Before submitting
Area
Not sure
Problem or use case
Today a thread in t3code is tied to a single agent running one task at a time. There is no way to run multiple agents in parallel within the same thread, whether multiple instances of the same provider (e.g. several Claude agents working on different parts of a task) or a mix of different providers (e.g. Claude and Codex together). This limits how quickly independent sub-tasks in the same conversation/thread can be worked on, since everything is serialized through a single agent.
Proposed solution
Allow spawning and running several agents concurrently inside the same thread, similar to Cursor's "Multitask"/parallel agents mode: either multiple instances of the same provider or a mix of different providers (e.g. Claude + Codex + OpenCode) working side by side on separate sub-tasks, with their outputs surfaced back into the shared thread/conversation.
Why this matters
Parallel agents let users get through multi-part tasks much faster by working on independent sub-tasks simultaneously instead of waiting for one agent to finish each step in sequence. It also lets users combine the strengths of different providers on the same problem (e.g. one agent handling backend changes while another handles frontend or tests) without leaving the thread.
Smallest useful scope
A minimal version could support spawning 2 additional agents inside a thread (same provider, running on clearly separated sub-tasks), with their output appended to the thread once done.
Alternatives considered
Currently the only workaround is opening separate threads for each sub-task and manually merging the results, which loses shared context and adds manual coordination overhead. Cursor's Multitask mode is the closest existing example of this pattern.
Risks or tradeoffs
Running multiple agents concurrently increases cost (multiple provider sessions billed at once) and adds complexity around merge conflicts when agents edit overlapping files or state. The UI/thread model also needs a clear way to show which agent produced which output, and how partial/conflicting results are reconciled.
Examples or references
Cursor's "Multitask" mode, which lets multiple agents work in parallel within the same session, is a comparable existing implementation of this pattern.
Contribution
Before submitting
Area
Not sure
Problem or use case
Today a thread in t3code is tied to a single agent running one task at a time. There is no way to run multiple agents in parallel within the same thread, whether multiple instances of the same provider (e.g. several Claude agents working on different parts of a task) or a mix of different providers (e.g. Claude and Codex together). This limits how quickly independent sub-tasks in the same conversation/thread can be worked on, since everything is serialized through a single agent.
Proposed solution
Allow spawning and running several agents concurrently inside the same thread, similar to Cursor's "Multitask"/parallel agents mode: either multiple instances of the same provider or a mix of different providers (e.g. Claude + Codex + OpenCode) working side by side on separate sub-tasks, with their outputs surfaced back into the shared thread/conversation.
Why this matters
Parallel agents let users get through multi-part tasks much faster by working on independent sub-tasks simultaneously instead of waiting for one agent to finish each step in sequence. It also lets users combine the strengths of different providers on the same problem (e.g. one agent handling backend changes while another handles frontend or tests) without leaving the thread.
Smallest useful scope
A minimal version could support spawning 2 additional agents inside a thread (same provider, running on clearly separated sub-tasks), with their output appended to the thread once done.
Alternatives considered
Currently the only workaround is opening separate threads for each sub-task and manually merging the results, which loses shared context and adds manual coordination overhead. Cursor's Multitask mode is the closest existing example of this pattern.
Risks or tradeoffs
Running multiple agents concurrently increases cost (multiple provider sessions billed at once) and adds complexity around merge conflicts when agents edit overlapping files or state. The UI/thread model also needs a clear way to show which agent produced which output, and how partial/conflicting results are reconciled.
Examples or references
Cursor's "Multitask" mode, which lets multiple agents work in parallel within the same session, is a comparable existing implementation of this pattern.
Contribution