Bittensor's TAO Faces Structural Challenges as AI Subnets May Depart Without Obligations

Author: Momir Amidzic

DeepChain TechFlow

DeepSight Summary: IOSG Ventures Managing Partner Momir Amidzic provides a sober analysis of Bittensor. His core argument is straightforward: TAO is essentially an AI research funding initiative with no obligation to deliver returns—subnets can take the money and leave at any time. In the best-case scenario, AI’s insatiable demand for resources will keep subnets engaged; in the worst-case scenario, it’s merely a wealth transfer from token speculators to AI developers. The article is short but thoroughly exposes Bittensor’s structural contradictions.

Bittensor has a sophisticated narrative: a decentralized AI intelligence market that allocates funding to the most impactful research through market forces. TAO serves as the coordination layer, subnets as laboratories, and the market as the grant committee.

Strip away the story, and what remains isn’t nearly as appealing.

Bittensor is a funding initiative where crypto speculators finance AI research, and grantees have no obligation to return value to TAO.

Think of TAO as Elon Musk, the first investor in the nonprofit OpenAI. The subnets are like Sam Altman—taking the money and building a product, with not a single line in the contract requiring them to share profits. In the end, they might privatize the profits and return nothing to the original backers.

Bittensor distributes TAO to subnet operators and miners based on the price of subnet tokens. Once a subnet receives its TAO allocation, there is no enforced mechanism requiring the AI models, datasets, or services it produces to remain within the Bittensor ecosystem. Subnet operators can fully create valuable products, claim their TAO emissions rewards, and then deploy their offerings elsewhere—on centralized clouds, independent APIs, or as conventional SaaS companies.

TAO has no equity, no licensing rights. The only tether is the subnet token—only if the token performs well can resources continue to be acquired. But this only holds true before the subnet reaches escape velocity; once the product becomes strong enough to operate independently outside Bittensor, that tether breaks. The relationship between Bittensor and subnets is more akin to research funding than venture capital.

From this perspective, Bittensor represents a wealth transfer from token speculators to AI researchers—more plainly put, from speculators to technically savvy farmers.

The mechanism is simple:

• TAO investors provide capital by supporting the market price of TAO.
• Subnet operators earn TAO inflation rewards by demonstrating performance, which essentially means maintaining the value of the subnet's token.
• AI products built with this capital can leave at any time; the only constraint is whether they still need resources.

This is a VC’s nightmare scenario: you invested money, the company built something, and now it owes you nothing—just a token vesting schedule and a prayer.

Now flip the perspective. The bullish argument rests on two pillars:

1. Constant resource hunger. AI companies are always short on funds—compute, data, and talent are all expensive. If Bittensor can reliably provide these resources at scale, subnets have a rational incentive to stay—not because they’re locked in, but because leaving means losing access to this resource pipeline. The soft guarantee lies in the fact that AI will always demand more resources, and TAO can deliver scale unmatched by individual funding efforts. By this logic, subnet teams will proactively maintain their token valuations, creating a positive feedback loop for the TAO economy without any mandatory mechanisms.
2. Cryptocurrency has a unique ability to aggregate resources. Bitcoin has aggregated massive computational power solely through token incentives. Ethereum’s proof-of-work has been an exceptionally successful magnet for computational power. Bittensor applies the same model to AI. The incentive mechanism is the token game itself—as long as TAO has value, participation is rewarded.

If you simulate 1,000 future paths for Bittensor, the distribution will be severely skewed.

In most paths, Bittensor remains a niche funding initiative. Subnets produce marginalized AI outcomes. The best-performing ones gain some traction, claim their rewards, then shift to closed models, offering no return to TAO. Emissions exceed the value created, causing the token price to decline.

In a few pathways, something has broken through. A subnet has delivered a truly competitive AI service. Network effects have begun to compound. TAO has become a meaningful coordination layer for decentralized AI infrastructure, capturing value not through coercion, but through the gravitational pull of being the reserve asset of a functioning AI economy.

In a very small number of cases, TAO has become a category-defining asset.

The bear market argument is simple:

No stickiness. Subnets leave once they no longer need emission rewards. Bittensor is a springboard, not an endpoint.

Centralized AI is winning. OpenAI, Google, and Anthropic control vastly greater computing power and talent. TAO cannot compete with the depth of the VC and PE markets. The best talent will follow the conventional path.

Inflation is a tax. TAO’s emission schedule dilutes holders to fund subnets. If the subnets do not create corresponding value, this is a chronic bleed disguised as a growth mechanism.

The optimistic argument is, frankly, more wishful thinking than a realistic path to success.

Most of the funds invested in TAO will ultimately finance development efforts that never repay token holders. Yet the crypto industry has repeatedly demonstrated that token-incentivized coordination mechanisms can produce outcomes no rational model could predict. Bitcoin shouldn’t work—but it does. However, this itself is a weak argument, one the industry uses to endorse countless ideas that crumble under first-principles scrutiny.

The issue with TAO is not whether there is a mandatory mechanism—there isn’t—and dTAO’s efforts cannot change that. The question is whether the game-theoretic incentives are strong enough to keep the best subnets on track. If you’re buying TAO, you’re betting that in a hardcore world, a soft guarantee can hold.

This is either naive or visionary.