Orchestrating Parallel AI Agents to Triple Delivery Throughput
Turning a repetitive monorepo unification effort into a parallel-agent workflow — delivering three times the throughput
About
A client engaged Lumenalta®to carry out a platform unification effort inside a large monorepo, where a single epic required the same kind of change to be applied across many separate packages. Lumenalta®'s engineers owned the work end to end, from planning each change through review, testing, and delivery.
Rather than treat the engagement as a fixed task list, Lumenalta®'s team recognized an opportunity to change how the work itself was executed.
3× throughput
for the epic compared with the team's usual baseline
3 parallel sub-agents
dispatched per workflow run, behind a human review gate
24 story points
across 12 work items delivered in a single sprint
Challenge
The unification task was repetitive but not trivial. Because the project lived in a monorepo, the same change had to be made carefully across numerous packages. Worked the conventional way — one ticket at a time, one package after another — the epic meant crawling through the codebase sequentially, with throughput capped by how fast a single stream of work could move. The pattern across tickets was consistent enough to feel mechanical, yet the volume made it slow to clear.
Solution
After completing the first two tickets of the epic, Lumenalta®'s team saw that the work followed a clear, repeatable pattern — one that could be generalized into a workflow driven by parallel agents, so multiple packages could be addressed at once instead of one by one. That insight turned a long task list into an orchestration problem.
The workflow runs in defined stages:
- Ingest. It reads each ticket's description to understand the change required.
- Isolate. It sets up separate, isolated Git work trees so parallel work cannot collide.
- Plan. It architects a plan for the change before any code is written.
- Human review gate. Lumenalta®'s engineers step in to review the planning output and provide any clarifications needed — the point where human judgment shapes the work before it scales.
- Parallel execution. Once clarified, the system dispatches up to three sub-agents to execute the changes across packages simultaneously.
The cap of three agents is deliberate. Because Lumenalta®'s engineers review, test, and take ownership of everything the agents produce before it ships, the workflow is sized to keep that human review meaningful rather than overwhelmed. The agents supply velocity; Lumenalta®'s engineers supply direction and intent.
Just as important is what the workflow is not. It is not a reusable template to be applied blindly. It is an instrument crafted for one specific epic, built by synthesizing what the team knew about the codebase with its own engineering experience. Lumenalta®'s approach is grounded in evidence rather than hype: a study evaluating 180 agent configurations underscores that multi-agent systems are not a universal solution — coordination can dramatically improve performance on parallelizable tasks while degrading it on sequential ones. Knowing which is which is the expertise that makes the workflow pay off.
Results
Generalizing the pattern into parallel agents changed the economics of the epic:
- Throughput multiplied. In a single sprint, Lumenalta®delivered 24 story points across 12 work items — roughly a threefold increase over the team's normal baseline for this epic.
- A team win, not a solo trick. The shift moved the team from tackling one task at a time to orchestrating work in batches, raising the whole team's output rather than a single contributor's.
- Quality stayed owned by humans. Every change is reviewed and tested by Lumenalta®'s engineers before delivery. Speed is delegated to the agents; quality remains the team's responsibility.
The broader lesson is that velocity and control are not in tension when the workflow is designed for both. By pairing parallel execution with a human review gate and a deliberate limit on concurrency, Lumenalta®scaled delivery without surrendering the judgment that keeps a unified platform coherent — a pattern the team can carry into the next epic that fits it.
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