Table of Contents
Bittensor is often grouped with other AI-focused crypto projects, but that framing increasingly understates what the network is. While TAO is still largely valued like a conventional crypto asset, moving with liquidity, sentiment, and short-term market flows, the underlying system it secures is evolving into something structurally different.
That disconnect was the focus of a recent post by @RvCrypto, which argues that TAO should "ultimately be valued based on the quality of its subnets and the real economic value they create."
$TAO should ultimately be valued based on the quality of its subnets and the real economic value they create.
— RVCrypto (@RvCrypto) December 22, 2025
At the moment, $TAO is largely valued like a typical crypto asset, driven by liquidity, sentiment, and short-term flows. But Bittensor is not a typical network. It’s an… pic.twitter.com/7x3YKlkc9N
In this framing, Bittensor is not simply a protocol offering AI services, but an economic system where subnets operate as independent, incentivized businesses competing to deliver measurable utility.
Subnets are no longer theoretical experiments. As RVCrypto points out, many are already shipping products, landing partners, and in some cases generating real revenue. Others are close behind, with clear and incentivized routes to market.

⚡ We're partnering with @zeussubnet to bring the best weather forecasting models to Chutes, starting with Microsoft Aurora.
— Chutes (@chutes_ai) December 1, 2025
Aurora is operational on Chutes’ infrastructure: it fetches the latest ERA5 data, runs Aurora’s inference, interpolates predictions to hourly resolution,… pic.twitter.com/9KWbyWnetO
As this progresses, value creation moves from abstract expectations toward observable economic activity. Over time, that activity is expected to show up in cash flows, buybacks, and direct demand for TAO within liquidity pools.
Therein lies the inflection point highlighted in the post.
As long as subnet activity remains disconnected from sustained TAO demand, the asset is likely to continue trading like an AI narrative token. Once subnet-generated revenue begins to consistently translate into buying pressure through buybacks and capital allocation decisions, the valuation framework shifts. At that point, TAO starts to be priced as the base asset of a growing intelligence economy rather than a speculative proxy.
RVCrypto also emphasizes that this model differs from most crypto narratives because the economics are visible. Incentives, emissions, revenue, and capital flows all occur on-chain, where they can be tracked and verified. By 2026, the post argues, these dynamics will become increasingly difficult to ignore as subnet performance shows up directly in TAO demand.
"By 2026, I expect this to become impossible to ignore because the economics will be visible were they matter most: on-chain."
The feedback loop at the center of the argument is as follows:
- Subnets create value.
- That value flows back into TAO.
- As more value is routed into the base asset, demand increases while supply tightens.
- Over time, that imbalance forces repricing driven by fundamentals rather than speculation.
In this context, comparisons to traditional AI tokens fall short. Rather than selling access or abstract vision, Bittensor coordinates competition. Intelligence is produced, ranked, and paid for in a market environment. Subnets are the source of that value, and TAO is the beneficiary and settlement layer.
If Bittensor’s intelligence economy continues to grow as its subnet ecosystem matures, the conclusion drawn in RVCrypto’s post is that the market will eventually have to price TAO accordingly.
Disclaimer: This article is for informational purposes only and does not constitute financial, investment, or trading advice. The information provided should not be interpreted as an endorsement of any digital asset, security, or investment strategy. Readers should conduct their own research and consult with a licensed financial professional before making any investment decisions. The publisher and its contributors are not responsible for any losses that may arise from reliance on the information presented.
