Bitget officially launched GetAgent Playbook, a new strategy workflow layer within GetAgent and Bitget AI that moves AI trading beyond conversational interfaces.
The launch also marks the first user-facing implementation of Agent Harness, Bitget’s framework for organising AI reasoning, execution, and risk management into structured trading workflows.
While recent industry developments have focused on AI assistants capable of summarising markets, answering questions, and executing basic actions, Bitget sees the next stage of AI adoption emerging around workflow orchestration rather than larger models alone.
Earlier this year, Bitget reported more than 1 million users completing AI-powered trades across tools such as GetAgent and GetClaw, generating over $1.2 billion in cumulative trading volume.
“AI trading is evolving from Q&As into workflows, and half the complexity of using AI in trading workflows is configuring the prompt,” said Gracy Chen, CEO of Bitget.
“With GetAgent Playbook, users can simply pick and choose from a library of ready strategies to plug and play, turning trading ideas into something users can run, adapt, and build on easily.”
Users remain fully in control throughout the process. Playbooks can be browsed, previewed, configured, subscribed to, launched, and monitored while operating within user-authorised, isolated sub-accounts.
The system is designed around transparency, allowing users to review strategy logic, market fit, and risk settings before activation. Playbook will be available to GetAgent Plus and Pro users.
Under the hood sits Agent Harness, the technical layer powering Playbook.
Rather than relying on a single AI model, Agent Harness coordinates market analysis, execution logic, and risk controls into structured workflows while enforcing boundaries around execution paths, position sizing, and anomalies.
Every action remains logged and auditable.
Within Bitget’s Universal Exchange model, GetAgent Playbook extends AI from market interpretation into strategy infrastructure, supporting Bitget’s broader vision of an Agent-Native Exchange where intelligent systems become part of how markets are accessed and operated.
Since launching GetAgent, GetClaw, and Agent Hub, Bitget has expanded its AI ecosystem across traders, developers, and autonomous systems.
Agent Hub now supports 9 modules and 58 tools spanning Spot, Futures, Margin, Copy Trading, Earn, P2P trading, fund management, and execution functions.
The post Bitget moves AI trading from prompts to playbooks appeared first on Invezz
