AI visibility report
AI visibility report for Amp in Autonomous Coding Agents.
Outside the top three on 14 of the 25 prompts buyers actually ask.
Augment Code is cited on 6 of those losses.
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Track Amp across these prompts daily.
Start free trialStill absent from 100% of tracked prompt responses
Top-3 citations across 125 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Gemini Search
ChatGPT
Bing Copilot
Perplexity
Google AI ModeHow to read this. Amp appears in 0% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.
Where Amp is losing
Prompts where competitors are visible and Amp is not.
These prompt-level losses are the first prompts to track and repair.
Where Amp is winning
No clear strengths identified yet.
Where Amp is losing5
Which AI coding agents handle context window limitations most gracefully when working across dozens of files in an enterprise codebase?
Competitors on 3 platforms
Track this promptWhat AI coding agents support bring-your-own LLM provider so a platform team can route through an existing enterprise model contract?
Competitors on 3 platforms
Track this promptWhat agentic coding tools handle long-running tasks reliably — resuming after an interruption rather than starting over from scratch?
Competitors on 2 platforms
Track this promptWhich cloud coding agents integrate with CI pipelines to automatically attempt fixes when a build or test suite fails?
Competitors on 1 platform
Track this promptWhat autonomous coding agents run tasks inside a secure sandbox so a compromised prompt can't affect the host filesystem?
Competitors on 1 platform
Track this prompt
Track Amp daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Amp is a frontier autonomous coding agent developed by Amp Frontier Corporation, a company spun out of Sourcegraph in December 2025. Delivered as a CLI with integrations for VS Code, JetBrains, Neovim, and Zed, Amp routes tasks across multiple leading frontier models—including Claude Opus 4.8 for its smart mode and GPT-5.5 for deep and rush modes—selecting the best model for the complexity of each task. It supports parallel subagent execution, an Oracle secondary-reasoning model, a Librarian for GitHub code search, and a Painter for AI image generation. Amp uses a pay-as-you-go credit system with no markup for non-enterprise users. Workspace thread sharing, enterprise SSO, zero-data-retention inference, and a TypeScript plugin API serve team and enterprise buyers. Amp claims profitability since its spinout and describes its design philosophy as ruthlessly frontier-focused.
Amp is an autonomous coding agent delivered as a CLI tool with IDE integrations that routes development tasks across multiple frontier AI models. It offers three operating modes—smart, deep, and rush—and specialized subagents including an Oracle for high-reasoning tasks, a Librarian for GitHub code search, and a Painter for image generation. A TypeScript plugin system and MCP support enable extensibility, while thread sharing and workspace collaboration address team workflows. Amp targets developers who want raw frontier-model power for coding without being locked into a single IDE or provider.
Key Facts
- Founded
- 2025
- HQ
- San Francisco, USA
- Founders
- Quinn Slack, Beyang Liu, Thorsten Ball +3 more
- Status
- Private
Target users
Key Capabilities10
- Three agent modes: smart (unconstrained frontier models), deep (extended reasoning via GPT-5.5), and rush (fast, low-token GPT-5.5 for small tasks)
- Parallel subagent orchestration for multi-file or multi-step tasks with independent context windows
- Oracle: secondary high-reasoning model (GPT-5.5 with high reasoning effort) invokable for complex debugging or code review
- Librarian: specialized subagent for searching and reading public and private GitHub repositories
- Painter: image generation and editing tool powered by GPT Image 2
- TypeScript plugin system with event hooks, custom tools, custom agent modes, and command palette commands
- MCP (Model Context Protocol) integration with lazy loading via skill-bundled mcp.json files
- AGENTS.md and Skills system for codebase-specific and user-wide agent guidance
- Thread sharing, workspace collaboration, and remote control from web and mobile
- Automated code review with extensible checks via .agents/checks/ Markdown definitions
Key Use Cases8
- Autonomous multi-file code editing, refactoring, and test fixing from the terminal
- Parallel code migration tasks (e.g., converting CSS to Tailwind across multiple files using subagents)
- Deep debugging sessions using the Oracle for complex reasoning on hard bugs
- Cross-repository research using the Librarian to inspect framework or library source code
- Legacy codebase modernization (e.g., COBOL migration guided by AGENTS.md context files)
- Automated code review with custom checks enforcing team security and style invariants
- CI/CD pipeline integration via --execute and --stream-json flags for non-interactive agentic runs
- Enterprise team collaboration with workspace thread sharing, SSO, and per-user cost controls
Recent Trend
How AI describes Amp1
Amp * OpenCode Progress streams back into Linear and PRs are linked automatically.
Which agentic coding platforms integrate with project management tools so engineers can assign tickets directly to an AI agent to action?
Most cited sources
No cited source mix is available for this brand yet.
Alternatives in Autonomous Coding Agents6
Amp positions itself as the 'frontier' autonomous coding agent: CLI-first, multi-model (routing across Claude Opus, GPT-5.5, and others depending on task complexity), with a pay-as-you-go pricing model that passes LLM API costs through to users at zero markup for individuals and non-enterprise teams.
- Unlike IDE-native competitors such as Cursor or Windsurf, Amp is editor-agnostic and integrates with VS Code, JetBrains, Neovim, and Zed via a shared CLI.
- Its explicit design philosophy is to continuously shed legacy features and workflows in favor of what current frontier models support, positioning against more conservative, subscription-based tools.
- Enterprise features (SSO, zero data retention, managed policies) target regulated organizations, while the free tier and credit-based model lower the barrier for individual developers.
- AAugment Code#19
- AAnthropic (Claude Code)#23
- Block (Goose)#33
- OpenAI (Codex CLI / Codex)#43
- CCursor (Anysphere)#62
- Factory (Droid)#52
Reviews
Praised
- Highly agentic and autonomous multi-file task execution
- IDE agnosticism — works with VS Code, JetBrains, Neovim, Zed
- Smart automatic context and thread management
- Multi-model routing matching model to task complexity
- Pay-as-you-go with no markup on LLM costs
- Polish and premium UX compared to Claude Code and Codex
- Workspace thread sharing for team collaboration
- Audio and web remote-control notifications
Criticized
- Subagents cannot communicate mid-task, limiting complex coordination
- AI-generated code quality requires careful human review
- Cost unpredictability with advanced models at scale
- No native Windows support (WSL required)
- No bring-your-own-key option for model providers
- Tools run autonomously without approval prompts by default
- Enterprise pricing at 50% premium over individual plans
User testimonials from X/Twitter describe Amp as polished, highly agentic, and more reliable than Claude Code or OpenAI Codex for autonomous multi-file tasks. Independent developer reviews highlight strong codebase context awareness, IDE agnosticism, smart context management, and quality-of-life features like audio completion notifications. Common criticisms include concerns about AI-generated code quality requiring review, cost unpredictability at scale with advanced models, and subagents' inability to communicate mid-task. The G2 listing (4.5/5, 90 reviews) conflates older Sourcegraph Cody reviews with the current Amp product, limiting its reliability as a standalone signal for the Amp coding agent.
Pricing
Amp uses a credit-based, pay-as-you-go model. For individual and non-enterprise workspace users, LLM API costs are passed through with zero markup; the minimum credit purchase is $5. Enterprise workspaces are priced at 50% above individual/team rates and require a one-time $1,000 USD purchase to activate, which grants $1,000 of Enterprise-tier credits. Enterprise includes SSO (Okta, SAML), directory sync, zero data retention for LLM text inputs, per-user entitlements, IP allowlisting, and managed settings. A free tier (Amp Free) exists for interactive CLI sessions; execute-mode (amp -x) consumes paid credits only. Credits are pooled at the workspace level and expire after one year of account inactivity. Invoicing is via Stripe.
Limitations
- Subagents operate in isolation and cannot communicate with each other or receive mid-task guidance; the main agent only receives their final summary.
- Amp does not support bring-your-own-key (BYOK) for model providers (removed May 2025).
- Windows is supported only via WSL, not natively.
- Amp runs tools autonomously without approval prompts by default, which requires custom plugin configuration to restrict.
- Enterprise usage is priced 50% above individual/team rates.
- The free tier (Amp Free) applies only to interactive sessions, not execute-mode runs.
- Context within a thread is managed automatically but subagents start without the parent thread's accumulated conversation context.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Gemini Search | ChatGPT | Bing Copilot | Perplexity | Google AI Mode |
|---|---|---|---|---|---|
Capability0/5 cited (0%) | |||||
What AI coding agents handle multi-repo tasks well — making coordinated changes across a frontend and backend repo in a single session? | |||||
Which autonomous coding agents can reliably write and run tests, interpret failures, and self-correct without human intervention? | |||||
I'm looking for an agentic CLI that supports tool use like web search and shell execution during a coding task — what are my options? | |||||
What autonomous coding tools handle legacy codebases in dynamically typed languages best — Python 2 or older PHP specifically? | |||||
Which cloud coding agents are best for generating and merging pull requests asynchronously without a developer staying in the loop? | |||||
Developer Experience0/5 cited (0%) | |||||
Which autonomous coding agents give the best real-time feedback loop when running multi-step tasks so developers stay in control? | |||||
Which agentic IDEs have the smoothest experience for reviewing and approving AI-generated changes before they touch the main branch? | |||||
What AI coding agents do senior engineers prefer for refactoring large codebases without babysitting every intermediate step? | |||||
Which AI coding agents handle context window limitations most gracefully when working across dozens of files in an enterprise codebase? | |||||
What autonomous coding tools are best suited for a solo developer who wants to delegate routine feature work and focus on architecture? | |||||
Integrations & Ecosystem0/5 cited (0%) | |||||
Which cloud coding agents integrate with CI pipelines to automatically attempt fixes when a build or test suite fails? | |||||
Which autonomous coding agents integrate natively with popular code editors so devs can trigger agent tasks without leaving their IDE? | |||||
What AI coding agents support bring-your-own LLM provider so a platform team can route through an existing enterprise model contract? | |||||
Which agentic coding platforms integrate with project management tools so engineers can assign tickets directly to an AI agent to action? | |||||
What autonomous coding tools have the best ecosystem of community plugins for extending agent capabilities with custom tools and workflows? | |||||
Performance & Reliability0/5 cited (0%) | |||||
What autonomous coding agents run tasks inside a secure sandbox so a compromised prompt can't affect the host filesystem? | |||||
Which autonomous coding agents are most cost-efficient for high-volume use — minimising frontier LLM provider token spend per merged PR? | |||||
Which cloud coding agents have the best uptime and task success rates for a mid-size team running dozens of concurrent agent jobs daily? | |||||
Which AI coding agents complete multi-file tasks fastest without sacrificing correctness — benchmarks or real-world comparisons? | |||||
What agentic coding tools handle long-running tasks reliably — resuming after an interruption rather than starting over from scratch? | |||||
Setup & First Run0/5 cited (0%) | |||||
What are the best agentic IDEs for a team migrating from a traditional code editor that want AI-assisted multi-file editing from day one? | |||||
Which agentic CLI tools work out of the box on popular operating systems without requiring a container sandbox just to get started? | |||||
Which cloud coding agents can be connected to an existing private repo and start opening pull requests with minimal setup? | |||||
What's the easiest AI coding agent to get running locally on a large existing TypeScript monorepo without hours of configuration? | |||||
I'm evaluating autonomous coding agents for a 10-person startup — which ones can a new engineer get productive with in under an hour? | |||||
Turn this matrix into daily prompt monitoring.
Track prompt changesVertical Ranking
| # | Brand | PresencePres. | Share of VoiceSoV | DocsDocs | BlogBlog | MentionsMent. | Avg PosPos | Sentiment |
|---|---|---|---|---|---|---|---|---|
| 1 | Augment Code | 8.8% | 32.7% | 0.0% | 0.0% | 8.0% | #7.2 | +0.21 |
| 2 | Anthropic (Claude Code) | 3.2% | 12.7% | 0.0% | 0.0% | 3.2% | #3.9 | +0.35 |
| 3 | Block (Goose) | 3.2% | 12.7% | 0.0% | 0.0% | 3.2% | #4.9 | +0.54 |
| 4 | OpenAI (Codex CLI / Codex) | 3.2% | 10.9% | 0.8% | 0.0% | 2.4% | #7.7 | +0.25 |
| 5 | Factory (Droid) | 2.4% | 10.9% | 0.0% | 0.0% | 1.6% | #4.7 | +0.60 |
| 6 | Cursor (Anysphere) | 2.4% | 5.5% | 0.8% | 0.8% | 2.4% | #16.7 | +0.27 |
| 7 | Warp | 1.6% | 3.6% | 1.6% | 0.0% | 1.6% | #4.0 | +0.30 |
| 8 | All Hands AI (OpenHands) | 0.8% | 5.5% | 0.0% | 0.0% | 0.8% | #2.0 | +0.70 |
| 9 | OpenCode | 0.8% | 1.8% | 0.0% | 0.0% | 0.8% | #2.0 | +0.60 |
| 10 | Cognition (Devin) | 0.8% | 1.8% | 0.8% | 0.0% | 0.8% | #3.0 | +0.80 |
| 11 | Aider AI | 0.8% | 1.8% | 0.0% | 0.0% | 0.8% | #27.0 | +0.00 |
| 12 | Amp | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 13 | Cline Bot Inc. | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 14 | Lovable | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 15 | Replit (Agent 3) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 16 | Roo Code (Roomote) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
| 17 | StackBlitz (Bolt.new) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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