TAO (TAO)

$TAO keeps fighting to defend the key $190 support, really important level More trading setups at: https://t.co/N3WuQcWWkm https://t.co/G3SYNOLtkz

If my conviction is that Bittensor can become a major decentralized AI infrastructure and grow its market cap by 10x or even 20x over the coming years, then buying at $150 instead of $194 may end up being far less important than simply building a position. No one knows whether $TAO will rebound tomorrow, revisit $150, or fall even lower. That's exactly why DCA makes sense. It removes the psychological burden of trying to perfectly time the bottom. The bigger risk may not be paying a few extra dollars per TAO, it may be missing a meaningful part of the long-term upside. Of course, this thesis ultimately depends on one thing: Bittensor and its subnets must deliver real adoption and real revenue. If they do, I believe very few people are prepared for what could follow.

$TAO feels like a huge pressure cooker. Protocol upgrades. Emission changes. Higher-quality subnets shipping real products and groundbreaking R&D. The open-source AI narrative going mainstream. There’s literally too much bullish news to keep track of. Everything is lining up for #Bittensor.

I genuinely believe there's a point in the not-too-distant future where: 1. $TAO has its first true breakout subnet. 2. The ecosystem changes are behind us and Bittensor moves toward full decentralization. 3. The market turns bullish again. When that day comes, I think the entire ecosystem will be viewed very differently.

This is the most bullish the bittensor:native ecosystem has been since May

bittensor:native Bittensor needs to find the balance between building and moving fast assertively. I’m looking forward to hearing the positive sides of “move slower”. We will have this opportunity at @ExploitSummit

Bittensor >> SN 24 Quasar https://t.co/FQ2Y59YZIg @QuasarModels At first, many of us saw it as a subnet focused on long-context AI models. Today, the vision is becoming much broader. They're now opening a private beta for hardware teams, aiming to bring mechanical engineering, electronics, and firmware into a single AI-powered workspace with a shared understanding of the entire product. This isn't just about building a better model anymore. It's about building a tool that solves real engineering problems. Research is important. But turning research into a product that people actually use is where real value is created. Congratulations to the Quasar team on another impressive step forward.