Cursor vs Conductor vs Superset — Which Agentic Code Editor Is The Best?

Topic / Goal

The speaker reviews and compares agentic coding editors—tools that run multiple coding agents in parallel so the user types little manual code. The video focuses on Conductor and Superset (newer), and Cursor (older “OG” AI editor), ending with a recommendation.

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Conductor (review + workflow details)

How it Works

• Uses a workspace + setup script model.
  • A setup script runs whenever a new “work tree” (agent instance workspace) is created.
• Each agent runs in its own isolated GitHub work tree, reducing change-collision risk.
• Agent controls:
  • command R starts/stops the run process
  • Provides a terminal instance per agent

Underlying Tech

• Conductor is described as a GUI wrapper around Claude Code and GPT Code.
• Supports a “plan” mode:
  • The LLM generates a plan
  • Then implements the changes

Key Feature: Model Handoff

• After planning, the user can “hand off” the plan to another model for implementation.
  • Example: generate a plan with one model (e.g., Opus) and implement with another (e.g., GPT 5.3).

Code Review / PR Workflow

• Shows changes via a diff viewer that feels PR-like.
• Supports AI code review of changes.
• Diff history behavior:
  • Often shows only the latest turn’s diff in the review UI
  • A way exists to view historical diffs
  • The speaker notes it can occasionally get out of sync
• Comments on diffs are possible, but:
  • Multi-line comment blocks are annoying/limited (comments appear effectively constrained when highlighting).
• Strong end-to-end automation:
  • One-click PR creation
  • Shows GitHub Actions / CI checks status (and links to logs) inside the app
  • Workspaces organize items into tabs (e.g., in progress, agents in review/PR mode, history/done)

Pros

• Polished graphical UI (speaker prefers GUI over terminal).
• Smooth workflow: agent edits → diff review → PR → CI status.
• Quality-of-life: inline visibility into CI failures and logs; includes “Fix error” on failing test cases.

Cons / Limitations

• May lag behind the newest Claude/GPT tooling:
  • Because Conductor wraps Claude Code/GPT Code, it may not support the latest command updates immediately (example: {slash} simplify and {slash} batch not available).
• Diff view is mostly text diff only:
  • No strong LSP/IntelliSense-style features (e.g., references or jump-to-definition).
• Complex edits may still require opening Cursor.

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Superset (review + workflow details)

How it Works

• Similar overall concept to Conductor (multi-agent/workspaces/diff + PR flow).
• Implemented in a CLI / terminal-first style.
• Adds a workspace initiation prompt like: “What do you want to build…”
  • The user prompt can seed the initial agent work.

Underlying Tech / Compatibility Advantage

• Because Superset is terminal-forward, the speaker claims it supports the latest Claude Code / GPT Code versions and commands faster.
• This avoids Conductor’s UI wrapper delay.

Code Review / PR Workflow

• Diff viewer experience described as very similar to Conductor.
• Includes a UI control to show/hide unchanged lines.
• However:
  • Like Conductor, it’s mainly a diff tool without deeper LSP/intellisense-style workflows.
  • PR CI/check visualization is less “fancy”:
    • The speaker must open the PR page to verify merge safety.

Model Handoff Limitation

• Unlike Conductor, the speaker couldn’t find a way to hand off a plan to a different model for implementation.

Other Workflow Refinement Gaps

• Superset is reported as weaker at automatically tracking PR state and organizing work:
  • Less automatic movement into done/backlog, requiring more manual management.
• CI status/check progress reporting is slower/less informative in the UI.

Pros

• Best for users who prefer terminal-first workflows.
• Claimed advantage: bleeding-edge Claude/GPT command support via direct terminal access.
• Can use arbitrary CLI tools directly (example: Gemini CLI for UI/UX design tasks).

Cons

• Less refined end-to-end experience than Conductor:
  • CI visualization, PR safety checks, workspace automation, and model handoff
• The user may still need an IDE elsewhere for complex work.

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Cursor (review + issues with multi-agent workflow)

Agent-Mode Positioning

• The speaker argues Cursor’s agent mode is not the first-class citizen.
• Cursor’s “hero product” is framed as the traditional AI IDE rather than an agent orchestration layer.

Observed Problems

• Multi-agent review confusion:
  • The UI/PR review panel sometimes shows stale or mismatched changes versus what each agent chat claims it changed.
  • Summaries may say multiple files changed, but the review panel shows only one file—or shows the previous agent’s changes.
• Workflow friction:
  • Pre-check/PR creation errors occur
  • Sometimes the PR must be created via a new branch or after retrying
• The speaker describes a learning curve / instability in mapping changes to each agent.

Important Note

• The speaker also mentions uncertainty about whether conversation continuation across workspaces was possible.
• It was initially thought impossible, but later “works.”
• They call it a “bloopers alert,” suggesting earlier failure was due to misunderstanding or capability mismatch.

Conclusion on Cursor

• As of filming (March 2026), the speaker feels Cursor’s multi-agent experience is not smooth and requires “fighting” the tool.
• They believe it will likely improve later (feature is actively being worked on), but for now it’s less reliable than Conductor/Superset.

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Overall Recommendation (speaker’s conclusion)

• Best overall: Conductor
  • Most seamless agent edits → review → PR → CI checks experience
  • Lowest learning curve for the speaker’s workflow
  • Strong GUI and integration features
• Superset
  • Best alternative if you prefer terminal-only workflows
  • Want faster access to latest CLI-supported commands/tools
• Cursor
  • Recommended only if you want Cursor’s traditional IDE capabilities for deeper edits
  • Not endorsed as the primary agentic multi-agent workflow due to synchronization/review confusion

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Main Speakers / Sources (as stated)

• Primary speaker / reviewer: the video narrator (testing Conductor, Superset, and Cursor)
• Referenced external source/creator: “Cat Woo” (head of PM, creator of Claude Code)
• Sponsors / referenced company: Crusoe AI (video sponsor for model deployment/inference acceleration)