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Workflow

AI Trading Assistant Workflow

Use AI to research, structure and pressure-test a trade plan, keeping approval and execution firmly human.

1 min readupdated 2026-09-02

/ quick answer

An assistant that assembles market and on-chain context, drafts a plan with explicit risk parameters, argues the opposite case, and hands it to you for approval. Use AI to research, structure and pressure-test a trade plan, keeping approval and execution firmly human.

Use AI to research, structure and pressure-test a trade plan, keeping approval and execution firmly human. The problem it solves: Trade decisions get made from fragments — a chart, a thread, a feeling — with no risk review and no record of the reasoning. An assistant that assembles market and on-chain context, drafts a plan with explicit risk parameters, argues the opposite case, and hands it to you for approval. It runs in 7 steps, starting with ingest context: price structure, liquidity, on-chain flows, upcoming catalysts and unlocks.
Problem
Trade decisions get made from fragments — a chart, a thread, a feeling — with no risk review and no record of the reasoning.
Solution
An assistant that assembles market and on-chain context, drafts a plan with explicit risk parameters, argues the opposite case, and hands it to you for approval.
Steps
  1. 01Ingest context: price structure, liquidity, on-chain flows, upcoming catalysts and unlocks.
  2. 02AI analysis: summarise the setup, the assumptions it depends on, and what would falsify it.
  3. 03Plan generation: entry zone, invalidation level, position size from your risk-per-trade rule, first target.
  4. 04Adversarial pass: instruct the model to argue against the trade and list what it cannot verify.
  5. 05Risk gate: reject the plan automatically if size exceeds limits or the invalidation level is undefined.
  6. 06Human approval: you accept, modify or discard — the assistant never signs.
  7. 07Execution and logging: execute manually from your wallet or CEX, log plan versus outcome for later review.
Tools Used
Prompts Used
Related Dictionary

/ frequently asked

Can the AI trade for me?

Technically yes, and it is a bad default. Language models are non-deterministic and can act on fabricated inputs. Keep signing human, or restrict execution to deterministic code with allowlists and spend caps.

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Related concepts

The vocabulary this page depends on.

  • →On-chain Agent

    An on-chain agent is an AI agent with read access to blockchain data and a tightly scoped ability to propose or execute transactions.

  • →Stop Loss & Take Profit

    Stop loss and take profit are pre-committed exit rules that convert a discretionary decision into an executable instruction.

  • →Crypto Risk Management

    Risk management in crypto is position sizing plus custody hygiene: deciding what you can lose per trade and what a single compromise can reach.

  • →Autonomous Workflow

    An autonomous workflow runs end-to-end without a human triggering each step — an agent decides the path, while humans set goals and approve exceptions.

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Related workflows

Turn this into a repeatable process.

  • →Automated Crypto Alerts

    Define the conditions that would change a decision, monitor them automatically, and receive one clean notification instead of watching charts.

  • →Automated DCA Workflow

    Set a recurring buy schedule that runs without your attention, with sizing and frequency chosen so fees stay negligible.

  • →AI Crypto Research Workflow

    A repeatable research loop: turn a question into market data, on-chain evidence and a written risk view before any position is considered.

  • →DEX Trading Workflow

    Execute an on-chain swap deliberately: research, liquidity check, route comparison, sized order, then position monitoring.

all workflows →

Related tool stacks

The tools that run it in production.

  • →AI Trading Stack

    Adds an AI analysis and risk-review layer on top of a trading stack, keeping approval and execution human.

  • →AI Crypto Research Stack

    A read-only research stack combining an AI assistant, web search, market data and on-chain analytics to screen assets quickly.

  • →Crypto Trading Stack

    Market data, charting, DEX access and a Web3 wallet — the minimum toolset for deliberate on-chain trade execution.

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Related prompts

Reusable prompts for this job.

all prompts →

Related use cases

How people apply it, and what came out.

  • →Build An AI Trading Assistant

    An assistant that drafts and attacks its own trade plans raised plan completeness to 100% and rejected a fifth of setups on liquidity grounds.

  • →Automate Trading Alerts

    Encoding invalidation levels as automated alerts removed screen-watching and caught two thesis breaks the trader would have slept through.

  • →Build An AI Crypto Research Agent

    A read-only research agent produced daily briefings on a 30-token watchlist, cutting a 90-minute manual routine to a 10-minute review.

  • →Get Token Alerts

    Replacing price-only alerts with condition-based rules cut notifications by 80% and caught a liquidity withdrawal before price reflected it.

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Comparisons & alternatives

Pick between the options.

  • →Manual Trading vs Automated Trading

    Manual trading adapts to context; automation enforces consistency. Most durable setups automate monitoring and keep judgement human.

  • →AI Agent vs Trading Bot

    A trading bot executes fixed rules deterministically; an AI agent interprets context and decides which steps to take — powerful for research, risky for execution.

  • →CEX vs DEX

    Centralised exchanges optimise for liquidity, fiat access and convenience; DEXs optimise for custody, permissionless listing and on-chain transparency.

  • →AI Research vs Traditional Research

    AI research compresses breadth and drafting; traditional research supplies verification and accountability for the claims you act on.

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