The mind
- 01 Reason
- 02 Plan
- 03 Learn
- 04 Decide
- 05 Act
A Web3-native foundation for the autonomous economy
AI agents are becoming economic participants. Web3 gives them identity, ownership, payments, markets and settlement.
Network / pulse
01 / Thesis
Traditional software waits for a command. Autonomous agents observe, reason, decide and act across open networks — continuously.
See the runtimeThe missing half
Without Web3, an agent can think. With Web3, it can participate in the economy.
Where the economy starts
The first generation of autonomous agents is already taking shape across markets, research, security and machine-to-machine commerce.
Continuously analyzes market structure, on-chain activity, news, liquidity and risk to make policy-bound decisions.
Inspect the runtimeEvaluates protocols, yield, liquidity and exposure across networks — then rebalances within explicit policies.
Explore the stackReads reports, governance, whitepapers, news and chain data to produce a continuously updated thesis.
Read the researchWatches addresses, contracts, whale flows and protocol events to classify behavior and surface signals.
Follow the signalAnalyzes contracts, approvals, transactions and governance changes to explain risk before it compounds.
See security layersDiscovers services, compares quotes, pays with stablecoins, verifies results and updates portable reputation.
Trace an interactionA different class of demand
Agent workloads scale by frequency, context size, reasoning depth, tool calls and agent count — not synthetic token generation.
Always-on loops observe, reason, act, then observe again. Seven days a week, not one chat at a time.
Each decision carries history, market context, memory, tool results, portfolio state and risk rules.
A useful action is a chain of planning, research, analysis, validation, execution and review.
A manager delegates to research, data, risk, trading and compliance agents — multiplying context and calls.
Capacity / scenario 001
One autonomous trading agent can trigger millions of tokens every day through monitoring, research, reasoning, risk evaluation and post-trade review.
Illustrative workload Actual consumption depends on model, context size, reasoning frequency, architecture and strategy complexity.
1 agent → 17M tokens / day
The operating layer
AEF provides the environment. Users and institutions control their own strategies, policies and execution boundaries.
AEF does not operate proprietary trading strategies, custody user funds or guarantee returns. Third-party users deploy and operate their own autonomous agents.
The open layer beneath
Economic agency is not a feature. It is a stack of primitives that lets autonomous software identify, own, pay, contract and settle.
Read the foundation principlesIdeas for an open economy
A field guide to identity, ownership, payments and open markets for autonomous software.
Read the reportWhy programmable, global settlement is a missing primitive for AI agents.
Read insightLong context, multi-step reasoning and the economics of continuous analysis.
Read insightA foundation for the open machine economy
We are convening the protocols, researchers, infrastructure providers and builders shaping the economic layer for autonomous agents.
Join the ecosystem