Guides to how agents work, how they use data and tools, and which controls matter before applying them to crypto.
7 articles
Learning path
Learn what an agent can do, how it connects to data and tools, and where human validation, permissions, and risk limits belong.
Distinguish agents, bots, and assistants. Understand their limits before using them around financial decisions.
Understand data, models, tools, memory, permissions, and validation before building.
Compare analysis, automation, and bots without assuming every example is a live product.
This framework applies to both managed tools and custom agents. Automation does not remove the responsibility to verify.
Source, date, coverage, and quality.
Visible objective, assumptions, and rules.
Sources, tests, and human review.
Minimum permissions, limits, and a stop path.
No. LV Chat explains concepts, finds CryptoLV guides, and can calculate position size. It does not connect wallets, monitor live markets, or execute trades.
A managed agent prioritizes quick setup within a provider's defined limits. A custom agent offers more control over data, tools, permissions, and evaluation, but requires your own maintenance and security.
Check the date and source of its data, every tool permission, how outputs are verified, and whether a person can stop or correct any action before capital is at risk.

Before connecting a bot or AI agent to an exchange, understand its permissions, failure modes, costs, and scam signals.

Use AI to organize public blockchain data without turning labels, flows, dashboards, or model summaries into trading instructions or identity claims.

A practical way to design agent-initiated payments without treating a wallet, payment protocol, or identity proposal as permission to spend without limits.

Five practical ways an AI agent can reduce friction in crypto workflows without taking over research, security decisions, or control of a wallet.

What OpenClaw's own security guidance says about local-first agents, trusted operators, tools, credentials, multi-user isolation, and crypto-adjacent workflows.

A builder-focused reference architecture for crypto AI agents that keeps untrusted input, model reasoning, tools, policy, signing, logs, and recovery in separate layers.

A practical, source-backed path from read-only research assistant to tightly controlled transaction workflow, without treating autonomy as a trading edge.
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