Augment Code

Augment Code is aimed at a harder problem than single-file completion: helping engineering teams work across large, living codebases. The current vendor pages position Augment around a Context Engine and the Cosmos agent platform, with agents involved in triage, authoring, review, and verification. The site also publishes outcome claims such as a 4x ship-cycle improvement, 70%+ pages resolved before an on-call engineer joins, and 30% fewer repetitive engineering hours. Treat those numbers as vendor claims, not guarantees, but they make the positioning clear: Augment is selling operational software throughput, not just a faster tab-complete.

The fetched pricing page was specific. It listed Indie at $20 per month with 40,000 credits, Standard at $60 per developer per month with 130,000 credits, Max at $200 per developer per month with 450,000 credits, and Enterprise as custom. The page also referenced Context Engine, MCP and native tools, SOC 2 Type II, no-AI-training language, auto top-up credits, and code-review usage. Those details matter for buyers because agentic coding can become expensive when teams run long tasks, code review loops, or incident investigations.

Augment should be compared with Cursor Agent, GitHub Copilot Agents, Claude, Sourcegraph Cody, and Aider. Cursor is more editor-native, Copilot is GitHub-native, Claude Code is terminal-first, Cody leans on Sourcegraph’s code-search context, and Aider is open-source and Git-aware. Augment’s best case is a team with sprawling services, old migrations, ownership boundaries, and enough onboarding or incident work that deep context has real economic value.

Run a pilot on one service before rolling out broadly. Use three benchmark tasks: a small feature, a bug with a failing test, and a codebase question requiring cross-file context. Track accepted changes, review comments, CI failures, time to merge, and credit burn. Augment is most compelling when it reduces reviewer burden and context-hunting time. If your repositories are small or your team mostly needs lightweight autocomplete, the higher tiers may be unnecessary.

Implementation checklist: connect one representative repository, document the credit budget, and decide which tasks count as success before inviting the whole engineering team. Require branch protection, CI, and code-owner review. For each benchmark task, record the prompt, files changed, tests run, credits used, and reviewer feedback. Separate “helped me understand the system” from “generated mergeable code,” because both are valuable but they justify different spending. Security review should cover repository retention, model-training policy, SSO, audit logs, and whether generated code review features are included in the selected tier. Expand only when Augment reduces context-hunting and review effort, not merely when demos look impressive.