For developers building GTM tools and automations, Amp is a coding agent that writes and edits code through a CLI and TypeScript SDK, with agents running on your own machines or independently in parallel on its remote computers.
Presence & Market Position
#20 of 26
Coding Agents & Harnesses for GTM
Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →
Amp, Sourcegraph's agentic coding tool, positions itself around the economics of running agents rather than the agent itself. It dropped its own price to zero for anyone bringing their own compute and model subscription, moved the paid surface to parallel remote execution, and extended access to desktop and mobile alongside its CLI and SDK. Conversation around Amp mostly tracks the broader model-release cycle: it shows up in setup guides and release notes as one of the supported coding agents when a new frontier model ships, named alongside the category's established harnesses rather than debated on its own terms. That makes for a quieter, early footprint in the coding-agent conversation relative to the wider market it sits in.
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Business Profile
Amp is Sourcegraph's coding agent, shipped as a product line rather than a separately financed startup — no funding round of its own is on record. Launched in 2025 with a team of about 18, it ships on a near-weekly cadence: mobile and desktop apps, team collaboration inside threads, multi-repo projects, and custom model selection have all landed within a few months. In September 2026 it restructured pricing around that speed, dropping the agent itself to free for anyone bringing their own compute and model subscription, and moving the bill to paid remote execution instead — a small team betting on distribution over harness monetization.
Agent Readiness
Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →
Amp ships a CLI and TypeScript SDK for direct agent access, plus MCP client support for pulling in outside tools — it consumes MCP servers rather than exposing one of its own. Build-out has focused on the agent's own surface: custom model selection, steerable messaging, and remote execution environments (orbs) for running agents in parallel, with recent releases extending that reach to mobile and desktop control.
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