Plain-English building
Both can draft an executable system from a description of the job and let collaborators refine it without application code.
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Malleable compared with OpenAI Workspace Agents
Malleable vs. OpenAI Workspace Agents: shared agents and multi-person operations
OpenAI Workspace Agents and Malleable both turn plain-English direction into repeatable work across company tools, with shared editing, schedules, triggers, permissions, and approvals. Workspace Agents centers that system on a reusable agent. Malleable centers it on the operation the team owns together.
Shared foundation
What Malleable and OpenAI Workspace Agents have in common.
Repeatable work
Both can run recurring assignments through schedules, direct use, or programmatic triggers.
Connected action
Both use approved tools, apps, skills, and company context to gather information and act across systems.
Governed collaboration
Both support shared ownership, published changes, constrained actions, and human confirmation before sensitive writes.
The main difference
What is shared and improved across the team?
OpenAI Workspace Agents
A Workspace Agent packages reusable instructions, a model, files, memory, skills, apps, permissions, schedules, and channels. Teammates run or co-edit that agent.
Malleable
The team shares an operation: its outcome, stages, rationale, constraints, roles, handoffs, and run history. Agents and people each perform the parts they own.
Side by side
What follows from that difference.
OpenAI Workspace Agents
Malleable
System boundary
OpenAI Workspace Agents
The shared system ends at the agent, its apps, channels, and schedulesMalleable
The shared system spans the complete multi-person operationAuthorship
OpenAI Workspace Agents
Builders translate the process into an agent plan and configurationMalleable
Domain experts define and inspect how the operation should runRun consistency
OpenAI Workspace Agents
Each trigger starts an agent that interprets the same instructions againMalleable
The published operation keeps a stable path while judgment handles variationHuman coordination
OpenAI Workspace Agents
People invoke, supervise, or approve the agent through configured channelsMalleable
Handoffs bring each participant in for the work they ownChange scope
OpenAI Workspace Agents
Editors change agent assets and must anticipate effects on every runMalleable
The expert describes the change and reviews its operational effectAudit context
OpenAI Workspace Agents
Versions and runs show agent use, while operating rationale lives elsewhereMalleable
One record connects rationale, published changes, runs, and decisions