The key to successful AI agents within an enterprise? Shared memory and context. This, according to Asana CPO Arnab Bose, provides detailed history and direct access from the get-go — with guardrail checkpoints and human oversight, of course. This way, “when you assign a task, you’re not having to go ahead and re-provide all of the context about how your business works,” Bose said at a recent VB event in San Francisco. AI as an active teammate, rather than a passive add-onAsana launched Asana AI Teammates last year with the philosophy that, just like humans, AI agents should be plugged directly into a team or project to create a collaborative system. To further this mission, the project management company has fully integrated with Anthropic’s Claude. Users can choose from 12 pre-built agents — for common use cases like IT ticket deflection — or build their own, then assign them to project teams and immediately provide a historical record of what tasks have already been completed and what is still yet to be resolved. Agents also have access to third-party resources like Microsoft 365 or Google Drive. “When that agent gets created, it’s not acting on behalf of someone, it manifests itself as a teammate and it gets all of the same sharing permissions, it inherits that,” Bose explained. Everything anyone does — humans and AI included — is documented to allow for “ease of explainability” and a “very transparent and trustworthy system.”But just like human workers, AI agents are kept in check: Critically, workflows incorporate checkpoints, where humans can give feedback and ask the agent to tweak certain elements of a project or adjust research plans. This is documented in what Bose called a “very human-readable way.” Also import …
