---
title: "Wilson Lin"
description: "Cursor researcher documenting planner-worker architectures for long-running autonomous coding."
section: "entities"
type: "entity"
created: "2026-08-24"
updated: "2026-08-24"
confidence: "high"
tags: ["person", "agents", "workflow"]
canonical: "https://pyweb.dev/wiki/wilson-lin"
---
# Wilson Lin

Wilson Lin is an author of Cursor's [Scaling long-running autonomous coding](https://cursor.com/blog/scaling-agents), which documents experiments coordinating hundreds of coding agents on large software projects.

## Planner–Worker Architecture

The Cursor team reports that flat peer coordination suffered from lock contention, abandoned locks, and agents choosing small, safe tasks. Their replacement separated responsibilities:

- planners explore and create tasks, recursively spawning sub-planners;
- workers complete assigned tasks without coordinating with one another;
- a judge decides whether another iteration is required.

The experiments included the FastRender browser project and other long-running migrations. The post presents these as research systems requiring review, not proof that autonomous swarms replace normal engineering discipline.

## Related Concepts

- [multi agent orchestration](/wiki/multi-agent-orchestration)
- [agent harness engineering](/wiki/agent-harness-engineering)
- [agentic engineering patterns](/wiki/agentic-engineering-patterns)

## Primary Source

- [Cursor: Scaling long-running autonomous coding](https://cursor.com/blog/scaling-agents)

---

## Agent Navigation

cluster: person (170 pages) | betweenness: 30.3

### References (outbound)
- [Multi-Agent Orchestration](https://pyweb.dev/wiki/multi-agent-orchestration.md)
- [Agent Harness Engineering](https://pyweb.dev/wiki/agent-harness-engineering.md)
- [Agentic Engineering Patterns](https://pyweb.dev/wiki/agentic-engineering-patterns.md)

### Referenced by (inbound)
- [Cursor](https://pyweb.dev/wiki/cursor.md)
- [Agentic Engineering Entity Accounting](https://pyweb.dev/wiki/agentic-engineering-entity-accounting.md)

### Evidence (verified primary sources)
- https://cursor.com/blog/scaling-agents

### Machine endpoints
- Knowledge graph: https://pyweb.dev/api/graph.json
- Graph analysis: https://pyweb.dev/api/graph-analysis.json
- Context index: https://pyweb.dev/llms.txt