ChatGPT Work and Claude Cowork are not enterprise execution agents

ChatGPT Work and Claude Cowork are designed primarily as agentic workspaces. A separate option is to assemble an internal system from orchestration frameworks, custom agents, and MCP servers. These approaches solve useful problems, but they begin with different units of work from an execution agent operating on an ERP.

The relevant comparison is architectural rather than a connector count. Workspace products optimize for research, files, and office deliverables on a vendor’s model. Bruce optimizes for controlled completion on systems of record, with the inference provider treated as a replaceable dependency.

What ChatGPT Work and Claude Cowork actually are

Both products provide an agentic workspace around a vendor’s inference stack. ChatGPT Work focuses on long-running tasks across connected applications and office deliverables. Claude Cowork focuses on desktop files, connectors, plugins, and background knowledge work. Their enterprise controls govern workspace access and sessions. ERP execution adds a different control problem: transaction authority, validation against live state, recovery, and a function-specific definition of completion.

• Unit of done — a document, a folder, a research pack, a slide. Not a posted PO, journal, or close step scored against a job spec.
• State — files, chat, connectors. Not a continuously refreshed enterprise context graph with eviction.
• Tools — a catalog the vendor and your admin enable. Not a learned execution graph: intent → sequence → validation → recovery → completion on this tenant’s stack.
• Evals — session quality and policy logs. Not pass/fail of the same functional job at unlike businesses.
• Model — the workspace and inference provider are coupled; changing the model generally changes the product surface.

These tools are appropriate for research, analysis, and document production. Posting a purchase order, receiving inventory, or closing the books requires a separate execution contract because the resulting ERP state becomes authoritative for other teams and downstream systems.

What an internal build must supply

An internal build can provide complete control over orchestration, schemas, and deployment. It also leaves the team responsible for defining each job, encoding tenant-specific transaction rules, handling partial failure, and constructing production evaluations. Frameworks and MCP servers provide useful primitives; they do not include a pre-trained execution graph or cross-tenant evidence that a functional job completes correctly.

A workspace, an orchestration framework, and an execution system can coexist because they own different parts of the operating stack.

Where Bruce sits

Bruce is EGI’s enterprise execution agent. Its ERP runtime separates four concerns: the context graph maintains current tenant state; the execution graph defines the job and recovery paths; evaluations score resulting actions; and the control plane authorizes or rejects each write. Claude, GPT, or Gemini can provide inference within that runtime without owning the execution contract.

The practical deployment pattern is often coexistence. Use a workspace agent for files, research, and presentations. Build internally when the organization intends to own the execution infrastructure. Use an execution agent when a defined job must complete on a live ERP with policy, audit, and measurable operational outcomes.