I made coding agents compete against each other instead of accepting the first solution
I've been building an AI coding agent called Offset, and one of its features ended up becoming the thing I'm most interested in:
Speculative Branching.
Give Offset a coding task and it can create multiple isolated Git worktrees and have different agents independently attempt the task.
Then it can test those implementations and use the results to determine which approach actually succeeded.
It's basically:
one task → multiple implementations → tests → winner → merge
I also built a Planner → Implementer → Critic orchestration mode, multi-provider model support, subagents, BYOK, and a terminal UI around the whole workflow.
The project is still evolving, so I'm curious about something more fundamental:
Would you actually want an agent to spend extra inference/compute exploring several solutions, if it increased the chance of getting a working implementation?
Or is a single strong model with good tool use already the better approach?
I'm the person who built Offset, so feel free to tear the idea apart 😅
I'll put the project links in the comments.