AI visibility report
AI visibility report for Anthropic (Claude Code) in Autonomous Coding Agents.
Outside the top three on 10 of the 25 prompts buyers actually ask.
Augment Code is cited on 6 of those losses.
Free trial. Setup comes pre-filled for Anthropic (Claude Code).
Track Anthropic (Claude Code) across these prompts daily.
Start free trialStill absent from 96.8% 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. Anthropic (Claude Code) appears in 3.2% of tracked prompt responses. Presence is absolute coverage; share of voice is relative citation share; sentiment measures tone only when the brand appears.
Where Anthropic (Claude Code) is losing
Prompts where competitors are visible and Anthropic (Claude Code) is not.
These prompt-level losses are the first prompts to track and repair.
Where Anthropic (Claude Code) is winning4
Which autonomous coding agents can reliably write and run tests, interpret failures, and self-correct without human intervention?
Avg # 1.0 · 1 platform
What autonomous coding agents run tasks inside a secure sandbox so a compromised prompt can't affect the host filesystem?
Avg # 2.0 · 1 platform
What agentic coding tools handle long-running tasks reliably — resuming after an interruption rather than starting over from scratch?
Avg # 2.0 · 1 platform
Which cloud coding agents integrate with CI pipelines to automatically attempt fixes when a build or test suite fails?
Avg # 3.0 · 1 platform
Where Anthropic (Claude Code) 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 promptWhich agentic CLI tools work out of the box on popular operating systems without requiring a container sandbox just to get started?
Competitors on 1 platform
Track this promptWhat's the easiest AI coding agent to get running locally on a large existing TypeScript monorepo without hours of configuration?
Competitors on 1 platform
Track this promptWhat AI coding agents do senior engineers prefer for refactoring large codebases without babysitting every intermediate step?
Competitors on 1 platform
Track this prompt
Track Anthropic (Claude Code) daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Claude Code is Anthropic's agentic coding system, generally available since May 2025, that orchestrates entire software projects rather than offering line-by-line autocomplete. It reads full codebases, plans multi-step changes, edits files across directories, executes shell commands and test suites, and commits results—operating from a terminal CLI, VS Code or JetBrains plugin, standalone desktop app, or web browser. Powered by Anthropic's Claude Sonnet and Opus frontier models, it extends its reach via the open Model Context Protocol (MCP), connecting to GitHub, GitLab, Jira, Slack, and custom APIs. It targets professional engineers, enterprise teams running large-scale migrations, and non-engineers building software by describing outcomes in plain language. Enterprise plans add HIPAA compliance, 500K-token context, SSO, and granular spend controls.
Claude Code is Anthropic's terminal-native, agentic coding system that autonomously reads codebases, plans and executes multi-file changes, runs tests, fixes failures, and manages git workflows. Backed by Anthropic's Claude Sonnet and Opus frontier models, it operates at the project level rather than suggesting the next line, and extends via MCP, IDE plugins, CI/CD integrations, a desktop app, and the web—targeting both professional engineers and non-engineers who need to build software by describing outcomes in plain language.
Key Facts
- Founded
- 2021
- HQ
- San Francisco, CA
- Founders
- Dario Amodei, Daniela Amodei, Benjamin Mann
- Employees
- 3000-5000
- Funding
- ~$132B
- ARR
- ~$47B (Anthropic overall, May 2026 est.)
- Customers
- 300,000+ business customers; 1,000+ spen
- Valuation
- $965B
- Status
- Private
Target users
Key Capabilities10
- Whole-codebase context reading and navigation (up to 200K tokens on subscription, 500K on Enterprise, 1M via API on Opus)
- Autonomous multi-file code editing, refactoring, and feature development across entire projects
- Test execution, failure interpretation, and iterative bug fixing until test suites pass
- Native git workflow automation: commits, branches, pull requests, and merge requests
- GitHub Actions and GitLab CI/CD integration with automated PR/MR code review
- Model Context Protocol (MCP) extensibility connecting to external tools, databases, and APIs
- Multi-agent orchestration: parallel sub-agents coordinated by a lead agent for concurrent task execution
- Configurable autonomy and permissions model (per-action approval to fully autonomous classifier-gated modes)
- CLAUDE.md project memory, Skills, Hooks, and Routines for persistent workflow customization
- Cross-surface availability: terminal CLI, VS Code, JetBrains, desktop app, web, iOS, and Slack
Key Use Cases8
- Large-scale codebase migrations across languages or frameworks
- Autonomous feature development across multi-file, multi-language projects
- Incident investigation and root-cause diagnosis in production systems
- CI/CD pipeline monitoring with automated failure remediation
- Code review automation via GitHub and GitLab integrations
- Onboarding engineers to unfamiliar or legacy codebases
- Non-engineer prototyping and internal tooling by PMs, founders, and ops teams
- Dependency upgrades, lint fixes, and routine maintenance automation
Anthropic (Claude Code) customer outcomes
4 days vs. 10 engineer-weeks estimated
Deployed Claude Code to 1,370 engineers via a zero-configuration enterprise signed binary. One team completed a 10,000-line Scala-to-Java migration in four days, a project estimated at ten engineer-weeks without AI assistance.
80% reduction in incident investigation time
Integrated Claude Code into development workflows, enabling non-engineering teams in sales, risk, and finance to query data warehouses using natural language instead of writing SQL.
~20 hours active development vs. 2–3 months manual estimate
Migrated a 50,000-line Python library to Go using Claude Code in approximately 20 hours of active development, a project the team estimated would take two to three months manually.
79% reduction in feature delivery time (24 days → 5 days)
Reduced average feature delivery time from 24 working days to 5 by running multiple Claude Code sessions in parallel. A single autonomous run implemented a complex activation vector extraction method in vLLM (12.5M lines of code) in 7 hours with 99.9% numerical accuracy.
Recent Trend
How AI describes Anthropic (Claude Code)
No concise AI response excerpt is available for this brand yet.
Most cited sources5
2Effective harnesses for long-running agents \ Anthropic
anthropic.com·Home
- 2
Making Claude Code more secure and autonomous with sandboxing \ Anthropic
anthropic.com·Blog Post
- 1
Harness design for long-running application development
anthropic.com·Home
- 1
Demystifying evals for AI agents \ Anthropic
anthropic.com·Blog Post
- 1
Claude Code | Anthropic's agentic coding system \ Anthropic
anthropic.com·Product Page
Alternatives in Autonomous Coding Agents6
Claude Code is Anthropic's first-party agentic coding agent, uniquely positioned as the only major autonomous coding tool built and maintained by the same organization that trains the underlying frontier models (Claude Sonnet and Opus).
- Unlike IDE-embedded tools (Cursor, GitHub Copilot) or open-source CLI agents (Aider, OpenCode), Claude Code benefits from vertical integration between model and agent, allowing Anthropic to co-optimize reasoning for agentic tasks, control safety defaults, and distribute the tool across its existing subscription tiers.
- In enterprise segments, it leads on HIPAA compliance, offers 500K-token context windows on Enterprise plans, and has deployed at firms like Stripe (1,370 engineers), Ramp, and Rakuten.
- Claude Code reached $2.5B in annualized revenue by February 2026 per public reporting, reflecting dominant enterprise adoption.
- Its closest rivals are Cursor for IDE-native developers and OpenAI Codex CLI for teams preferring OpenAI models.
- AAugment Code#19
- Block (Goose)#33
- OpenAI (Codex CLI / Codex)#43
- CCursor (Anysphere)#62
- Factory (Droid)#52
- WWarp#72
Reviews
Praised
- Whole-codebase context awareness and architectural understanding
- High first-pass code accuracy across multi-file changes
- Strong ROI compared to developer or plugin licensing costs
- Seamless MCP, Skills, and connector ecosystem integration
- Accessible to non-engineers for building production systems
- Terminal-native workflow suited to CLI-first developers
- Fast onboarding to unfamiliar or legacy codebases
- Configurable autonomy and permission controls for safe enterprise use
Criticized
- Terminal-first UX less polished than IDE-native tools like Cursor
- Rate limits (5-hour session windows, weekly caps) interrupt heavy workloads
- Token cost unpredictability and risk of large unexpected API bills
- No free tier for Claude Code access
- Data privacy concerns for proprietary codebases on a closed API
- Key commands and features hard to discover for new users
- MCP tool calls silently add token overhead to session costs
- Context exhaustion on very large monorepos
Claude Code holds a 4.9/5 rating on G2 with 14 reviews as of mid-2026, with 92% five-star reviews. Reviewers—including non-engineers who built production systems without a coding background—consistently highlight its whole-codebase context awareness, high first-pass code accuracy, and strong ROI relative to developer costs or plugin licenses. Common criticisms center on the terminal-first interface being unfamiliar to IDE-centric developers, rate-limit friction during heavy use, and token cost unpredictability at scale. Broader Claude platform reviews on Trustpilot (1,586 reviews) reflect frustration with subscription usage limits and customer support, which carries over to Claude Code experiences at the subscription tier.
Pricing
Claude Code requires a paid Claude subscription or Anthropic API account; there is no free-tier access. Individual plans: Pro at $20/month ($17/month billed annually) with Claude Sonnet access; Max 5x at $100/month (5× Pro usage limits, adds Opus access); Max 20x at $200/month (20× Pro limits). Team plans require at least 5 seats: Standard at $25/seat/month ($20 annual); Premium at $125/seat/month ($100 annual), which includes Claude Code. Enterprise is custom-priced, adding 500K context, HIPAA compliance, SSO, audit logs, and per-user spend caps. API billing (no subscription required) uses standard Anthropic token rates: Claude Sonnet at $3/M input and $15/M output tokens; Claude Opus at $5/M input and $25/M output tokens; prompt caching reduces cached input costs by up to 90%. Claude Code also runs on Amazon Bedrock, Google Vertex AI, and Microsoft Azure Foundry, billed through the respective cloud provider.
Limitations
- Claude Code is terminal-first, creating a steeper learning curve for developers accustomed to IDE-native tools like Cursor or GitHub Copilot.
- Rate limits—5-hour rolling session windows plus separate weekly caps—can interrupt heavy workloads, and cost management is complex at scale: API key misconfiguration can bypass subscription limits entirely, resulting in unexpectedly large pay-per-token bills.
- No free tier is available for Claude Code access.
- The closed-source API model raises data-privacy concerns for teams with proprietary codebases, as code is processed on Anthropic's infrastructure.
- MCP tool calls silently add token overhead.
- Native integrations are narrower than tools deeply embedded in the GitHub or JetBrains ecosystems, with most extensibility requiring MCP configuration.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Gemini Search | ChatGPT | Bing Copilot | Perplexity | Google AI Mode |
|---|---|---|---|---|---|
Capability1/5 cited (20%) | |||||
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 & Ecosystem1/5 cited (20%) | |||||
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 & Reliability2/5 cited (40%) | |||||
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% | — | — |
Turn this into your team dashboard
Sign up to unlock project-level analytics, daily tracking, actionable insights, custom prompt configurations, adoption tracking, AI traffic analytics and more.
Free trial. Setup comes pre-filled from this report.