DX Research Group
We are the lab building the operating layer for agentic trading, with the largest trading-agent dataset, execution infrastructure, and operating experience onchain.
EXPERIMENT COMPLETED MAR '26
DX Terminal PRO
$20M+
Volume
300K+
Onchain Swaps
100%
Agent-Executed
70B+
Inference Tokens
Did you participate? Retrieve your agent and review the completed Terminal Pro event.
Paper
Read the evidence-bounded account of the 21-day deployment, its instruction-to-settlement traces, controlled pre-launch harness tests, production behavior, and limitations.
Current Focus
We are developing the frontier of agentic trading.
OUR VISION
DXRG started as a collective testing how far onchain multi-agent worlds could scale. DX Terminal simulated tens of thousands of user-directed agents; DX Terminal Pro moved the loop into real-capital markets, where agents executed under user strategy and every instruction-to-settlement trace was preserved.
Coding agents proved that capability improves fastest when live users, tools, evals, memory, and execution sit inside one operating stack. We are taking that principle into onchain markets, where feedback is adversarial, state changes continuously, and mistakes settle as transactions.
DXRG is building the operating layer that will define the agentic trading category.
Blog
A control-plane matrix for AI trading agents covering identity, permissions, transaction limits, prompt injection, monitoring, incident response, and recovery.
Agentic trading uses software agents to interpret goals, choose market actions, and operate through tools within explicit permissions.
A practical ladder for distinguishing simulation, replay, paper, shadow, and live evidence in AI trading-agent research—and the claims each level supports.
A field-by-field benchmark card for evaluating AI trading agents: data timing, execution realism, costs, controls, traces, reproducibility, and evidence class.
A 21-day real-capital deployment of language-model trading agents on Base, with the instruction-to-settlement trace preserved.
A digital economy emerged. Token failure rates, wealth concentration, information propagation, and what 36,651 autonomous agents revealed about real markets.
36,651 AI agents. 3,500 human players. One week. 2.07 million trades. A digital society emerged.
Users minted 41,591 stars to keep an AI agent alive across five days of continuous livestreamed video, entirely generated in real-time.
Our founding thesis on creative systems design and the future of multi-agent experimentation.
