diff --git a/apps/marketing/content/blog/agent-orchestration-not-another-agent.mdx b/apps/marketing/content/blog/agent-orchestration-not-another-agent.mdx new file mode 100644 index 00000000000..5952130ef62 --- /dev/null +++ b/apps/marketing/content/blog/agent-orchestration-not-another-agent.mdx @@ -0,0 +1,121 @@ +--- +title: "You Don't Need Another AI Coding Agent — You Need an Orchestrator" +description: "The AI coding tools landscape is flooded with agents. The real bottleneck isn't agent quality — it's managing multiple agents at scale. Here's why orchestration is the missing layer." +author: satya +date: 2026-02-18 +category: Product +relatedSlugs: + - parallel-coding-agents-guide + - roadmap-to-100-agents + - working-with-worktrees-in-superset +--- + +Every month, a new AI coding agent launches. Claude Code. Codex. Aider. OpenCode. Cursor's agent mode. Windsurf's Cascade. Devin. The list keeps growing. Each promises to be smarter, faster, more capable than the last. + +Here's the thing: the agents are already good enough. Claude Code can refactor a module. Codex can write a test suite. Aider can iterate on a bugfix. The quality difference between top-tier agents is shrinking. What's not getting better is the workflow around them. + +The real bottleneck isn't agent quality. It's agent quantity. + +--- + +## The Single-Agent Ceiling + +Most developers use AI coding agents the same way: + +1. Open terminal +2. Describe a task +3. Watch the agent work +4. Review the output +5. Give feedback or merge +6. Repeat + +This is sequential. One task at a time. The agent might take 5 minutes. Your review might take 10. That's one task per 15 minutes, four tasks per hour. For an individual developer, that's a solid productivity boost. + +But your codebase has 50 parallelizable tasks right now. Writing tests for untested modules. Refactoring deprecated patterns. Updating stale documentation. Migrating config formats. Fixing lint warnings. Each task is independent. None requires the output of another. + +Running them one at a time means 50 tasks at 15 minutes each: over 12 hours. Running 5 in parallel: under 3 hours. Running 10 in parallel: under 2 hours. The math is straightforward. The orchestration is the hard part. + +--- + +## Why Orchestration Is Hard + +### Isolation + +Two agents in the same directory destroy each other's work. You need filesystem-level isolation — each agent in its own working directory with its own branch. Git worktrees solve this elegantly, but setting them up manually for every task is tedious. + +### Session Management + +Agents crash. Terminals close. Laptops go to sleep. If your agent's session dies, you lose the context and have to restart. For a single agent, this is annoying. For 10 agents, it's unmanageable. + +### Review + +The review workflow matters more with parallel agents, not less. You need to see what each agent changed, verify it against the task description, and decide whether to merge or iterate. Without a unified view across all tasks, you're tab-switching between terminals. + +### Task Allocation + +Not every task suits every agent. Claude Code handles complex refactors better than Codex. Codex is faster for well-defined tasks. Aider excels at iterative changes. An orchestrator lets you match agents to tasks instead of using one agent for everything. + +--- + +## Orchestration vs More Agents + +The AI coding industry is betting heavily on better agents. Smarter models, larger context windows, better tool use. These improvements are real and valuable. + +But consider: a 20% improvement in agent quality (smarter code, fewer bugs) improves throughput by 20%. Running 5 agents in parallel instead of 1 improves throughput by 5x. The orchestration layer has more leverage than the agent layer. + +This isn't an argument against better agents. It's an argument that the orchestration layer deserves equal attention. The best coding agent in the world, run one at a time, is slower than a good agent run ten at a time. + +--- + +## What Good Orchestration Looks Like + +### Automatic Isolation + +Creating a task should automatically create a Git worktree and branch. No manual setup, no remembering to checkout a new branch, no worrying about file conflicts. The orchestrator handles this transparently. + +### Session Persistence + +Agent sessions should survive crashes, app restarts, and laptop sleep cycles. A background daemon that owns the sessions independently of the UI solves this — the same pattern that tmux uses for terminal multiplexing, applied to agent orchestration. + +### Agent Agnosticism + +Lock-in to a single agent is a strategic mistake. The AI landscape moves fast. Today's best agent might be tomorrow's second-best. An orchestrator should run any CLI-based agent — Claude Code, Codex, Aider, OpenCode, or whatever ships next week. + +### Unified Review + +All active tasks, their status, and their diffs should be visible in one place. When a task completes, the review workflow should be fast: see the diff, open in your editor if needed, merge or give feedback. Seconds per review, not minutes. + +### Editor Integration + +Developers have strong editor preferences. The orchestrator shouldn't force an editor choice. It should integrate with whatever you use — VS Code, Cursor, JetBrains, Xcode, Neovim — and let you open any worktree in your preferred environment. + +--- + +## Building This at Superset + +We built [Superset](https://superset.sh) because we hit this ceiling ourselves. We were running Claude Code for everything — and it was great for individual tasks. But scaling to 5-7 agents manually was operational overhead that distracted from the actual work. + +The architecture is intentionally simple: + +- **Git worktrees** for isolation (no containers, no VMs) +- **Persistent daemon** for session management (Unix domain sockets, survives crashes) +- **Any CLI agent** as a first-class citizen (no SDK integrations to maintain) +- **Built-in diff viewer** for fast review +- **Editor integration** for deep inspection (VS Code, Cursor, JetBrains, Xcode) + +The orchestrator doesn't make agents smarter. It makes using agents at scale practical. That's the missing layer in most developers' AI workflows — not a better agent, but a better way to run the agents they already have. + +--- + +## The Compound Effect + +Running parallel agents has a compound effect on productivity: + +1. **More tasks completed per day** — 5x agents means 5x throughput (minus review overhead) +2. **Faster iteration** — while one agent iterates on feedback, others are working on new tasks +3. **Better agent matching** — use the right agent for each task instead of one-size-fits-all +4. **Reduced context switching** — tasks run to completion in isolation instead of being stashed and resumed + +The developers we work with who've adopted parallel agent workflows don't go back to single-agent work. The throughput difference is too large. The question shifts from "which agent should I use?" to "how many agents can I effectively manage?" + +That's the right question. And the answer is: as many as your orchestrator supports and your review speed allows. diff --git a/apps/marketing/content/blog/parallel-coding-agents-guide.mdx b/apps/marketing/content/blog/parallel-coding-agents-guide.mdx new file mode 100644 index 00000000000..9ab00d9ebb8 --- /dev/null +++ b/apps/marketing/content/blog/parallel-coding-agents-guide.mdx @@ -0,0 +1,210 @@ +--- +title: "The Complete Guide to Running Parallel AI Coding Agents" +description: "How to run multiple AI coding agents in parallel without conflicts. Covers isolation strategies, orchestration patterns, and practical workflows for scaling from 1 to 10+ agents." +author: avi +date: 2026-02-18 +category: Engineering +relatedSlugs: + - working-with-worktrees-in-superset + - roadmap-to-100-agents + - git-worktrees-history-deep-dive +--- + +Running one AI coding agent is straightforward. Running ten at once introduces problems that most developers haven't encountered before: file conflicts, branch collisions, resource contention, and a review bottleneck that grows linearly with agent count. This guide covers the patterns that work and the mistakes to avoid. + +--- + +## Why Parallel Agents? + +A single coding agent handles one task at a time. You prompt, it works, you review, you iterate. At best, you're doing one unit of agent work per cycle. + +But most codebases have dozens of parallelizable tasks at any given time: + +- Writing tests for module A doesn't conflict with refactoring module B +- Updating API docs doesn't conflict with fixing a database query +- Adding input validation doesn't conflict with migrating a config format + +These tasks are independent. They can — and should — run simultaneously. The bottleneck isn't the agent or the model. It's the human orchestrating one task at a time. + +--- + +## The Isolation Problem + +Running two agents in the same directory creates immediate problems: + +``` +Agent 1: Opens src/auth/login.ts, starts refactoring +Agent 2: Opens src/auth/login.ts, starts adding validation +Agent 1: Writes its version of login.ts +Agent 2: Writes its version of login.ts (overwrites Agent 1) +Agent 1: Commits — but the file is Agent 2's version +``` + +This isn't a theoretical risk. It happens every time two agents touch overlapping files. Even if they're editing different files, a shared `git index` means their commits can include each other's uncommitted changes. + +### Solution: One Worktree Per Agent + +Git worktrees solve this at the filesystem level: + +``` +~/project/ # Your main working tree +~/project-agent-tests/ # Agent 1: writing tests (own branch, own files) +~/project-agent-refactor/ # Agent 2: refactoring auth (own branch, own files) +~/project-agent-docs/ # Agent 3: updating docs (own branch, own files) +``` + +Each worktree has: +- Its own copy of the working directory +- Its own branch +- Its own staging area (git index) + +They share the git object store, so creating a worktree takes seconds and costs minimal disk space. + +--- + +## Orchestration Patterns + +### Pattern 1: Manual Worktrees + +The simplest approach — create worktrees yourself and run agents manually: + +```bash +git worktree add ../project-tests -b agent/tests +cd ../project-tests +claude-code "Write unit tests for the auth module" +``` + +This works for 2-3 agents but breaks down at scale. You're managing worktrees, branches, and terminals manually. + +### Pattern 2: Scripted Orchestration + +A shell script that automates worktree creation and agent launching: + +```bash +#!/bin/bash +TASK_NAME="$1" +AGENT_CMD="$2" +BRANCH="agent/$TASK_NAME" +WORKTREE_DIR="../$(basename $(pwd))-$TASK_NAME" + +git worktree add "$WORKTREE_DIR" -b "$BRANCH" +cd "$WORKTREE_DIR" +eval "$AGENT_CMD" +``` + +Better, but still no unified view of all tasks, no session persistence, and no diff review workflow. + +### Pattern 3: Dedicated Orchestrator + +Tools like [Superset](https://superset.sh) handle orchestration end-to-end: + +1. **Task creation** — describe the task, pick an agent +2. **Automatic isolation** — worktree and branch created automatically +3. **Session management** — persistent daemon keeps sessions alive across crashes +4. **Diff review** — built-in diff viewer for reviewing agent output +5. **Editor integration** — open any worktree in VS Code, Cursor, JetBrains, or Xcode + +This is the approach that scales to 5-10+ concurrent agents without operational overhead. + +--- + +## Choosing the Right Agent Per Task + +Different agents have different strengths. A parallel workflow lets you match agents to tasks: + +### Claude Code +- Complex multi-file refactors +- Architectural changes (new patterns, module restructuring) +- Debugging subtle issues that require deep codebase understanding +- Tasks requiring MCP tool integration + +### Codex CLI +- Well-scoped, clearly defined tasks +- Full Auto mode for autonomous execution +- Tasks where OpenAI models (o3, o4-mini) perform well +- Cost-sensitive tasks using cheaper models + +### OpenCode +- Tasks where model flexibility matters (75+ providers) +- Cost optimization across different providers +- Teams running local models via Ollama +- Tasks that benefit from LSP integration + +### Aider +- Iterative pair programming tasks +- Small, focused changes with tight feedback loops +- Tasks requiring frequent back-and-forth + +The key insight: you don't have to choose one agent for everything. Run Claude Code on the complex refactor and Codex on the test generation simultaneously. + +--- + +## The Review Bottleneck + +Parallel agents create a new problem: review throughput. If you run 10 agents and each produces a diff in 15 minutes, you have 10 diffs to review per hour. + +### Strategies for Fast Review + +**Prioritize by risk:** A test addition is low-risk and can be reviewed quickly. A database migration is high-risk and needs careful review. Triage diffs by impact. + +**Review diffs, not files:** Don't re-read the entire file. Focus on what changed. If the diff is scoped to what you asked for and the tests pass, a quick review is usually sufficient. + +**Let agents verify their own work:** Before reviewing, check if the agent ran tests. If tests pass and the diff is clean, your review is a sanity check rather than a first-pass audit. + +**Use structured task descriptions:** "Add input validation to the signup form: email must be valid, password must be 8+ characters, display inline errors" produces a reviewable diff. "Improve the signup form" produces something unpredictable. + +**Batch similar tasks:** Review all test additions together, then all refactors. Context switching between different types of changes is the biggest time sink in review. + +--- + +## Resource Management + +### CPU and Memory + +Each agent consumes local resources for: +- The agent process itself (terminal, file I/O) +- Language servers (TypeScript, Go, Python) if the agent uses them +- Build processes if the agent runs builds +- Test suites if the agent runs tests + +On a modern laptop, 5-7 concurrent agents are comfortable. Beyond that, you may want to stagger agent launches or limit concurrent builds. + +### API Rate Limits + +Each agent makes API calls to its model provider. Running 10 Claude Code instances hits Anthropic's rate limits faster than one. Monitor your provider's rate limit headers and throttle if needed. + +### Disk Space + +Each worktree is a full checkout of your working directory. For a 1GB repo, 10 worktrees use ~10GB. The git object store is shared, so history isn't duplicated. Clean up completed worktrees promptly. + +--- + +## Common Mistakes + +### Running Too Many Agents at Once + +Start with 2-3 until you're comfortable with the review workflow. Scaling to 10 before you can review at speed creates a backlog that slows everything down. + +### Vague Task Descriptions + +"Fix the bugs" will produce unpredictable results. "Fix the null pointer in UserService.getProfile when user.avatar is null — add a null check and return a default avatar URL" gives the agent exactly what it needs. + +### Ignoring Branch Conflicts + +If two agents modify the same file on different branches, you'll hit merge conflicts when merging. Plan your task allocation to minimize overlap. If tasks must touch the same files, run them sequentially. + +### Not Running Tests + +If the agent doesn't run tests, you're reviewing blind. Either include "run tests and fix any failures" in your prompt, or verify tests pass before reviewing the diff. + +--- + +## Getting Started + +1. **Pick an orchestrator** — [Superset](https://superset.sh) handles worktrees, sessions, and review +2. **Pick your agents** — Start with Claude Code or Codex, expand later +3. **Start with 2-3 tasks** — Parallelizable, non-overlapping tasks +4. **Review quickly** — Focus on diffs, not full file reads +5. **Scale gradually** — Add more agents as your review speed improves + +The goal isn't to run the most agents possible. It's to maximize useful throughput — tasks completed per hour that meet your quality bar. Parallel agents get you there faster than sequential work, but only if the orchestration and review workflow supports it. diff --git a/apps/marketing/content/blog/working-with-worktrees-in-superset.mdx b/apps/marketing/content/blog/working-with-worktrees-in-superset.mdx new file mode 100644 index 00000000000..bd13371432d --- /dev/null +++ b/apps/marketing/content/blog/working-with-worktrees-in-superset.mdx @@ -0,0 +1,172 @@ +--- +title: "Working with Git Worktrees in Superset" +description: "How Superset uses Git worktrees to run multiple AI coding agents in parallel without conflicts. A practical guide to the workflow that lets you 10x your throughput." +author: kiet +date: 2026-02-18 +category: Engineering +relatedSlugs: + - git-worktrees-history-deep-dive + - roadmap-to-100-agents +--- + +Running one AI coding agent is useful. Running ten at once is a different game entirely. But running ten agents in the same working directory is a disaster — they step on each other's files, create merge conflicts mid-edit, and leave your codebase in an unpredictable state. + +Superset solves this with Git worktrees. Every agent gets its own branch and its own copy of the working directory, all backed by the same Git object store. No duplication, no conflicts, no chaos. This post walks through how it works in practice. + +--- + +## Why Worktrees Matter for Agent Orchestration + +When you run a coding agent like Claude Code or Codex, the agent reads files, writes code, and runs commands. If two agents try to edit the same file simultaneously, you get corrupted state. If they share a staging area, commits get tangled. + +Git worktrees eliminate this problem at the filesystem level. Each worktree is a separate checkout with its own: + +- **Working directory** — files on disk that the agent can read and modify +- **Branch** — an isolated ref that tracks the agent's changes +- **Index** — a separate staging area for commits + +What's shared across all worktrees: + +- **Object store** — commits, trees, and blobs exist exactly once +- **Refs** — branches created in one worktree are visible in all others +- **Config** — repository settings, remotes, hooks + +This means creating a new worktree is fast (seconds, not minutes) and cheap (megabytes, not gigabytes). You're not cloning the repo — you're checking out another copy of the files while sharing the entire history. + +--- + +## The Superset Workflow + +Here's what happens when you create a new task in Superset: + +### 1. Create a Task + +You describe what you want done — "add input validation to the signup form" or "refactor the payment service to use the new API." Superset creates a new Git worktree and checks out a fresh branch. + +``` +~/my-project/ # Your main working tree +~/.superset/worktrees/my-project/ + └── add-signup-validation/ # Agent's isolated worktree + ├── .git # Points back to main repo + └── (full project checkout) +``` + +### 2. Agent Works in Isolation + +The agent runs inside its worktree. It can: + +- Read and write any file +- Install dependencies +- Run builds and tests +- Make commits to its branch + +Meanwhile, your main working directory is untouched. You can keep coding, run your dev server, or create more tasks — each in its own worktree. + +### 3. Review the Diff + +When the agent finishes, Superset shows you a diff of everything it changed. The built-in diff viewer highlights additions, deletions, and modifications across all files. You can also open the worktree in your editor (VS Code, Cursor, JetBrains, Xcode) to inspect changes in full context. + +### 4. Merge or Iterate + +If the changes look good, merge the branch. If not, give the agent feedback and let it iterate — still in its own worktree, still isolated from everything else. + +--- + +## Running Multiple Agents in Parallel + +The real power of worktrees shows up when you're running multiple agents simultaneously. Here's a typical session: + +``` +Task 1: "Write unit tests for the auth module" + → Branch: agent/auth-tests + → Status: Running (Claude Code) + +Task 2: "Refactor database queries to use prepared statements" + → Branch: agent/db-refactor + → Status: Running (Codex) + +Task 3: "Update API documentation for v2 endpoints" + → Branch: agent/api-docs + → Status: Complete — ready for review + +Task 4: "Fix the race condition in the websocket handler" + → Branch: agent/ws-fix + → Status: Running (Claude Code) +``` + +Each task has its own worktree and branch. Agent 1 can't accidentally break Agent 2's work. When Agent 3 finishes, you review its diff while the others keep working. No waiting, no conflicts, no context switching between stashes. + +### How Superset Manages Concurrency + +Superset's persistent daemon manages all agent sessions via Unix domain sockets. This architecture means: + +- **Sessions survive crashes** — close and reopen Superset, your agents are still running +- **Priority-based scheduling** — the focused pane gets full resources, background tabs hydrate gradually +- **No interference** — each agent's terminal session is completely independent + +--- + +## Practical Tips + +### Start Small, Scale Up + +Begin with 2-3 parallel agents to get comfortable with the review workflow. As you build confidence in reviewing diffs quickly, scale up. Most developers find a sweet spot around 5-7 concurrent agents before review becomes the bottleneck. + +### Choose the Right Agent for Each Task + +Different agents have different strengths. Superset is agent-agnostic — use whatever works best for the job: + +- **Claude Code** — strong at complex refactors, architectural changes, and multi-file edits +- **Codex** — fast for well-scoped tasks with clear specifications +- **Aider** — good for iterative changes with tight feedback loops +- **OpenCode** — flexible with 75+ model providers, great for cost optimization + +### Organize Your Tasks + +Give each task a clear, specific description. "Fix bugs" is too vague. "Fix the null pointer exception in UserService.getProfile when the user has no avatar" gives the agent enough context to work independently. + +### Review Diffs, Not Code + +When an agent finishes, don't re-read the entire file. Focus on the diff. Superset's built-in diff viewer shows exactly what changed. If a change touches files you didn't expect, that's worth investigating. If it's scoped to what you asked for, a quick review is usually sufficient. + +### Clean Up Finished Worktrees + +After merging, remove the worktree. Superset handles this automatically when you close a completed task, but it's good practice to keep your worktree list clean. Old worktrees don't affect performance, but they clutter the list. + +--- + +## Worktrees vs Other Isolation Methods + +Why worktrees instead of containers, VMs, or separate clones? + +| Method | Setup Time | Disk Cost | Shared History | Merge Workflow | +|---|---|---|---|---| +| **Git worktrees** | Seconds | Low (shared objects) | Yes | Native git merge | +| **Separate clones** | Minutes | High (full repo copy) | No (separate remotes) | Push/pull between repos | +| **Docker containers** | Minutes | Medium (image layers) | Depends on mount | Volume-based, complex | +| **VMs** | Minutes | High (full OS) | No | Network-based, slow | + +Worktrees win on every axis that matters for coding agents: they're fast to create, cheap on disk, share git history natively, and use standard git merging. The agent doesn't know or care that it's in a worktree — it just sees a normal git repository. + +--- + +## When Worktrees Aren't Enough + +Worktrees isolate files and branches, but they share the runtime environment. If two agents both need to run `npm install` with conflicting dependencies, they'll still conflict at the system level. For full environment isolation, you'd layer containers on top of worktrees — but for the vast majority of coding tasks, worktree-level isolation is sufficient and dramatically simpler. + +The other limitation is the one-branch rule: Git doesn't allow the same branch to be checked out in multiple worktrees simultaneously. This is actually a feature — it prevents the exact class of bugs that parallel work creates. Superset enforces unique branches per task by default. + +--- + +## Getting Started + +If you're already using a CLI coding agent, adding Superset takes about two minutes: + +1. **Download Superset** from [superset.sh](https://superset.sh) +2. **Open your project** — Superset detects your git repository automatically +3. **Create a task** — describe what you want done, pick your agent +4. **Watch it work** — the agent runs in its own worktree while you keep coding + +The first time you see three agents working in parallel — each on its own branch, none interfering with each other — the workflow clicks. It's not three times faster (review is still human-speed), but it's dramatically more throughput than running agents one at a time. + +Git worktrees have been in Git since 2015. They were designed for a world where humans needed to work on multiple branches. Turns out, they're even more useful in a world where AI agents do. diff --git a/apps/marketing/content/compare/best-ai-coding-agents-2026.mdx b/apps/marketing/content/compare/best-ai-coding-agents-2026.mdx new file mode 100644 index 00000000000..f56fbe83d94 --- /dev/null +++ b/apps/marketing/content/compare/best-ai-coding-agents-2026.mdx @@ -0,0 +1,191 @@ +--- +title: "Best AI Coding Tools and Agents (2026): Complete Comparison" +description: "Compare the top AI coding tools of 2026 — Superset, Cursor, Claude Code, Codex, Windsurf, Devin, GitHub Copilot, and more. Find the right tool for your workflow." +date: 2026-02-18 +lastUpdated: 2026-02-18 +type: "roundup" +competitors: + - cursor + - claude-code + - codex + - windsurf + - devin + - github-copilot + - opencode + - aider + - conductor +keywords: + - best ai coding tools + - best ai coding agents 2026 + - ai coding tool comparison + - cursor alternatives + - claude code alternatives + - codex alternatives + - ai pair programmer comparison + - ai agent orchestration +--- + +The AI coding landscape in 2026 has split into two categories: **agents** that write code and **orchestrators** that manage agents. This guide compares the major tools in both categories so you can build the right stack for your workflow. + +--- + +## The Two Categories + +### AI Coding Agents + +These tools talk to AI models, read your code, and make changes: + +- **Claude Code** — Anthropic's terminal agent, strong at complex multi-file refactors +- **Codex CLI** — OpenAI's open-source terminal agent with sandbox modes +- **GitHub Copilot** — Inline completions + chat + Agent mode in your editor +- **Cursor** — AI-native IDE (VS Code fork) with deep editor integration +- **Windsurf** — AI-powered IDE with Cascade agentic workflows +- **Devin** — Fully autonomous cloud-based AI software engineer +- **OpenCode** — Open-source terminal agent supporting 75+ model providers +- **Aider** — Open-source terminal agent focused on iterative pair programming + +### Agent Orchestrators + +These tools run and manage multiple agents: + +- **Superset** — Desktop terminal that runs 10+ agents in parallel via Git worktrees +- **Conductor** — macOS app for running Claude Code and Codex in parallel + +Most developers use one tool from each category. The agent does the coding; the orchestrator scales it. + +--- + +## Comparison Table + +| Tool | Type | Parallelism | Editor Required | Open Source | Pricing | +|---|---|---|---|---|---| +| **Superset** | Orchestrator | 10+ agents, Git worktrees | None (works with any) | Yes (Apache 2.0) | Free + Pro $20/seat/mo | +| **Cursor** | Agent (IDE) | Sequential (+ cloud Background Agents) | Cursor IDE | No | Free, Pro $20/mo, Ultra $200/mo | +| **Claude Code** | Agent (CLI) | Single session | None | Source-available | Max $20-200/mo or API usage | +| **Codex CLI** | Agent (CLI) | Single session (+ cloud Codex) | None | Yes (Apache 2.0) | Free + API usage | +| **GitHub Copilot** | Agent (extension) | Single thread (+ cloud Coding Agent) | VS Code, JetBrains, etc. | No | Free, Pro $10/mo, Business $19/user/mo | +| **Windsurf** | Agent (IDE) | Sequential (Cascade flows) | Windsurf IDE | No | Free, Pro $15/mo, Ultra $60/mo | +| **Devin** | Agent (cloud) | Multiple cloud VMs | None (web interface) | No | Teams $500/seat/mo | +| **OpenCode** | Agent (CLI) | Single session | None | Yes (MIT) | Free + API usage | +| **Aider** | Agent (CLI) | Single session | None | Yes (Apache 2.0) | Free + API usage | +| **Conductor** | Orchestrator | Multiple agents, Git worktrees | None | No | Free | + +--- + +## AI Coding Agents: Detailed Breakdown + +### Claude Code + +Anthropic's terminal-based coding agent. You describe a task, and Claude reads your codebase, writes code, runs commands, and creates commits. Strong at multi-file refactors, architectural changes, and complex debugging. Uses Claude models only (Sonnet, Opus, Haiku). Available via Anthropic Max subscription or pay-per-token API. + +**Best for:** Complex refactors, multi-file changes, architectural work + +### Codex CLI + +OpenAI's open-source terminal agent. Three operational modes: Suggest (proposes changes), Auto Edit (applies changes, asks before commands), and Full Auto (fully autonomous). Also available as a cloud service via ChatGPT that creates PRs from tasks. Uses OpenAI models (o3, o4-mini). + +**Best for:** Well-scoped tasks, autonomous execution in sandbox mode + +### GitHub Copilot + +The most widely adopted AI coding tool. Provides inline completions (ghost text as you type), a chat panel, and Agent mode for multi-file changes. Also offers a cloud-based Coding Agent that works from GitHub Issues. Supports multiple models (GPT-4o, Claude, Gemini). Integrated into VS Code, JetBrains, and Neovim. + +**Best for:** Inline completions, real-time editing assistance, teams already on GitHub + +### Cursor + +A VS Code fork with AI baked into every interaction: Tab completions, inline edits, chat, and Composer for multi-file changes. Also offers cloud-based Background Agents. Supports multiple models through Cursor's servers. Strong on single-task depth and editor UX. + +**Best for:** Developers who want AI deeply integrated into their VS Code workflow + +### Windsurf + +Another VS Code fork with AI integration. Cascade is its agentic feature — multi-step workflows that read, write, and execute code. Memories system learns your project patterns over time. More focused on workflow automation than raw completions. + +**Best for:** Multi-step agentic workflows within an IDE + +### Devin + +A fully autonomous AI software engineer from Cognition. Runs in cloud VMs with browser, editor, and terminal access. You assign tasks via chat or Slack and get PRs back. Event-driven workflows can trigger from Linear tickets, Slack messages, etc. The most autonomous option but also the most expensive. + +**Best for:** Fully autonomous task delegation, teams with budget for $500/seat/mo + +### OpenCode + +Open-source terminal agent from the SST team with 75+ model providers. Supports Anthropic, OpenAI, Google, AWS Bedrock, OpenRouter, and local models via Ollama. Includes LSP integration, MCP support, and a Bubble Tea TUI. The most flexible agent for model choice. + +**Best for:** Model flexibility, cost optimization across providers, open-source purists + +### Aider + +Open-source terminal agent focused on pair programming. Works with many models, supports git integration out of the box, and excels at iterative back-and-forth editing. Strong community and well-maintained documentation. + +**Best for:** Iterative pair programming, smaller focused changes + +--- + +## Agent Orchestrators: Detailed Breakdown + +### Superset + +Desktop terminal that runs any CLI-based coding agent in parallel across isolated Git worktrees. Each task gets its own branch and working directory — agents can't conflict with each other or your main work. Persistent daemon means sessions survive crashes. Integrates with VS Code, Cursor, JetBrains, and Xcode. Open source (Apache 2.0), zero telemetry. + +**Best for:** Running 5-10+ agents in parallel, agent-agnostic teams, privacy-conscious developers + +### Conductor + +macOS app from Melty Labs for running Claude Code and Codex in parallel with Git worktree isolation. Integrates with Linear and GitHub for issue-to-PR workflows. Closed source, free, Apple Silicon required. + +**Best for:** Claude Code-centric teams on Linear who want a visual dashboard + +--- + +## Recommended Stacks + +### The Parallel Powerhouse + +**Superset + Claude Code + Codex CLI** + +Run Claude Code for complex tasks and Codex for well-scoped ones, both orchestrated by Superset in parallel worktrees. Maximum throughput with agent flexibility. Add Copilot in your editor for inline completions. + +### The All-in-One Editor + +**Cursor or Windsurf** + +If you want everything in one app — completions, chat, agentic workflows — pick Cursor (more mature, larger community) or Windsurf (more workflow-focused). Trade-off: editor lock-in and sequential agent work. + +### The Budget Stack + +**Superset + OpenCode + Aider** + +All open source. Use OpenCode with cost-efficient models (local Ollama, AWS Bedrock) and Aider for iterative work. Superset orchestrates both in parallel. Total cost: API usage only. + +### The Autonomous Delegator + +**Devin + GitHub Copilot** + +Assign tasks to Devin and let it work autonomously while Copilot assists your own editing. Maximum delegation at premium price. + +--- + +## Frequently Asked Questions + +### Which AI coding tool is the best in 2026? + +There's no single "best" — it depends on your workflow. For parallel agent execution, Superset is the leading orchestrator. For single-agent depth, Claude Code and Cursor lead. For inline completions, GitHub Copilot is the standard. Most developers combine tools from different categories. + +### Can I use multiple AI coding tools together? + +Yes, and most teams do. A common stack is an orchestrator (Superset) + a primary agent (Claude Code or Codex) + inline completions (Copilot). These tools serve different purposes and don't conflict. + +### What's the difference between an AI coding agent and an AI coding orchestrator? + +An agent talks to AI models, reads your code, and makes changes. An orchestrator runs many agents in parallel with isolation and management. Think of it as the difference between a developer and a project manager — one does the work, the other coordinates many workers. + +### Is it worth paying for AI coding tools? + +The free tiers of most tools are sufficient for light usage. If you're using agents for multiple hours daily, paid plans and direct API access typically offer better throughput and reliability. At scale, the ROI is significant — AI agents can handle work that would take hours. + +### Which tool is most private? + +Superset and OpenCode are both open source and run locally with no telemetry. Codex CLI is open source but requires OpenAI API calls. Cursor, Windsurf, Devin, and Copilot all route code through external servers. diff --git a/apps/marketing/content/compare/superset-vs-claude-code.mdx b/apps/marketing/content/compare/superset-vs-claude-code.mdx new file mode 100644 index 00000000000..0adecbd59a3 --- /dev/null +++ b/apps/marketing/content/compare/superset-vs-claude-code.mdx @@ -0,0 +1,117 @@ +--- +title: "Superset vs Claude Code (2026): Agent Orchestrator vs AI Coding Agent" +description: "Compare Superset and Claude Code for AI-powered development. Superset orchestrates many Claude Code instances in parallel across isolated worktrees." +date: 2026-02-18 +lastUpdated: 2026-02-18 +type: "1v1" +competitors: + - claude-code +keywords: + - superset vs claude code + - claude code alternative + - claude code parallel agents + - claude code orchestration + - claude code worktrees + - ai coding agent comparison +--- + +Claude Code is Anthropic's terminal-based AI coding agent. Superset is an orchestration layer that runs multiple Claude Code instances in parallel, each in its own Git worktree. They're complementary — Superset doesn't replace Claude Code, it multiplies it. + +--- + +## At a Glance + +| | **Superset** | **Claude Code** | +|---|---|---| +| **Category** | Agent orchestration terminal | AI coding agent (terminal-native) | +| **What it does** | Runs 10+ coding agents in parallel with Git worktree isolation | AI assistant that reads, writes, and debugs code in your terminal | +| **AI approach** | Agent-agnostic — orchestrates Claude Code, Codex, Aider, OpenCode, or any CLI agent | Claude models only (Sonnet, Opus, Haiku) via Anthropic API | +| **Parallelism** | Core feature — many agents on separate branches simultaneously | Single session; requires separate terminal tabs for parallelism | +| **Isolation** | Automatic Git worktree per task — agents cannot conflict | Shares your working directory — manual worktree setup needed | +| **Pricing** | Free tier + Pro $20/seat/mo | Free tier (limited), Pro $20/mo via Anthropic Max or API usage | +| **Open source** | Yes (Apache 2.0) | Source-available (not open source) | + +--- + +## What Is Superset? + +Superset is a desktop terminal that orchestrates CLI-based coding agents — Claude Code, Codex, Aider, OpenCode — in parallel across isolated Git worktrees. Each agent gets its own branch and working directory. A persistent daemon manages sessions via Unix domain sockets, so they survive app restarts and crashes. Includes a built-in diff viewer and integrates with VS Code, Cursor, JetBrains, and Xcode. Open source (Apache 2.0) with zero telemetry. + +--- + +## What Is Claude Code? + +Claude Code is Anthropic's official CLI tool for AI-assisted coding. You run it in your terminal, describe what you want in natural language, and Claude reads your codebase, writes code, runs commands, creates commits, and even opens pull requests. It supports tool use, MCP servers, custom hooks, and deep codebase understanding through its context window. It uses Anthropic's Claude models exclusively. + +--- + +## Key Differences + +### Orchestrator vs Agent + +Claude Code is the agent — it talks to Claude models, reads your code, and makes changes. Superset is the orchestrator — it runs many Claude Code instances in parallel, each in its own isolated environment. This is the fundamental distinction: Claude Code does the work, Superset scales it. + +### Single Session vs Many Sessions + +With Claude Code alone, you work one task at a time in your terminal. You can open multiple tabs, but you have to manually set up isolation (separate directories, separate branches) and manage the overhead yourself. Superset automates this entirely: create a task, and it spins up a worktree, creates a branch, and launches Claude Code inside it. + +### Automatic Isolation + +Running Claude Code directly, it modifies files in your current directory. If you start two Claude Code instances in the same directory, they'll overwrite each other's changes. Superset creates a separate Git worktree per task, giving each Claude Code instance an isolated copy of the repository. This is what makes running 10+ agents at once safe. + +### Agent Flexibility + +Claude Code only works with Anthropic's models. Superset doesn't care which agent you use — run Claude Code for complex refactors, Codex for well-defined tasks, Aider for iterative changes, or mix and match per task. If a better agent ships tomorrow, you can use it in Superset immediately without changing your workflow. + +### Session Persistence + +If your terminal crashes while Claude Code is running, you lose the session. Superset's daemon architecture means agent sessions persist across crashes and app restarts. Close your laptop, open it tomorrow, and your agents are still running. + +--- + +## Pricing + +Superset offers a free tier and Pro at $20/seat/month. Claude Code is available through Anthropic Max ($20/mo for limited usage, $100/mo or $200/mo for higher limits) or pay-per-token via Anthropic's API. When using Claude Code inside Superset, you pay Superset's plan plus your Anthropic API usage — no markup, no credit system. + +--- + +## Which Should You Choose? + +**Choose Claude Code alone if you:** +- Work on one task at a time with real-time AI collaboration +- Prefer a single-agent workflow with deep context +- Don't need to run multiple agents in parallel +- Want the simplest possible setup (just install and run) + +**Choose Superset + Claude Code if you:** +- Want to run 5-10+ Claude Code instances in parallel across separate tasks +- Need automatic Git worktree isolation so agents never conflict +- Want sessions that survive crashes and app restarts +- Plan to use other agents alongside Claude Code (Codex, Aider, OpenCode) +- Work on large codebases where parallel execution saves hours + +Most Superset users run Claude Code as their primary agent. Superset doesn't compete with Claude Code — it makes Claude Code more powerful by adding parallelism, isolation, and persistence. + +--- + +## Frequently Asked Questions + +### Is Superset a Claude Code replacement? + +No. Superset does not talk to AI models or write code. It orchestrates agents like Claude Code in parallel, each in its own Git worktree. Think of it as a multiplier for Claude Code, not a substitute. + +### Can I use Claude Code without Superset? + +Yes. Claude Code works perfectly in any terminal. Superset adds value when you want to run multiple instances in parallel with automatic isolation — which becomes important as you scale from one agent to many. + +### How many Claude Code instances can I run in Superset? + +As many as your machine and API rate limits allow. Most developers run 5-10 concurrent agents. Superset's daemon handles concurrency, and its priority-based scheduling ensures the focused task gets full resources. + +### Does Superset modify how Claude Code works? + +No. Claude Code runs exactly as it would in any terminal. Superset just provides the worktree, branch, and terminal session. All Claude Code features — tool use, MCP servers, hooks, slash commands — work normally. + +### Is Superset open source? + +Yes. Superset is open source under Apache 2.0 with zero telemetry. The full codebase is on GitHub. Claude Code is source-available but not open source. diff --git a/apps/marketing/content/compare/superset-vs-codex.mdx b/apps/marketing/content/compare/superset-vs-codex.mdx new file mode 100644 index 00000000000..20d262357ad --- /dev/null +++ b/apps/marketing/content/compare/superset-vs-codex.mdx @@ -0,0 +1,113 @@ +--- +title: "Superset vs Codex CLI (2026): Agent Orchestrator vs OpenAI's Coding Agent" +description: "Compare Superset and OpenAI Codex CLI for AI-powered development. See how parallel agent orchestration differs from a single cloud-backed coding agent." +date: 2026-02-18 +lastUpdated: 2026-02-18 +type: "1v1" +competitors: + - codex +keywords: + - superset vs codex + - codex alternative + - codex cli alternative + - openai codex alternative + - codex parallel agents + - ai coding agent comparison +--- + +Codex CLI is OpenAI's terminal-based coding agent. Superset is an orchestration layer that runs multiple Codex instances (and other agents) in parallel, each in its own Git worktree. They solve different problems: Codex does the coding, Superset scales it horizontally. + +--- + +## At a Glance + +| | **Superset** | **Codex CLI** | +|---|---|---| +| **Category** | Agent orchestration terminal | AI coding agent (terminal-native) | +| **What it does** | Runs 10+ coding agents in parallel with Git worktree isolation | AI assistant that reads, writes, and executes code via OpenAI models | +| **AI approach** | Agent-agnostic — works with Codex, Claude Code, Aider, OpenCode, etc. | OpenAI models only (o3, o4-mini, GPT-4.1) | +| **Parallelism** | Core feature — many agents on separate branches simultaneously | Single session; cloud Codex runs tasks remotely | +| **Isolation** | Automatic Git worktree per task | Sandbox modes (network-disabled, full-auto) per session | +| **Pricing** | Free tier + Pro $20/seat/mo | Free and open source (Apache 2.0); pay for OpenAI API usage | +| **Open source** | Yes (Apache 2.0) | Yes (Apache 2.0) | + +--- + +## What Is Superset? + +Superset is a desktop terminal that orchestrates CLI-based coding agents in parallel across isolated Git worktrees. Each agent — Codex, Claude Code, Aider, OpenCode, or any CLI process — gets its own branch and working directory. A persistent daemon manages sessions so they survive app restarts and crashes. Includes a built-in diff viewer and integrates with VS Code, Cursor, JetBrains, and Xcode. Open source (Apache 2.0) with zero telemetry. + +--- + +## What Is Codex CLI? + +Codex CLI is OpenAI's open-source terminal agent for software engineering. It runs locally, understands your codebase through file reading and command execution, and can write code, fix bugs, and refactor across files. It offers three operational modes: Suggest (proposes changes for approval), Auto Edit (applies file changes, asks before commands), and Full Auto (executes everything autonomously). It uses OpenAI's models, primarily codex-1 for cloud tasks and o3/o4-mini for local sessions. + +--- + +## Key Differences + +### Orchestrator vs Agent + +Codex CLI is the agent — it reads code, talks to OpenAI models, and writes changes. Superset is the orchestrator — it runs many Codex instances in parallel, each in its own isolated environment. Run Codex inside Superset to get automatic worktree isolation and parallel execution with zero manual setup. + +### Local vs Cloud + +Codex CLI runs locally by default but also offers cloud-based Codex (via the Codex dashboard) for heavier tasks. Cloud Codex runs in a sandboxed VM, creates branches, and produces pull requests. Superset is entirely local — all agents run on your machine in Git worktrees. No code leaves your environment unless the agent's API calls send it. + +### Single Agent vs Many Agents + +With Codex CLI alone, you work one task at a time: prompt, review, iterate. With Superset, you assign tasks to multiple Codex instances simultaneously — one writing tests, another refactoring a service, a third fixing lint errors — each on its own branch with its own worktree. + +### Agent Flexibility + +Codex CLI only works with OpenAI's models. Superset doesn't care which agent you use — run Codex for tasks where OpenAI models excel, Claude Code for complex architectural work, and Aider for iterative changes. Mix and match per task based on what works best. + +### Session Persistence + +Codex CLI sessions end when the terminal closes. Superset's persistent daemon keeps sessions alive across crashes and restarts. Start a long-running Codex task, close your laptop, and it's still running when you come back. + +--- + +## Pricing + +Superset offers a free tier and Pro at $20/seat/month. Codex CLI is free and open source — you pay for OpenAI API usage only. Cloud Codex is included in ChatGPT Pro ($200/mo) and Plus ($20/mo with limited tasks). When using Codex CLI inside Superset, you pay Superset's plan plus OpenAI API costs — no markup. + +--- + +## Which Should You Choose? + +**Choose Codex CLI alone if you:** +- Work on one task at a time and prefer a simple terminal workflow +- Want OpenAI's models (o3, o4-mini) for coding tasks +- Prefer Full Auto mode for autonomous execution in a sandboxed environment +- Need cloud-based Codex for heavy tasks that benefit from remote compute + +**Choose Superset + Codex CLI if you:** +- Want to run 5-10+ Codex instances in parallel across separate tasks +- Need automatic Git worktree isolation so agents never conflict +- Want sessions that survive crashes and app restarts +- Plan to mix Codex with other agents (Claude Code, Aider, OpenCode) per task +- Work on large codebases where parallel execution saves hours + +Superset and Codex CLI work together naturally. Each Superset task launches Codex in its own worktree — you get Codex's coding ability with Superset's parallelism and isolation. + +--- + +## Frequently Asked Questions + +### Is Superset a Codex replacement? + +No. Superset does not talk to AI models or write code. It orchestrates agents like Codex in parallel, each in its own Git worktree. Think of Superset as a multiplier for Codex, not a substitute. + +### Can I run Codex in Full Auto mode inside Superset? + +Yes. Each Superset task runs Codex in its own isolated worktree. You can use any Codex mode — Suggest, Auto Edit, or Full Auto — safely, because worktree isolation means an autonomous agent can't affect your main working directory. + +### How does cloud Codex compare to Superset? + +Cloud Codex runs in OpenAI's VMs and produces pull requests. Superset runs agents locally in Git worktrees. Cloud Codex offloads compute but sends code to OpenAI's servers. Superset keeps everything local with zero telemetry. They serve different trust and infrastructure models. + +### Are both tools open source? + +Yes. Both Superset and Codex CLI are open source under Apache 2.0. You can inspect, modify, and self-host either. diff --git a/apps/marketing/content/compare/superset-vs-devin.mdx b/apps/marketing/content/compare/superset-vs-devin.mdx new file mode 100644 index 00000000000..298744cbf63 --- /dev/null +++ b/apps/marketing/content/compare/superset-vs-devin.mdx @@ -0,0 +1,104 @@ +--- +title: "Superset vs Devin (2026): Local Agent Orchestration vs Cloud AI Engineer" +description: "Compare Superset and Devin for AI-powered development. See how local parallel agent orchestration differs from a fully remote AI software engineer." +date: 2026-02-18 +lastUpdated: 2026-02-18 +type: "1v1" +competitors: + - devin +keywords: + - superset vs devin + - devin alternative + - devin vs superset + - ai software engineer comparison + - ai coding agent comparison +--- + +Devin is a cloud-based AI software engineer that works autonomously in a remote VM. Superset is a desktop terminal that orchestrates local coding agents in parallel across Git worktrees. They represent opposite ends of the AI development spectrum: Devin offloads work to the cloud, Superset keeps everything local. + +--- + +## At a Glance + +| | **Superset** | **Devin** | +|---|---|---| +| **Category** | Agent orchestration terminal | Autonomous AI software engineer | +| **Architecture** | Fully local — agents run on your machine | Fully remote — runs in cloud VMs | +| **AI approach** | Agent-agnostic — orchestrates any CLI agent | Proprietary AI with browser, editor, and terminal in cloud | +| **Parallelism** | 10+ agents across isolated local worktrees | Multiple Devin sessions run as separate cloud VMs | +| **Code privacy** | Code never leaves your machine | Code runs on Cognition's cloud infrastructure | +| **Pricing** | Free tier + Pro $20/seat/mo | Teams $500/seat/mo | +| **Open source** | Yes (Apache 2.0) | No (closed source) | + +--- + +## What Is Superset? + +Superset is a desktop terminal that orchestrates CLI-based coding agents in parallel across isolated Git worktrees. Each agent — Claude Code, Codex, Aider, OpenCode — gets its own branch and working directory. A persistent daemon manages sessions so they survive crashes. Includes a built-in diff viewer and integrates with VS Code, Cursor, JetBrains, and Xcode. Open source (Apache 2.0) with zero telemetry. + +--- + +## What Is Devin? + +Devin is Cognition's AI software engineer — a cloud-based autonomous agent that runs in its own virtual machine with a browser, code editor, terminal, and planner. You assign tasks via chat or Slack, and Devin works independently: reading docs, writing code, debugging, running tests, and creating pull requests. It has event-driven workflows (triggers from Linear, Slack, etc.) and a review system that annotates PRs before human review. + +--- + +## Key Differences + +### Local vs Cloud + +Superset runs everything locally. Your code stays on your machine, agents use your local git repos, and nothing is sent to external servers beyond what the agents' own API calls require. Devin runs entirely in Cognition's cloud — your code is cloned into remote VMs where Devin operates. This is the fundamental architectural difference and drives most of the trade-offs below. + +### Control vs Autonomy + +Superset gives you direct terminal access to each agent. You see what it's doing in real time, can interrupt, redirect, or provide feedback mid-task. Devin aims for full autonomy — you assign a task and check back later for a PR. This makes Devin more hands-off but less controllable when it goes in the wrong direction. + +### Agent Flexibility + +Devin is a single proprietary agent — you use Cognition's AI or nothing. Superset is agent-agnostic: run Claude Code for complex refactors, Codex for well-scoped tasks, Aider for iterative work. When a better agent ships, use it in Superset immediately. With Devin, you wait for Cognition to improve their model. + +### Isolation Mechanism + +Superset isolates agents using Git worktrees — lightweight, fast, and built into git itself. Devin isolates each session in a full cloud VM with its own OS, browser, and toolchain. VMs provide stronger isolation (separate environments) but at much higher cost and latency. + +### Pricing + +Superset offers a free tier and Pro at $20/seat/month plus your agents' API costs. Devin costs $500/seat/month for the Teams plan. The price difference is significant — Superset plus API usage for heavy agent use typically costs a fraction of Devin's monthly fee. + +--- + +## Which Should You Choose? + +**Choose Devin if you:** +- Want a fully autonomous AI that works in the background with minimal oversight +- Need event-driven workflows (auto-respond to Linear tickets, Slack messages) +- Prefer cloud-based execution where you don't manage local compute +- Have budget for $500/seat/month and the ROI justifies it + +**Choose Superset if you:** +- Want direct control over each agent — see what they're doing, redirect in real time +- Need code to stay local with zero telemetry +- Want agent flexibility (Claude Code, Codex, Aider, OpenCode — your choice per task) +- Prefer the cost efficiency of local execution with direct API pricing +- Need an open-source tool you can inspect and modify + +--- + +## Frequently Asked Questions + +### Can Devin and Superset work together? + +They serve different workflows. Devin is a cloud-based autonomous engineer. Superset is a local agent orchestrator. You might use Devin for fully autonomous background tasks and Superset for interactive parallel work where you want more control. + +### Is Devin worth the price premium? + +Devin's $500/seat/month buys full autonomy: assign tasks via Slack, get PRs back. If your workflow benefits from hands-off delegation and you have the budget, it can be valuable. If you prefer direct control and cost efficiency, Superset at $20/seat/month plus API costs delivers more throughput per dollar. + +### Is Superset open source? + +Yes. Superset is open source under Apache 2.0 with zero telemetry. Devin is closed source from Cognition. + +### Which is better for security-sensitive codebases? + +Superset. Code never leaves your machine. Devin runs code on Cognition's cloud infrastructure. For regulated industries, government work, or sensitive IP, local execution is a hard requirement. diff --git a/apps/marketing/content/compare/superset-vs-github-copilot.mdx b/apps/marketing/content/compare/superset-vs-github-copilot.mdx new file mode 100644 index 00000000000..2a471dd7f47 --- /dev/null +++ b/apps/marketing/content/compare/superset-vs-github-copilot.mdx @@ -0,0 +1,113 @@ +--- +title: "Superset vs GitHub Copilot (2026): Agent Orchestration vs AI Pair Programmer" +description: "Compare Superset and GitHub Copilot for AI-assisted development. See how parallel agent orchestration differs from inline AI code completion and chat." +date: 2026-02-18 +lastUpdated: 2026-02-18 +type: "1v1" +competitors: + - github-copilot +keywords: + - superset vs github copilot + - github copilot alternative + - copilot alternative + - copilot vs superset + - ai coding assistant comparison + - ai pair programmer comparison +--- + +GitHub Copilot is an AI pair programmer that lives inside your editor, offering inline completions and chat. Superset is a terminal that runs many AI coding agents in parallel, each in its own Git worktree. They target different workflows: Copilot assists you line-by-line as you type, Superset dispatches autonomous agents to work on entire tasks independently. + +--- + +## At a Glance + +| | **Superset** | **GitHub Copilot** | +|---|---|---| +| **Category** | Agent orchestration terminal | AI pair programmer (editor extension) | +| **What it does** | Runs 10+ coding agents in parallel with Git worktree isolation | Inline code completions, chat, and Copilot Agent mode in your editor | +| **AI approach** | Agent-agnostic — orchestrates any CLI agent | Multiple models (GPT-4o, Claude, Gemini) via GitHub | +| **Parallelism** | Core feature — many agents on separate branches simultaneously | Single-threaded; Copilot Coding Agent runs one task at a time in cloud | +| **Editor** | Works alongside any editor | VS Code, JetBrains, Neovim (extension) | +| **Pricing** | Free tier + Pro $20/seat/mo | Free tier (limited), Pro $10/mo, Business $19/user/mo, Enterprise $39/user/mo | +| **Open source** | Yes (Apache 2.0) | No (closed source) | + +--- + +## What Is Superset? + +Superset is a desktop terminal that orchestrates CLI-based coding agents in parallel across isolated Git worktrees. Each agent — Claude Code, Codex, Aider, OpenCode — gets its own branch and working directory. A persistent daemon manages sessions so they survive crashes. Includes a built-in diff viewer and integrates with VS Code, Cursor, JetBrains, and Xcode. Open source (Apache 2.0) with zero telemetry. + +--- + +## What Is GitHub Copilot? + +GitHub Copilot is an AI coding assistant from GitHub (Microsoft). It integrates into your editor as an extension, providing inline code completions (ghost text as you type), a chat panel for questions and code generation, and Copilot Agent mode that can make multi-file changes autonomously. Copilot also offers a cloud-based Coding Agent that creates PRs from GitHub Issues. It uses multiple models including GPT-4o, Claude Sonnet, and Gemini, accessible through GitHub's infrastructure. + +--- + +## Key Differences + +### Inline Assistant vs Parallel Orchestrator + +Copilot is built for the editing experience — it completes your code as you type, answers questions in a chat panel, and can make changes across files via Agent mode. Superset runs many autonomous agents simultaneously, each on a separate task in a separate worktree. Copilot makes you faster at writing code; Superset makes many agents work in parallel while you do something else. + +### Completions vs Autonomous Tasks + +Copilot's primary interaction is inline completion: you type, it suggests. Its Agent mode and Coding Agent can handle larger tasks, but the core experience is real-time assistance while you code. Superset dispatches fully autonomous tasks — "refactor the payment service," "add tests for the auth module" — and agents work independently until done. + +### Editor Integration vs Editor Independence + +Copilot lives inside your editor (VS Code, JetBrains, Neovim). Superset is a separate terminal that works alongside any editor. This means Copilot can assist with editing-specific features (completions, inline diffs), while Superset focuses on orchestration and isolation without caring which editor you use. + +### Model and Agent Flexibility + +Copilot supports multiple models (GPT-4o, Claude, Gemini) through GitHub's infrastructure. Superset supports any CLI-based agent — and by extension, whatever models those agents support. The difference is direct vs proxied: with Superset, you bring your own API keys and pay providers directly. With Copilot, you use GitHub's model access through their pricing tiers. + +### Privacy + +Superset runs entirely locally — no telemetry, code stays on your machine. Copilot sends code context to GitHub/Microsoft servers for processing. Copilot Business and Enterprise offer data retention controls, but code still transits external servers. Superset's open-source codebase is fully auditable. + +--- + +## Pricing + +Superset offers a free tier and Pro at $20/seat/month, plus your agents' API costs. GitHub Copilot offers Free (limited), Pro ($10/mo or $100/year), Business ($19/user/mo), and Enterprise ($39/user/mo). Copilot's pricing includes model access; Superset's doesn't (you pay agents' API costs separately). + +--- + +## Which Should You Choose? + +**Choose GitHub Copilot if you:** +- Want real-time inline code completions as you type +- Prefer AI assistance integrated directly into your editor +- Work primarily in VS Code or JetBrains +- Want a simple, low-cost AI assistant ($10/mo) that improves your editing speed + +**Choose Superset if you:** +- Run CLI-based coding agents and want to parallelize across 10+ tasks +- Need autonomous agents working on separate tasks while you do other work +- Want agent and model flexibility with no vendor lock-in +- Need code to stay local with zero telemetry +- Work on large codebases where parallel execution saves hours + +**Use both** for the best of each: Copilot for inline completions while you code, Superset to dispatch parallel agents for larger tasks. They don't overlap — Copilot helps you write code faster, Superset helps you scale agent work wider. + +--- + +## Frequently Asked Questions + +### Is Superset a Copilot replacement? + +No. Superset does not provide inline completions, code suggestions, or editor integration. It orchestrates autonomous coding agents in parallel. Use Copilot for real-time editing assistance and Superset for parallel autonomous tasks. + +### How does Copilot's Coding Agent compare to Superset? + +Copilot's Coding Agent runs in a cloud VM and creates PRs from GitHub Issues — one task at a time per repository. Superset runs many agents locally in parallel across Git worktrees. Copilot's agent is cloud-hosted and GitHub-integrated; Superset's approach is local, agent-agnostic, and parallel. + +### Can I use Copilot inside a Superset worktree? + +Yes. When you open a Superset worktree in VS Code, Copilot works normally — it sees the worktree as a regular git repository. You get Copilot's completions while reviewing or editing agent output. + +### Is Superset open source? + +Yes. Superset is open source under Apache 2.0 with zero telemetry. GitHub Copilot is closed source. diff --git a/apps/marketing/content/compare/superset-vs-windsurf.mdx b/apps/marketing/content/compare/superset-vs-windsurf.mdx new file mode 100644 index 00000000000..1eabdbf9a76 --- /dev/null +++ b/apps/marketing/content/compare/superset-vs-windsurf.mdx @@ -0,0 +1,112 @@ +--- +title: "Superset vs Windsurf (2026): Parallel Agent Orchestration vs AI IDE" +description: "Compare Superset and Windsurf for AI-assisted development. See how parallel agent orchestration differs from an AI-powered integrated development environment." +date: 2026-02-18 +lastUpdated: 2026-02-18 +type: "1v1" +competitors: + - windsurf +keywords: + - superset vs windsurf + - windsurf alternative + - windsurf vs superset + - ai ide comparison + - ai coding tool comparison +--- + +Windsurf is an AI-powered IDE that embeds AI into every part of the editing experience. Superset is a terminal that runs many AI coding agents in parallel, each in its own Git worktree. They solve fundamentally different problems: Windsurf replaces your editor with an AI-native one, Superset scales autonomous agent work alongside any editor. + +--- + +## At a Glance + +| | **Superset** | **Windsurf** | +|---|---|---| +| **Category** | Agent orchestration terminal | AI-powered IDE (VS Code fork) | +| **AI approach** | Agent-agnostic — works with Claude Code, Codex, Aider, or any CLI agent | Built-in AI models proxied through Windsurf servers | +| **Parallelism** | Core feature — 10+ agents across isolated worktrees | Sequential by default; Windsurf Flows handles multi-step tasks | +| **Editor** | Works alongside any editor (VS Code, Cursor, JetBrains, Xcode) | You must use the Windsurf IDE | +| **Pricing** | Free tier + Pro $20/seat/mo | Free tier (limited), Pro $15/mo, Ultra $60/mo, Teams $35/seat/mo | +| **Privacy** | Fully local — no telemetry, code never leaves your machine | Code sent to Windsurf servers and third-party AI providers | +| **Open source** | Yes (Apache 2.0) | No (closed source) | + +--- + +## What Is Superset? + +Superset is a desktop terminal that orchestrates CLI-based coding agents in parallel across isolated Git worktrees. Each agent — Claude Code, Codex, Aider, OpenCode — gets its own branch and working directory. A persistent daemon manages sessions so they survive crashes. Includes a built-in diff viewer and integrates with VS Code, Cursor, JetBrains, and Xcode. Open source (Apache 2.0) with zero telemetry. + +--- + +## What Is Windsurf? + +Windsurf (from Codeium) is a VS Code fork with AI integrated throughout the editing experience. Its core feature is Cascade, an agentic workflow engine that can read files, write code, run terminal commands, and search your codebase in multi-step flows. It also offers Tab completions, inline chat, and a Memories system that learns your project's patterns over time. Windsurf routes requests through its servers to provide access to multiple AI models. + +--- + +## Key Differences + +### Single Agent vs Many Agents + +Windsurf's Cascade is a single agentic flow — it tackles one task at a time through multiple steps (reading code, writing changes, running commands). Superset runs many agents simultaneously in isolated worktrees: one writing tests, another refactoring a service, a third updating docs. Windsurf improves single-task depth; Superset adds multi-task breadth. + +### Editor Lock-In vs Editor Freedom + +Using Windsurf means adopting the Windsurf IDE. If you use JetBrains, Xcode, Neovim, or even Cursor, you have to switch. Superset runs alongside any editor — it's a terminal, not an IDE. Use VS Code today, switch to JetBrains tomorrow, nothing changes in your Superset workflow. + +### Model Lock-In vs Model Freedom + +Windsurf routes all AI requests through its servers and credit system. You get access to multiple models (GPT-4, Claude, etc.) but Windsurf controls the routing and pricing. Superset runs whatever CLI agents you install — your API keys, your models, no middleman. When a new agent ships, use it immediately. + +### Privacy + +Superset runs entirely locally — no telemetry, no data collection, code never leaves your machine. The full source is on GitHub under Apache 2.0. Windsurf sends code to its servers and third-party AI providers. Windsurf is closed source, so you cannot audit what data is collected or how it's processed. + +### Session Persistence + +Windsurf's Cascade sessions live within the IDE — close the window and the context resets. Superset's persistent daemon keeps agent sessions alive across crashes and app restarts. Long-running tasks continue even when you close and reopen the app. + +--- + +## Pricing + +Superset offers a free tier and Pro at $20/seat/month. You also pay your agents' API providers directly — no markup, no credit system. Windsurf offers a free tier, Pro at $15/month, Ultra at $60/month, and Teams at $35/seat/month, all using a credit-based system for AI requests. + +--- + +## Which Should You Choose? + +**Choose Windsurf if you:** +- Want AI deeply embedded in your editing experience (completions, inline chat, multi-step flows) +- Primarily use VS Code and are comfortable switching to a fork +- Prefer a single integrated tool that handles editing and AI in one app +- Don't need to run multiple agents in parallel + +**Choose Superset if you:** +- Run CLI-based coding agents and want to parallelize across 10+ tasks +- Use JetBrains, Xcode, Neovim, or any non-VS Code editor +- Need code to stay on your machine with no telemetry +- Want agent and model flexibility with no vendor lock-in +- Need sessions that survive crashes and app restarts + +Both tools can coexist. Use Windsurf as your editor for inline AI assistance, and Superset alongside it to dispatch parallel agents for larger tasks like test generation, refactors, and migrations. + +--- + +## Frequently Asked Questions + +### Is Superset a Windsurf replacement? + +No. Superset provides no inline completions, syntax highlighting, or file editing. It is a terminal for orchestrating AI coding agents in parallel. Superset and Windsurf serve different functions and can be used together. + +### Does Windsurf support parallel agents? + +Windsurf's Cascade handles multi-step tasks sequentially within a single flow. It does not run multiple independent agents in parallel across isolated environments. Superset's worktree-based isolation is specifically designed for parallel agent execution. + +### Is Superset open source? + +Yes. Superset is open source under Apache 2.0 with zero telemetry. Windsurf is closed source from Codeium. + +### Can I use Windsurf as my editor with Superset? + +Yes. Superset integrates with any editor. You can open Superset worktrees in Windsurf to review agent changes in the full IDE context. diff --git a/apps/marketing/src/app/blog/[slug]/page.tsx b/apps/marketing/src/app/blog/[slug]/page.tsx index 4e8fd8b0e4e..ab50b72d9d6 100644 --- a/apps/marketing/src/app/blog/[slug]/page.tsx +++ b/apps/marketing/src/app/blog/[slug]/page.tsx @@ -2,7 +2,11 @@ import { COMPANY } from "@superset/shared/constants"; import type { Metadata } from "next"; import { notFound } from "next/navigation"; import { MDXRemote } from "next-mdx-remote/rsc"; -import { ArticleJsonLd, BreadcrumbJsonLd } from "@/components/JsonLd"; +import { + ArticleJsonLd, + BreadcrumbJsonLd, + FAQPageJsonLd, +} from "@/components/JsonLd"; import { extractToc, getAllSlugs, @@ -65,6 +69,7 @@ export default async function BlogPostPage({ params }: PageProps) { { name: post.title, url }, ]} /> + {post.faq && post.faq.length > 0 && } @@ -91,6 +96,8 @@ export async function generateMetadata({ return { title: post.title, description: post.description, + ...(post.keywords && + post.keywords.length > 0 && { keywords: post.keywords }), alternates: { canonical: url, }, diff --git a/apps/marketing/src/app/compare/page.tsx b/apps/marketing/src/app/compare/page.tsx new file mode 100644 index 00000000000..2cecf180c92 --- /dev/null +++ b/apps/marketing/src/app/compare/page.tsx @@ -0,0 +1,129 @@ +import type { Metadata } from "next"; +import Link from "next/link"; +import { GridCross } from "@/app/blog/components/GridCross"; +import { getComparisonPages } from "@/lib/compare"; +import { formatCompareDate } from "@/lib/compare-utils"; + +export const metadata: Metadata = { + title: "Compare Superset | AI Coding Tool Comparisons", + description: + "Compare Superset with Cursor, Claude Code, Codex, Windsurf, Devin, GitHub Copilot, and more. See how parallel agent orchestration stacks up against other AI coding tools.", + alternates: { + canonical: "/compare", + }, + openGraph: { + title: "Compare Superset | AI Coding Tool Comparisons", + description: + "Compare Superset with Cursor, Claude Code, Codex, Windsurf, Devin, GitHub Copilot, and more.", + url: "/compare", + images: ["/opengraph-image"], + }, + twitter: { + card: "summary_large_image", + title: "Compare Superset | AI Coding Tool Comparisons", + description: + "Compare Superset with Cursor, Claude Code, Codex, Windsurf, Devin, GitHub Copilot, and more.", + images: ["/opengraph-image"], + }, +}; + +export default async function ComparePage() { + const pages = getComparisonPages(); + + const oneVsOne = pages.filter((p) => p.type === "1v1"); + const roundups = pages.filter((p) => p.type === "roundup"); + + return ( +
+ {/* Vertical guide lines */} +
+ + {/* Header section */} +
+
+ + + + + Compare + +

+ Superset vs the Alternatives +

+

+ See how Superset compares to other AI coding tools — from AI editors + to coding agents to cloud-based AI engineers. +

+ + + +
+
+ + {/* Content */} +
+ {roundups.length > 0 && ( +
+

+ Roundups +

+
+ {roundups.map((page) => ( + + ))} +
+
+ )} + + {oneVsOne.length > 0 && ( +
+

+ Head-to-Head Comparisons +

+
+ {oneVsOne.map((page) => ( + + ))} +
+
+ )} + + {pages.length === 0 && ( +

No comparisons yet.

+ )} +
+
+ ); +} + +function CompareCard({ + page, +}: { + page: ReturnType[number]; +}) { + return ( + +

+ {page.title} +

+ {page.description && ( +

+ {page.description} +

+ )} + + Updated {formatCompareDate(page.lastUpdated || page.date)} + + + ); +} diff --git a/apps/marketing/src/app/llms-full.txt/route.ts b/apps/marketing/src/app/llms-full.txt/route.ts new file mode 100644 index 00000000000..b3c42d6f950 --- /dev/null +++ b/apps/marketing/src/app/llms-full.txt/route.ts @@ -0,0 +1,111 @@ +import { COMPANY } from "@superset/shared/constants"; +import { getBlogPosts } from "@/lib/blog"; +import { getComparisonPages } from "@/lib/compare"; +import { FAQ_ITEMS } from "../components/FAQSection/constants"; + +function stripMdxSyntax(content: string): string { + return ( + content + // Remove import statements + .replace(/^import\s+.*$/gm, "") + // Remove JSX component tags (e.g.