Featured Agents hallucinate, judges struggle on hard problems, and we're surrounded by adversarial content. How dFusion is building verified intelligence — across data validation, corroboration, and the agent harness.
A guide to buying and setting up a subnet on dFusion, including how to get a subnet slot, configure your domain, or claim a pre-built subnet to start participating and accumulating points.
How dFusion turns usage into structured signal - from queries and data contributions to subnets that improve through repeated activity and incentivized participation.
What makes one subnet more valuable than another - the factors that determine signal quality, data relevance, activity, evaluation, and consistency over time.
How using AI has shifted from passive interaction to active participation in infrastructure - running queries, uploading files, rating outputs, and contributing to subnets.
How dFusion improves through usage: the input, validation, refinement, repeat loop that compounds value over time.
Insights on what drives repeat usage of AI tools and why domain-specific, ongoing context matters more than one-off capability.
Why usefulness in AI is defined by reliability, context, and integration into real workflows rather than novelty or raw capability.
Builders weigh in on what AI agents still struggle with today, from judgment and verification to reliability and contextual understanding.
Why long-term AI durability depends on the foundational layers being overlooked in today’s growth narrative.
As AI becomes infrastructure, the ecosystem stratifies into consumers who access intelligence and operators who help power it.
The hidden costs of scraped AI data and why durable intelligence requires incentive alignment, participation, and renewal.
AI is increasingly described as a technological revolution, but the deeper shift is the emergence of an intelligence economy and the question of who owns it.
Scraped data fueled the first wave of AI, but as systems mature its lack of consent, context, and incentives makes it a structural dead end.
Subnet Slots let operators run focused, domain-specific pieces of AI intelligence infrastructure, providing the trusted inputs increasingly autonomous AI systems will rely on.