AI visibility report
Augment Code ranks #1 in Autonomous Coding Agents AI search.
Outside the top three on 16 of the 25 prompts buyers actually ask.
OpenAI (Codex CLI / Codex) is cited on 7 of those losses.
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Track Augment Code across these prompts daily.
Start free trialBest among 17 vendors · still absent from 88% of tracked prompt responses
Top-3 citations across 125 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Perplexity
Bing Copilot
Gemini Search
Google AI Mode
ChatGPTLeader, with room to expand. Augment Code leads this category on presence and share of voice, but appears in only 12% of tracked prompt responses. The priority is defending current wins while expanding absolute coverage.
Where Augment Code is losing
Prompts where competitors are visible and Augment Code is not.
These prompt-level losses are the first prompts to track and repair.
Where Augment Code is winning1
What autonomous coding tools are best suited for a solo developer who wants to delegate routine feature work and focus on architecture?
Avg # 1.0 · 1 platform
Where Augment Code is losing5
What autonomous coding agents run tasks inside a secure sandbox so a compromised prompt can't affect the host filesystem?
Competitors on 3 platforms
Track this promptWhat autonomous coding tools have the best ecosystem of community plugins for extending agent capabilities with custom tools and workflows?
Competitors on 2 platforms
Track this promptWhich cloud coding agents are best for generating and merging pull requests asynchronously without a developer staying in the loop?
Competitors on 2 platforms
Track this promptWhich autonomous coding agents can reliably write and run tests, interpret failures, and self-correct without human intervention?
Competitors on 2 platforms
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 2 platforms
Track this prompt
Track Augment Code daily before the next report refresh.
Track these gapsResearch dossierCapabilities, use cases, sources, reviews, pricing, and FAQ
Overview
Augment Code (Augment Inc.) is a Palo Alto-based enterprise agentic software development platform founded in 2022 by Igor Ostrovsky (ex-Pure Storage chief architect) and Guy Gur-Ari (ex-Google AI researcher), led by CEO Scott Dietzen (ex-Pure Storage CEO). Its flagship product, Cosmos, orchestrates networks of AI agents across the full software development lifecycle—from ticket triage and code authoring through PR review, testing, and incident response. The platform's proprietary Context Engine maps codebase structure across up to 500,000 files, enabling agents to act with architectural awareness. Its Prism routing layer directs each AI turn to the highest-ROI model, claiming 20–30% cost reduction versus direct frontier-model access. Augment targets enterprise engineering organizations and has raised $252M in funding with customers including Adobe, MongoDB, Pure Storage, and DXC Technology.
Cosmos is Augment Code's unified agentic platform that coordinates specialized AI experts—PR Author, Code Reviewer, Tester, Incident Responder, Work Dispatcher, and more—across the entire SDLC. The Context Engine provides structural codebase understanding for large monorepos. Prism routes each LLM call to the optimal model per turn. A self-learning shared knowledge base captures team workflows and compounds organizational intelligence over time. Available via IDE extensions (VS Code, JetBrains, Visual Studio, Neovim), a CLI, and a managed cloud environment, with enterprise-grade controls including on-premises deployment, CMEK, VPC isolation, sandboxed agent execution, and comprehensive audit logging.
Key Facts
- Founded
- 2022
- HQ
- Palo Alto, California, USA
- Founders
- Igor Ostrovsky, Guy Gur-Ari
- Employees
- 100-200
- Funding
- $252M
- Valuation
- ~$977M (Apr 2024)
- Status
- Private
Target users
Key Capabilities10
- Context Engine: structural codebase indexing of up to 500,000 files with real-time dependency and call-graph mapping
- Cosmos platform: multi-agent SDLC orchestration from ticket triage through authored PR, review, testing, and incident response
- Prism model routing: per-turn LLM selection targeting 20–30% lower cost per task at maintained quality
- Autonomous code review agents with inline PR comments, risk analysis, and blast-radius assessment
- Ticket-to-PR automation: natural language task description to reviewed and merged pull request
- Incident management: autonomous alert investigation and resolution before on-call escalation
- Security remediation: automated CVE-to-reviewed-fix pipeline
- Self-learning organizational knowledge base with shared expert registry across agents and teams
- Enterprise security: SOC 2 Type II, ISO/IEC 42001 AIMS certification, CMEK, SAML/OIDC/SCIM, SIEM, audit logs
- Multi-model BYOK support with vendor-agnostic model selection across frontier and open-weights models
Key Use Cases8
- Automated pull request review and risk analysis at scale
- Ticket-to-PR: agent-driven feature development from backlog to merged code
- Security vulnerability (CVE) detection and automated remediation
- Test coverage generation and suite maintenance
- Incident triage and autonomous resolution before on-call escalation
- Legacy system modernization and large-scale codebase migrations
- Accelerated new engineer onboarding via codebase-aware agents
- Recurring SDLC workflow standardization across engineering organizations
Augment Code customer outcomes
50–100% productivity gains; 90%+ test coverage on major systems
Deployed persona-driven AI agents across development, QA, and product for 1,300+ engineers, achieving broad productivity gains and near-complete automated test coverage on major systems.
Delivery timeline reduced from ~1 year to 10 days on select projects
Embedded Augment Code into select critical projects within its 50,000-developer organization, dramatically cutting delivery timelines on those projects.
Development timeline reduced from 3 weeks to 3 days
Used context-aware AI agents to accelerate development of a personalized feature shipped in time for a major industry conference.
>40% increase in developer productivity
Early-access customer reporting broad developer productivity improvement across the engineering organization, cited in Augment's Series B announcement.
Targeting 3x delivery velocity
Scaling a 2,000-engineer organization using Augment's Context Engine on a 2.1M-line C++ codebase, targeting significant velocity improvement.
Recent Trend
How AI describes Augment Code3
.../System | Strategy for Context Limits | Strengths | Weaknesses | | --- | --- | --- | --- | | Sourcegraph Cody, Cursor, Augment Code | Index-first: persistent embeddings + code graphs | Handles huge repos well, reduces re-reading, strong enterpris...
Which AI coding agents handle context window limitations most gracefully when working across dozens of files in an enterprise codebase?
Best AI PR Automation Tools for Engineering Teams 2026 | Augment Code * Cost unpredictability: Usage-based billing (e.g., Devin’s ACUs) can spike with complex tasks.
Which cloud coding agents are best for generating and merging pull requests asynchronously without a developer staying in the loop?
Docker Sandboxes: Run Claude Code and More Safely | | Augment Code Execution Sandbox | Hardware-level isolation (microVMs, userspace kernels) | Default-deny filesystem & network policies | Designed for production-safe agent execution augmentcode.com...
What autonomous coding agents run tasks inside a secure sandbox so a compromised prompt can't affect the host filesystem?
Most cited sources8
11How Async AI Agent Workflows Survive Failures
augmentcode.com·Documentation
- 8
AI Coding Assistants for Large Codebases: A Complete Guide | Augment Code
augmentcode.com·Listicle
- 8
13 Best AI Coding Tools for Complex Codebases in 2026 | Augment Code
augmentcode.com·Listicle
- 8
What Is BYOA in AI Development? A Complete Guide | Augment Code
augmentcode.com·Documentation
- 7
Best AI PR Automation Tools for Engineering Teams 2026 | Augment Code
augmentcode.com·Listicle
- 7
How Do Agents Close the Build-Test-Fix Loop? | Augment Code
augmentcode.com·Comparison
Alternatives in Autonomous Coding Agents6
Augment Code positions itself as an enterprise-grade agentic SDLC platform for large engineering organizations, differentiating on its proprietary Context Engine (structural codebase indexing of up to 500,000 files) and the Cosmos orchestration layer that coordinates multiple AI agents across the full software development lifecycle.
- Unlike individual developer tools such as Cursor or Claude Code, Augment targets organizational-scale AI transformation—routing each AI turn via its Prism model-routing system, compounding shared organizational memory, and enforcing strict enterprise security (SOC 2 Type II, ISO/IEC 42001 AIMS, CMEK).
- Its stated benchmark advantage is delivering frontier-level code quality at 33% lower token cost versus running Claude directly on the same tasks.
- OpenAI (Codex CLI / Codex)#211
- All Hands AI (OpenHands)#310
- AAnthropic (Claude Code)#47
- Cline Bot Inc.#65
- Cognition (Devin)#75
- CCursor (Anysphere)#55
Reviews
Praised
- Superior context awareness across large and complex codebases
- Fast and relevant code suggestions with minimal flow disruption
- Seamless IDE integration across multiple editors
- Multi-model flexibility and BYOK support
- Enterprise security posture and compliance certifications
- Code review quality and cross-service dependency detection
- Agentic workflow automation reducing repetitive developer toil
Criticized
- Credit-based pricing perceived as unpredictable and expensive for heavy users
- October 2025 pricing migration described as bait-and-switch by legacy plan holders
- Slow or unresponsive customer support
- Agentic workflows slower than expected on large or complex tasks
- No native GitLab or Bitbucket integration for code review
- Higher cost than flat-rate competitors for individual developers
Augment Code earns strong ratings on Gartner Peer Insights (4.8/5, 41 reviews) with reviewers consistently praising the Context Engine's accuracy on large codebases, fast and contextually relevant suggestions, and seamless IDE integration. G2 data is extremely limited (2 reviews as of mid-2026 per secondary sources). Developer community sentiment is polarized: technical quality of codebase understanding is widely praised across Reddit, Hacker News, and Product Hunt, but the October 2025 credit pricing migration generated sustained criticism around cost unpredictability, customer support responsiveness, and perceived bait-and-switch billing changes.
Pricing
Business plan: $100/month flat for up to 50 seats, with $100 of pooled monthly usage included (LLM inference billed at provider list price plus a 40% service fee, plus compute). Pay-as-you-go top-ups available; purchased credits valid for 12 months. Enterprise plan: custom pricing with unlimited users, bespoke usage limits, volume discounts, SSO/OIDC/SCIM, CMEK, ISO 42001 compliance, multi-region compute, unlimited concurrent sessions, and dedicated support. No per-seat charge on Business; usage pooled across the team.
Limitations
- Credit-based pricing migration (October 2025, from message-based to usage-based billing) generated significant developer backlash, with community threads describing it as a bait-and-switch.
- Native code review integration is GitHub-only; GitLab and Bitbucket require CLI-based workarounds with manual setup.
- Business plan caps at 50 seats; larger teams require custom Enterprise contracts with undisclosed pricing.
- Customer support response times have been cited in reviews as slow (one Gartner reviewer reported a 10-day wait).
- Agentic workflows reported as slower than expected on larger or more complex tasks.
- Cost predictability is lower than flat-rate unlimited competitors such as Cursor or GitHub Copilot.
Frequently asked questions
Topic coverageCoverage by buyer topic
Topic Coverage
Prompt-Level Results
| Prompt | Google AI Mode | Perplexity | Gemini Search | Bing Copilot | ChatGPT |
|---|---|---|---|---|---|
Capability3/5 cited (60%) | |||||
Which cloud coding agents are best for generating and merging pull requests asynchronously without a developer staying in the loop? | Neither your brand nor a competitor was cited | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | Your brand was cited | A competitor was cited |
What autonomous coding tools handle legacy codebases in dynamically typed languages best — Python 2 or older PHP specifically? | Neither your brand nor a competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
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? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which autonomous coding agents can reliably write and run tests, interpret failures, and self-correct without human intervention? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited |
What AI coding agents handle multi-repo tasks well — making coordinated changes across a frontend and backend repo in a single session? | Neither your brand nor a competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Developer Experience3/5 cited (60%) | |||||
What autonomous coding tools are best suited for a solo developer who wants to delegate routine feature work and focus on architecture? | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which AI coding agents handle context window limitations most gracefully when working across dozens of files in an enterprise codebase? | Neither your brand nor a competitor was cited | Your brand was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
What AI coding agents do senior engineers prefer for refactoring large codebases without babysitting every intermediate step? | Neither your brand nor a competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which agentic IDEs have the smoothest experience for reviewing and approving AI-generated changes before they touch the main branch? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which autonomous coding agents give the best real-time feedback loop when running multi-step tasks so developers stay in control? | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Integrations & Ecosystem3/5 cited (60%) | |||||
Which autonomous coding agents integrate natively with popular code editors so devs can trigger agent tasks without leaving their IDE? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
What autonomous coding tools have the best ecosystem of community plugins for extending agent capabilities with custom tools and workflows? | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
What AI coding agents support bring-your-own LLM provider so a platform team can route through an existing enterprise model contract? | A competitor was cited | Your brand and a competitor were cited | A competitor was cited | Your brand was cited | A competitor was cited |
Which agentic coding platforms integrate with project management tools so engineers can assign tickets directly to an AI agent to action? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which cloud coding agents integrate with CI pipelines to automatically attempt fixes when a build or test suite fails? | A competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
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? | A competitor was cited | Your brand was cited | Neither your brand nor a competitor was cited | Your brand and a competitor were cited | A competitor was cited |
Which cloud coding agents have the best uptime and task success rates for a mid-size team running dozens of concurrent agent jobs daily? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
What agentic coding tools handle long-running tasks reliably — resuming after an interruption rather than starting over from scratch? | Neither your brand nor a competitor was cited | Your brand was cited | Your brand was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which AI coding agents complete multi-file tasks fastest without sacrificing correctness — benchmarks or real-world comparisons? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which autonomous coding agents are most cost-efficient for high-volume use — minimising frontier LLM provider token spend per merged PR? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Setup & First Run0/5 cited (0%) | |||||
I'm evaluating autonomous coding agents for a 10-person startup — which ones can a new engineer get productive with in under an hour? | Neither your brand nor a competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited |
Which cloud coding agents can be connected to an existing private repo and start opening pull requests with minimal setup? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
What's the easiest AI coding agent to get running locally on a large existing TypeScript monorepo without hours of configuration? | Neither your brand nor a competitor was cited | A competitor was cited | A competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
Which agentic CLI tools work out of the box on popular operating systems without requiring a container sandbox just to get started? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
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? | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | Neither your brand nor a competitor was cited | A competitor was cited |
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 | 12.0% | 22.1% | 0.0% | 0.0% | 8.0% | #6.3 | +0.33 |
| 2 | OpenAI (Codex CLI / Codex) | 11.2% | 20.6% | 3.2% | 0.0% | 48.0% | #4.0 | +0.66 |
| 3 | All Hands AI (OpenHands) | 9.6% | 14.5% | 3.2% | 6.4% | 19.2% | #4.6 | +0.52 |
| 4 | Anthropic (Claude Code) | 7.2% | 9.9% | 1.6% | 0.8% | 69.6% | #4.9 | +0.43 |
| 5 | Cursor (Anysphere) | 4.8% | 8.4% | 2.4% | 1.6% | 56.8% | #2.8 | +0.67 |
| 6 | Cline Bot Inc. | 4.8% | 7.6% | 0.8% | 1.6% | 19.2% | #2.9 | +0.60 |
| 7 | Cognition (Devin) | 4.8% | 7.6% | 4.8% | 0.0% | 42.4% | #5.4 | +0.67 |
| 8 | OpenCode | 2.4% | 3.1% | 1.6% | 0.0% | 16.0% | #2.0 | +0.57 |
| 9 | Aider AI | 1.6% | 2.3% | 1.6% | 0.0% | 23.2% | #5.3 | +0.90 |
| 10 | Factory (Droid) | 0.8% | 2.3% | 0.0% | 0.0% | 0.8% | #2.0 | +0.50 |
| 11 | Warp | 0.8% | 1.5% | 0.8% | 0.0% | 0.8% | #2.0 | +0.00 |
| 12 | Amp | 0.0% | 0.0% | 0.0% | 0.0% | 1.6% | — | — |
| 13 | Block (Goose) | 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% | 1.6% | — | — |
| 16 | Roo Code (Roomote) | 0.0% | 0.0% | 0.0% | 0.0% | 7.2% | — | — |
| 17 | StackBlitz (Bolt.new) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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