AI visibility report
Augment Code ranks #1 in Autonomous Coding Agents AI search.
Outside the top three on 9 of the 25 prompts buyers actually ask.
All Hands AI (OpenHands) is cited on 2 of those losses.
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Track Augment Code across these prompts daily.
Start free trialBest among 17 vendors · still absent from 86.4% of tracked prompt responses
Top-3 citations across 125 prompt × platform pairs
Peer Ranking
Key Metrics
Platform Breakdown
Perplexity
Google AI Mode
Gemini Search
Bing Copilot
ChatGPTLeader, with room to expand. Augment Code leads this category on presence and share of voice, but appears in only 13.6% 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 winning5
Which autonomous coding agents give the best real-time feedback loop when running multi-step tasks so developers stay in control?
Avg # 1.0 · 1 platform
What agentic coding tools handle long-running tasks reliably — resuming after an interruption rather than starting over from scratch?
Avg # 1.0 · 1 platform
What AI coding agents do senior engineers prefer for refactoring large codebases without babysitting every intermediate step?
Avg # 1.0 · 1 platform
What autonomous coding tools have the best ecosystem of community plugins for extending agent capabilities with custom tools and workflows?
Avg # 2.0 · 1 platform
Which autonomous coding agents can reliably write and run tests, interpret failures, and self-correct without human intervention?
Avg # 2.0 · 1 platform
Where Augment Code is losing5
What AI coding agents support bring-your-own LLM provider so a platform team can route through an existing enterprise model contract?
Competitors on 2 platforms
Track this promptWhat autonomous coding tools handle legacy codebases in dynamically typed languages best — Python 2 or older PHP specifically?
Competitors on 1 platform
Track this promptWhich cloud coding agents have the best uptime and task success rates for a mid-size team running dozens of concurrent agent jobs daily?
Competitors on 1 platform
Track this promptWhich AI coding agents handle context window limitations most gracefully when working across dozens of files in an enterprise codebase?
Competitors on 1 platform
Track this promptI'm looking for an agentic CLI that supports tool use like web search and shell execution during a coding task — what are my options?
Competitors on 1 platform
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
Augment Code : Uses asynchronous AI agent workflows that utilize durable long-running execution.
Which autonomous coding agents can reliably write and run tests, interpret failures, and self-correct without human intervention?
...emantic dependency analysis over simple pattern matching . Top Autonomous Tools for Legacy Codebases 1. Augment Code : Known for its high-performance Co...
What AI coding agents handle multi-repo tasks well — making coordinated changes across a frontend and backend repo in a single session?
Augment Code : Provides, alongside others like Codex, real-time code reviews and multi-file task automation, helping developers maintain control.
Which agentic IDEs have the smoothest experience for reviewing and approving AI-generated changes before they touch the main branch?
Most cited sources8
6How Async AI Agent Workflows Survive Failures - Augment Code
augmentcode.com·Documentation
- 5
AI Coding Assistants for Large Codebases: A Complete Guide | Augment Code
augmentcode.com·Article
- 5
What Is an Agent Execution Sandbox? | Augment Code
augmentcode.com·Documentation
- 5
AI Sprint Planning Tools: Jira, Linear, GitHub & Beyond | Augment Code
augmentcode.com·Product Page
- 4
13 Best AI Coding Tools for Complex Codebases in 2026 | Augment Code
augmentcode.com·Article
- 3
Best AI Model for Coding Agents in 2026: A Routing Guide
augmentcode.com·Documentation
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.
- AAnthropic (Claude Code)#26
- All Hands AI (OpenHands)#36
- OpenAI (Codex CLI / Codex)#45
- Block (Goose)#62
- Cline Bot Inc.#72
- CCursor (Anysphere)#52
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 | ChatGPT | Gemini Search | Bing Copilot |
|---|---|---|---|---|---|
Capability3/5 cited (60%) | |||||
What AI coding agents handle multi-repo tasks well — making coordinated changes across a frontend and backend repo in a single session? | |||||
What autonomous coding tools handle legacy codebases in dynamically typed languages best — Python 2 or older PHP specifically? | |||||
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? | |||||
Which cloud coding agents are best for generating and merging pull requests asynchronously without a developer staying in the loop? | |||||
Developer Experience3/5 cited (60%) | |||||
Which autonomous coding agents give the best real-time feedback loop when running multi-step tasks so developers stay in control? | |||||
Which AI coding agents handle context window limitations most gracefully when working across dozens of files in an enterprise codebase? | |||||
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? | |||||
What autonomous coding tools are best suited for a solo developer who wants to delegate routine feature work and focus on architecture? | |||||
Integrations & Ecosystem3/5 cited (60%) | |||||
Which cloud coding agents integrate with CI pipelines to automatically attempt fixes when a build or test suite fails? | |||||
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? | |||||
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? | |||||
Performance & Reliability2/5 cited (40%) | |||||
Which AI coding agents complete multi-file tasks fastest without sacrificing correctness — benchmarks or real-world comparisons? | |||||
Which cloud coding agents have the best uptime and task success rates for a mid-size team running dozens of concurrent agent jobs daily? | |||||
What autonomous coding agents run tasks inside a secure sandbox so a compromised prompt can't affect the host filesystem? | |||||
What agentic coding tools handle long-running tasks reliably — resuming after an interruption rather than starting over from scratch? | |||||
Which autonomous coding agents are most cost-efficient for high-volume use — minimising frontier LLM provider token spend per merged PR? | |||||
Setup & First Run2/5 cited (40%) | |||||
Which cloud coding agents can be connected to an existing private repo and start opening pull requests with minimal setup? | |||||
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? | |||||
I'm evaluating autonomous coding agents for a 10-person startup — which ones can a new engineer get productive with in under an hour? | |||||
What's the easiest AI coding agent to get running locally on a large existing TypeScript monorepo without hours of configuration? | |||||
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 | 13.6% | 33.8% | 0.0% | 0.0% | 9.6% | #5.9 | +0.34 |
| 2 | Anthropic (Claude Code) | 6.4% | 11.3% | 0.0% | 0.0% | 74.4% | #3.3 | +0.62 |
| 3 | All Hands AI (OpenHands) | 5.6% | 28.2% | 0.8% | 2.4% | 16.8% | #11.0 | +0.56 |
| 4 | OpenAI (Codex CLI / Codex) | 4.8% | 9.9% | 1.6% | 0.0% | 44.0% | #6.0 | +0.42 |
| 5 | Cursor (Anysphere) | 1.6% | 2.8% | 0.8% | 0.0% | 62.4% | #4.5 | +0.77 |
| 6 | Block (Goose) | 1.6% | 2.8% | 0.0% | 0.0% | 0.0% | #7.0 | +0.30 |
| 7 | Cline Bot Inc. | 1.6% | 5.6% | 0.0% | 0.0% | 17.6% | #9.5 | +0.55 |
| 8 | Factory (Droid) | 0.8% | 1.4% | 0.0% | 0.0% | 2.4% | #2.0 | +0.90 |
| 9 | Warp | 0.8% | 1.4% | 0.8% | 0.0% | 2.4% | #2.0 | +0.80 |
| 10 | Aider AI | 0.8% | 1.4% | 0.0% | 0.0% | 21.6% | #22.0 | +0.60 |
| 11 | Replit (Agent 3) | 0.8% | 1.4% | 0.0% | 0.0% | 4.0% | #24.0 | +0.60 |
| 12 | Amp | 0.0% | 0.0% | 0.0% | 0.0% | 0.8% | — | — |
| 13 | Cognition (Devin) | 0.0% | 0.0% | 0.0% | 0.0% | 40.0% | — | — |
| 14 | Lovable | 0.0% | 0.0% | 0.0% | 0.0% | 0.8% | — | — |
| 15 | OpenCode | 0.0% | 0.0% | 0.0% | 0.0% | 8.0% | — | — |
| 16 | Roo Code (Roomote) | 0.0% | 0.0% | 0.0% | 0.0% | 4.0% | — | — |
| 17 | StackBlitz (Bolt.new) | 0.0% | 0.0% | 0.0% | 0.0% | 0.0% | — | — |
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