A trader runs 11 Grok Bot agents, each with one job and a scope document, with a Red Team agent that must approve a trade first.
A trader runs 11 Grok Bot agents, each with one job and a scope document, with a Red Team agent that must approve a trade first.
The trader moved a daily swing-trading prep workflow onto Grok Bot and organized it as 11 separate agents with an org-chart structure, a shared memory layer, and an agentic verification step. Each agent had one job plus MAP.md and CONTRACT.md files to define scope, used its own persistent cloud computer with browser, terminal, and file storage, and a Red Team agent had to pass a trade before anything else moved; the human still kept execution because none of the agents could place trades.
They say the persistent browsing setup fixed most of the scraping breakage from the earlier system and was easier to set up than Claude Agent Teams. The post gives no performance numbers or P&L, and it leaves open problems around pinning models to agents and understanding Cursor integration.
The main catch is subscription/tooling tradeoffs: they say Grok Bot was much easier to manage than Claude Agent Teams, assuming you have the right subscription tier.
Set up a small team of agents for my pre-market prep: one to scan [markets or tickers], one to summarize news, one to check my risk limits of [rules], and one skeptical reviewer that must challenge and approve any trade idea. Give each a short scope document with its single job. Output a daily list of reviewed ideas with the reviewer's verdict, and never place a trade without my explicit confirmation.
Score every demo request against your ICP, update HubSpot and ping the right rep in Slack within a minute of the form submit.
Every new Zendesk ticket gets a category, priority and sentiment tag plus a draft reply in an internal note before an agent opens it.
Copilot and Claude review each PR for bugs, missing tests and risky changes before a human looks, so reviewers can focus on design.