# ParallelPilot: Supporting Coordination and Monitoring in Parallel AI Coding

arXiv: https://arxiv.org/abs/2609.33113 · HTML: https://mlsanity.com/paper/2609.33113/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 25 of its 62 references that are in the map.
- First posted on arXiv 27 Sep 2026.

## Builds on (most cited first, 25 of 25)

- [Executable Code Actions Elicit Better LLM Agents](https://mlsanity.com/paper/2402.01030/) (2024)
- [Multi-Agent Collaboration via Evolving Orchestration](https://mlsanity.com/paper/2505.19591/) (2025)
- [Interactive Debugging and Steering of Multi-Agent AI Systems](https://mlsanity.com/paper/2503.02068/) (2025)
- [Need Help? Designing Proactive AI Assistants for Programming](https://mlsanity.com/paper/2410.04596/) (2024)
- ["The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning](https://mlsanity.com/paper/1911.08089/) (2019)
- [AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol](https://mlsanity.com/paper/2506.12508/) (2025)
- [Towards AI-Native Software Engineering (SE 3.0): A Vision and a Challenge Roadmap](https://mlsanity.com/paper/2410.06107/) (2024)
- [When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming](https://mlsanity.com/paper/2306.04930/) (2023)
- [AgentLens: Visual Analysis for Agent Behaviors in LLM-based Autonomous Systems](https://mlsanity.com/paper/2402.08995/) (2024)
- [Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025](https://mlsanity.com/paper/2512.14012/) (2025)
- [On the Impact of AGENTS.md Files on the Efficiency of AI Coding Agents](https://mlsanity.com/paper/2601.20404/) (2026)
- [Effective Strategies for Asynchronous Software Engineering Agents](https://mlsanity.com/paper/2603.21489/) (2026)
- [Not Just Novelty: A Longitudinal Study on Utility and Customization of an AI Workflow](https://mlsanity.com/paper/2402.09894/) (2024)
- [Agentic Visualization: Extracting Agent-based Design Patterns from Visualization Systems](https://mlsanity.com/paper/2505.19101/) (2025)
- [Agentic Coding in the Wild: Characterizing GitHub Copilot Traces at Production Scale](https://mlsanity.com/paper/2608.00101/) (2026)
- [From Conversation to Orchestration: HCI Challenges and Opportunities in Interactive Multi-Agentic Systems](https://mlsanity.com/paper/2506.20091/) (2025)
- [When Parallelism Pays Off: Cohesion-Aware Task Partitioning for Multi-Agent Coding](https://mlsanity.com/paper/2606.00953/) (2026)
- [Evolving with AI: A Longitudinal Analysis of Developer Logs](https://mlsanity.com/paper/2601.10258/) (2026)
- [Coding with "Enemy": Can Human Developers Detect AI Agent Sabotage?](https://mlsanity.com/paper/2606.05647/) (2026)
- ["I'm Not Reading All of That": Understanding Software Engineers' Level of Cognitive Engagement with Agentic Coding Assistants](https://mlsanity.com/paper/2603.14225/) (2026)
- [FeedQUAC: Quick Unobtrusive AI-Generated Commentary](https://mlsanity.com/paper/2504.16416/) (2025)
- [XAI for Coding Agent Failures: Transforming Raw Execution Traces into Actionable Insights](https://mlsanity.com/paper/2603.05941/) (2026)
- [DoubleAgents: Human-Agent Alignment in a Socially Embedded Workflow](https://mlsanity.com/paper/2509.12626/) (2025)
- [From Planning to Revision: How AI Writing Support at Different Stages Alters Ownership](https://mlsanity.com/paper/2604.11009/) (2026)
- [One Developer Is All You Need: A Case Study of an AI-Augmented One-Person Squad in a Brownfield Enterprise](https://mlsanity.com/paper/2605.18461/) (2026)

## Abstract (arXiv)

As coding assistants become increasingly autonomous, developers run multiple sessions in parallel, shifting the challenge from code generation alone to coordinating and monitoring concurrent agent work. Through a formative study (N=14), we identified PILOT: five supervisory practices for Planning, Isolating, Logging, Observing, and Triaging parallel sessions. We present ParallelPilot, a design probe that instantiates PILOT through a planning interface, a run-logger, and an ambient dashboard alongside existing coding tools. In a counterbalanced within-subjects study (N=16), participants using ParallelPilot increased ticket throughput by 63% in short coding tasks and supervised an average of one more concurrent agent at peak, while their tracking effort and context switching dropped. ParallelPilot also clarified execution plans, task dependencies, and intervention cues, and 14 of 16 participants preferred it over their current setup. These gains were not accompanied by significant improvements in perceived control or perceived success in redirecting the agents. Our findings demonstrate the value of explicit supervision support and position PILOT as a scaffold for designing tools that help people supervise concurrent work within and beyond coding. We suggest that future coding assistants should pair high-level awareness with low-cost paths back to the implementation evidence developers need to judge and steer agent work.