Multi-Tasking Agents
April 9, 2025
AI agents are getting better at understanding intent, holding context, and offering relevant answers. But until recently, they’ve been confined to a single thread of conversation — reacting to whatever comes in, one message at a time. That model works well for simple interactions, but it begins to break down as tasks grow more complex.
Now imagine an agent that can do something more: not just respond, but create new conversations when needed. An agent that knows when a discussion should split, when a new context is required, or when a separate task needs its own space. This new capability — to initiate and redirect chats — is a small structural change that opens the door to more collaborative, task-aware AI.
What This Means in Practice
When agents can start new chats, they’re no longer bound to a single, linear thread. Instead, they can organize interactions in a more modular, intentional way. A customer support agent, for example, could detect that a user’s question spans two different topics — billing and technical setup — and offer to split the conversation. One thread continues to handle onboarding, while the other focuses purely on resolving the billing issue.
In internal tools, this capability can support workflows that require branching attention. Imagine an agent embedded in an HR platform: if it detects that an employee is updating benefits and also needs to submit a leave request, it can open a new chat focused on leave policies — without derailing the original task. Conversations become more focused, and users aren’t overwhelmed by juggling multiple goals in a single thread.
The agent, in this case, isn’t just answering questions — it’s managing attention, helping structure a more productive exchange.
“Once our agent could split conversations, it stopped feeling like a chatbot and started acting like a real teammate—handling multiple tasks without losing the thread.”
Redirection as Collaboration
Being able to redirect a user to a new conversation isn’t just a technical trick; it’s a way for agents to become more collaborative. Just as humans will say “let’s take this offline” or “let’s start a new thread for that,” agents can now make those same decisions to preserve clarity and intent.
This is especially valuable when an agent is supporting multi-step workflows. For instance: - During a troubleshooting session, if the agent detects that a hardware reset is needed, it can start a new chat that walks the user through that process, step-by-step, without interrupting the broader diagnostics thread. - In a training context, an agent can spin up a dedicated chat for a specific module or exercise, giving users a clean slate for focused interaction — and preserving the structure of the overall learning flow.
By initiating and managing multiple chats, agents take a more active role in organizing work and guiding users through complex tasks. The user doesn’t need to know which thread to use or when to switch topics — the agent handles that gracefully in the background.
A Foundation for Multi-Tasking Agents
This ability to split, redirect, and manage multiple conversational contexts is a foundational piece of building agents that can truly multi-task. It allows them to engage with more than one task at a time, not in a chaotic way, but with clear boundaries between threads. Each conversation becomes a dedicated workspace for a specific goal.
This is particularly important as we begin to expect more from AI — not just isolated responses, but end-to-end support across workflows. Whether it’s managing approvals, walking through product configurations, or triaging issues across different teams, agents need the ability to move fluidly between contexts without losing track of what’s important.
And that begins with something simple: the ability to say, “Let’s take this in a new chat.”
How This Changes What’s Possible
For users, this unlocks smoother, more structured experiences. Conversations stay focused, handoffs are cleaner, and workflows are easier to follow. You’re no longer stuck in a single, overloaded thread. Instead, your agent can guide you through tasks in a way that reflects how we naturally think and work: one focused task at a time, clearly separated, but all part of a larger whole.
As agents become more capable, we’ll see more use cases where multi-chat coordination becomes the norm. Agents might coordinate across teams, manage follow-ups across time, or maintain separate threads for planning, execution, and review. Each chat becomes a tool for clarity — not clutter.
This shift represents a meaningful step toward agents that aren’t just reactive tools, but proactive collaborators. By managing how and where conversations happen, they support us not just with information, but with structure. And in complex environments, structure is often what makes action possible.
