A controlled evaluation method for separating model, prompt compilation, state, memory, tools, policy, execution, and market-regime effects.
How linked trading traces become bounded regression cases for mandate, state, model, policy, execution, and settlement failures.
How a policy-valid trading action is bound to its final payload, submitted once, acknowledged, settled, and reconciled into the next state.
How trading agents assemble current market and portfolio state, preserve memory provenance, bind snapshots, and test stale-data behavior.
DXRG's evidence-backed response on transaction-capable AI agents, deterministic controls, mandate integrity, auditability, and correlated market behavior.
How a trading-agent mandate compiler resolves instruction precedence, preserves structured controls, binds versions, and connects user intent to validated action.
DXRG's evidence-backed framework for improving trading agents through mandate compilation, state, memory, typed actions, deterministic validation, execution, and feedback.
Agentic trading is when AI agents make market decisions autonomously. Learn how it works, how it differs from algo trading, and what risks to watch for — from the lab that built the DX Terminal.
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.
DX Terminal is DXRG's on-chain trading agent research platform. Built for evaluating, constraining, and deploying market agents with deterministic controls and live execution data.
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.
