Sourcegraph Amp vs Cosine Genie

Detailed side-by-side comparison to help you choose the right tool

Sourcegraph Amp

🔴Developer

AI Coding

Sourcegraph Amp is Sourcegraph's frontier-model coding agent built for monorepos, with live access to the Sourcegraph code graph and MCP support.

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Starting Price

Custom

Cosine Genie

🔴Developer

AI Coding

Autonomous AI software engineer trained on real engineering trajectories — "the copilot era is over."

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Starting Price

Custom

Feature Comparison

Scroll horizontally to compare details.

FeatureSourcegraph AmpCosine Genie
CategoryAI CodingAI Coding
Pricing Plans98 tiers6 tiers
Starting Price
Key Features
  • Frontier-model agent grounded in Sourcegraph's code graph
  • Monorepo-scale code intelligence: references, call sites, dependencies
  • Shared threads between VS Code and CLI

    Sourcegraph Amp - Pros & Cons

    Pros

    • Monorepo code-graph grounding beats embedding-only competitors on large repos.
    • Pass-through token pricing rewards heavy use instead of capping it.
    • Shared threads across VS Code and CLI match how senior engineers actually work.

    Cons

    • No managed model — you bring API keys, which is friction for team buyers.
    • VS Code extension is newer and less polished than the established Cody extension.
    • CLI is powerful but documentation still lags the product roadmap.

    Cosine Genie - Pros & Cons

    Pros

    • Genuine async workflow — file a ticket, get a PR, review in your normal flow
    • On-prem option clears regulated-environment procurement
    • Lumen models tuned for engineering tasks, not generic chat
    • Slack/issue-tracker triggers make integration with existing workflows easy
    • Strong SWE-bench Verified credibility from launch onward

    Cons

    • Team-tier pricing is steep relative to in-editor copilots
    • Like all autonomous agents, quality drops on ambiguous tickets or messy codebases
    • Younger / smaller vendor than GitHub or Cursor — vendor risk for the cautious
    • Sandboxed-cloud per-task model can make latency unpredictable
    • Best gains require teams to invest in clearer ticket hygiene

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