Dynamic workflows
Not every job is a flat set of parallel tasks. Many are pipelines: analyze, then plan, then implement, then verify — where each step depends on what came before, and the shape of later steps is decided by earlier results. A dynamic workflow in Syntic Code is exactly this kind of orchestration, where Amara chains agents together, passing output from one stage into the next and adapting the plan as it goes.
The word dynamic matters. The workflow is not a rigid script fixed in advance; Amara can decide at runtime how many agents to spawn, which specialist each stage needs, and whether a result warrants a follow-up step. This makes workflows well suited to open-ended tasks where you cannot enumerate every step up front.
Stages and hand-offs
A workflow is a sequence of stages, each carried by one or more agents. A typical implementation workflow might look like this:
- Investigate — an agent explores the codebase and reports how the relevant system works.
- Plan — a second agent turns that report into a concrete change plan.
- Implement — one or more agents apply the plan, often in parallel across files.
- Verify — a final agent runs tests and reviews the diff.
Each stage receives the previous stage’s output as its input. Because only results flow between stages — not full transcripts — the pipeline stays efficient even when individual stages do heavy exploration.
Branching and control
Workflows can branch on results. If verification fails, Amara can loop back to the implementation stage with the failure details rather than reporting a dead end. If investigation reveals two independent subsystems, the plan stage can fan out into parallel implementation teams. Combine workflows with agent teams for the parallel stages and with worktrees when concurrent implementers must edit code in isolation. Throughout, the agent view shows you which stage is active and lets you intervene before a bad result propagates downstream.