Could AI Agent Skills Make Some Bittensor Subnets Obsolete?

As AI agents become more capable, Bittensor’s alpha investors face a growing question. If an agent can deliver a subnet’s core service through a freely available skill, what makes that subnet worth paying for? The answer could help distinguish projects with lasting advantages from those built around accessible workflows.

Agent skills are reusable instructions for specific tasks, sometimes supported by scripts, reference material, and external tools. The language model interprets a request, while software handles defined steps such as retrieving information or interacting with an application. This can make execution more consistent, although errors and varying results remain possible.

An email skill, for example, could apply a user’s preferred tone and structure before placing a draft in their email client. Similar skills can support research, content preparation, and browser automation. As these workflows become easier to share and adapt, subnets offering comparable services face greater pressure to demonstrate better quality, convenience, or cost.

However, automating a task does not necessarily replace the infrastructure behind it. A skill can guide an agent to request inference or rent computing power, but it does not supply the models or hardware. Subnets providing reliable compute, valuable data, verification, or other difficult-to-reproduce capabilities may become useful suppliers to agents.

For alpha investors, the real test is what remains valuable once a workflow becomes easy to copy. Evaluating a subnet means examining its underlying resources, execution quality, pricing, and customer demand. Agent skills could weaken some business models while expanding access to others, making this distinction an important part of assessing long-term relevance.