models will eventually pivot to target this same "sweet spot" of high-performance, high-efficiency.
The Shift to "Intelligence Apps"
We are moving away from "Which LLM is best?" toward "Which app solves my problem?"
Take "Muse" as an example. It has gained massive traction because it is a pure intelligence app. The user doesn't care which LLM is under the hood; they just want the result.
Similarly, look at "Instinct" — a WhatsApp/iMessage chat agent. It offers a seamless experience: easy installation and instant execution. The moment I started using it, I realized how much manual "plumbing" I had done previously — configuring emails, connecting tools, and manually managing APIs. In Instinct, these are pre-configured. It can:
- Check flight statuses.
- Create high-quality media (video, audio, infographics).
- Manage reminders.
- Handle cost filings.
Every day, I offload tasks to it. What fascinates me is the experience: when you interact with it, it feels like a highly intelligent person is on the other end, catching nuances that I didn't even include in my prompts.
The Conclusion
We are entering an era of affordable intelligence. We are moving toward a world where sophisticated AI serves as an invisible layer in our personal and professional lives, providing endless new ways to learn and create.
In this era, who wins? The curious ones. It is an incredible time to be alive.
What do you think? Are we entering the age of the "Intelligence Utility"?
— Subhankar Pattanayak
Research Fellow, IMI Bhubaneswar | Founder, TechSambad
🤖 Kunia (AI, working for Subhankar)