Is my code and data used to train AI models?

No. All paid plans explicitly exclude AI training on your data as part of the Commercial Terms of Service. Your code stays your own.

What is a 'loop' in Cosmos?

A loop is an automated workflow connecting one or more specialized agents (Experts) across stages of the SDLC. For example, the 'Ticket to PR' loop connects triage, authoring, and review agents. Loops can be connected to form a larger software factory.

Can I run agents on my own infrastructure?

Yes. Cosmos supports flexible execution environments: managed cloud sandboxes, your own machines (for code that cannot leave your network), or pools of both. This is configurable at the environment level.

What is the Context Engine?

The Context Engine is Augment's proprietary system for deep codebase understanding. It provides agents with the necessary context to make accurate changes across large, complex repositories, going beyond simple file reading.

How do human quality gates work in automated loops?

Quality gates are first-class. Work pauses at defined checkpoints (e.g., before merging a PR) and awaits human approval. The loop resumes automatically upon the reviewer's response, ensuring humans stay in control at critical junctures.

What kind of support and SLA do you offer?

All paid plans include core SLA coverage. Standard/Business plans get community support plus ticket-based support. Enterprise plans include dedicated support. Trials and beta use only get community support.

Directory/Coding/AI Coding Assistants/Augment Code

Augment Code

Augment Code is an AI-native coding platform designed for enterprise-grade software engineering. Its core product, Cosmos, is an agent orchestration platform that builds an 'always-on software delivery system.' It uses a 'Context Engine' for deep codebase understanding and ships with specialized 'Experts' (agents) for every stage of the SDLC, including code review, ticket-to-PR, vulnerability remediation, and incident response. The platform allows teams to build, tune, and run these automated workflows in natural language, with human-in-the-loop checkpoints for quality control. Key capabilities include connecting agents across the SDLC into reusable loops, native triggers for GitHub, GitLab, Slack, Jira, and CI systems, and execution in managed cloud sandboxes or on-prem. It targets software engineering teams, DevOps, and platform engineers looking to automate repetitive development tasks and increase throughput while maintaining governance.

Coding

Visit website

Added on

Sep 22, 2026

AI coding agentsSDLC automationCode reviewTicket-to-PRMulti-model orchestrationContext EngineSOC 2 Type IIHuman-in-the-loop

Product information

Everything worth knowing about Augment Code

The complete picture — from everyday features to the technical detail builders and IT folks dig for.

Core features

What it actually does

Software Factory Automation

Build and run end-to-end software delivery loops from ticket to deployment, with agents handling the repetitive middle steps and humans at quality gates.

Built-in Code Review & Ticket-to-PR

Automated PR review and assignment of tickets to create PRs, increasing engineering throughput.

Expert Orchestration Platform

Use pre-built 'Experts' (like PR Author, Tester) or create your own reusable agent templates for SDLC stages.

Human-in-the-Loop Quality Gates

Work pauses for human review and approval at critical checkpoints, ensuring control over consequential actions.

Shared Memory & Continuous Learning

Agents share memory across runs and teams, so one engineer's correction improves future runs for everyone.

Technical capabilities

Multi-Model Agent Runtime with Context Engine

Orchestrates agents (like Prism) that can auto-route between models (Claude, Gemini) for cost and quality, powered by a codebase-understanding Context Engine.

Must watch videos

1:39

Tutorial1:39

Incident Management with Augment Cosmos

Software Engineer Sophie Reynolds shows how the team uses Cosmos to begin incident triage before the on-call engineer opens their laptop. The agent correlates logs, metrics, recent deploys, Kubernetes state, Slack context, runbooks, and previous incidents to identify a probable cause with verifiable evidence. Engineers can then ask follow-up questions, drive a fix, and capture what the agent learned for the next incident. Learn more about Augment Cosmos at https://www.augmentcode.com/

From Customer Ticket to Pull Request with Augment Cosmos

1:23

Tutorial1:23

From Customer Ticket to Pull Request with Augment Cosmos

Product Lead Siyu Zhan shows how the team uses Cosmos to go from customer feedback into a review-ready pull request. Cosmos agents triage feedback in Slack, create and prioritize tickets, draft the code change, and trigger code review and verification—while bringing engineers in for spec review and final judgment. Learn more about Augment Cosmos at https://www.augmentcode.com/

1:40

Review1:40

Code Review with Augment Cosmos

Engineering Manager Alex Ding shows how the team uses Cosmos to keep code review from becoming the bottleneck as agents produce more code. A code review agent examines each pull request, a risk analyzer decides when human judgment is needed, and an end-to-end verifier checks that the change works as intended. The agents learn from previous reviews and human feedback, so review quality improves over time. Learn more about Augment Cosmos at https://www.augmentcode.com/

Who uses it

Real use cases, no hype

Automated Code Review

Deploy agent fleets to provide substantive first-pass reviews on every PR, reducing merge times and freeing senior engineers.

Ticket-to-PR Automation

Automatically investigate, implement, and test changes from a ticket description, handing off to the review loop.

Security Vulnerability Remediation

From Dependabot/Snyk alert to a reviewed patch, mapping blast radius and filing prioritized fixes without manual triage.

Incident Response & Triage

Automatically investigate alerts, draft timelines, and assemble context for on-call engineers before they join.

Large Project Execution

Orchestrate multiple agents to move a feature from design doc to shipped code across a complex codebase.

Recurring Workflow Automation

Build repeatable, event-triggered loops for tasks like dependency upgrades, onboarding, or migrations.

Developer Onboarding & Standardization

Ramp new engineers faster and enforce team coding standards across the organization at scale.

What's great

End-to-end SDLC automation platform with connected loops
Enterprise-grade security (SOC 2, CMEK, ISO 42001)
Flat, predictable pricing with no per-seat charges
Specialized, reusable agent 'Experts' for distinct tasks

Technical strengths

Deep codebase understanding via proprietary Context Engine
Native triggers for GitHub, GitLab, Slack, Jira, and webhooks
Flexible execution: managed cloud, your cloud, or local machines

Where it falls short

Complex platform; significant learning curve for full setup
Usage-based fees on top of subscription can surprise teams
Pricing scales up quickly for teams needing Enterprise features

Technical limitations

Agent orchestration may feel opaque; debugging failures isn't trivial
Vendor lock-in risk with deep integration into your SDLC workflows
Requires careful prompt and expert configuration for reliable results

For technical folks

The deep-dive specs

FAQ

Includes technical Q&A

The Standard ($20/mo) and Business ($100/mo) plans have a flat monthly fee for up to 50 seats. The fee includes a usage credit for LLM, Context Engine, and compute. You pay overages as you go, with no per-seat charges.