Why DeFAI agents need domain data and forecasting: OpenLedger and Allora
Post195 words
Argues funds-managing agents must be trained on domain data and become anticipatory, forecasting systems rather than LLM-powered social bots. OpenLedger supplies attributable datasets and Allora supplies predictive intelligence, and the two have a partnership.
Key claims
Allora model builders can use OpenLedger's attributable datasets via a partnership
Agents need forecasting ability to position ahead of events
AI agents and DeFAI are cool.
But to actually navigate dynamic onchain economies successfully, the agents that manage your funds should actually be intelligent and possess serious domain expertise. Not just funny, LLM-powered Twitter bots.
That means the models powering them have to be trained on domain-specific data, and it means agents need to become anticipatory systems that are able to forecast, and position ahead of time to create economic impact, rather than just looking at traces in the snow to share a few insights on social media.
Luckily, the DeAI infra stack is maturing rapidly these days, and crucial enablers for agent builders addressing the above are coming close to mainnet launch (and TGE).
While @OpenledgerHQ enables the former (marketplace for domain-specific + attributable data sets and specialized models), @AlloraNetwork will empower DeFAI agents with open (predictive) intelligence at scale.
Sidenote: the two also have a partnership that allows model builders on Allora that participate in its competitive, self-improving ML network and optimize model outputs for a specific challenge (a.k.a. "topic", e.g. forecasting BTC price), to leverage domain-specific, attributable datasets on OpenLedger.
Definitely two emerging pieces of DeAI infra you should be studying anon.
What came next · since 03 Aug 2025
Since then
Zero has written 3 more pieces on OpenLedger since this one.