Harness has acquired select assets from Augment Code, including Cosmos and the Auggie CLI products, along with the Code Context Engine technology. The Augment Code team will join Harness to accelerate development of its Autonomous SDLC Platform. Cosmos will become the Harness Cosmos Software Factory Agent, automating engineering work from idea to code. It uses AI agents to plan changes, write code and tests, and open pull requests. Harness's existing agents then handle software delivery, security testing, runtime protection, and cost management. The acquisition connects Augment's Code Context Engine with Harness's Software Delivery Knowledge Graph, providing insights across the full software development lifecycle. This integration allows agents to understand both what is being built and what happens after deployment. Harness Cosmos is now available on the Harness platform.

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Augment Code review 2026: best AI for Large codebases? Most AI coding tools struggle when your codebase gets large. Thousands of interdependent files, legacy code mixed with new patterns, multiple services calling each other - and the AI starts losing the plot. Augment Code was built specifically for this problem. Its context engine is designed to understand messy, real-world enterprise codebases better than general-purpose tools. In 2026, Augment Code made a significant pivot: it retired individual plans in June and launched Intent, a standalone multi-agent orchestration product. This review covers both Augment Code's core context engine and the Intent product, their pricing, and who should (and shouldn't) pay for them. What is Augment Code? Augment Code is an AI coding tool built for large, complex codebases. Unlike tools that rely on open files or a limited context window to understand your code, Augment built a proprietary Context Engine that indexes your entire codebase and understands how components relate - even across large monorepos and microservice architectures. The core value proposition: when you ask Augment to implement a feature or explain some behavior, it already knows where the relevant code lives, which services interact, and what the existing patterns are. That context means less hallucination, fewer "it wrote something that doesn't fit the codebase" moments, and less time providing background. Intent: the multi-agent product. In early 2026, Augment launched Intent - a standalone macOS desktop application that orchestrates multiple AI agents working in parallel through isolated git worktrees. The architecture uses three agent types: * Coordinator - Breaks down the request, manages the plan, and routes tasks * Implementor - Writes code in an isolated git worktree * Verifier - Checks the output for correctness against the spec In May 2026, Augment added the Prism model router, which automatically routes each turn to the most appropriate model - matching quality against cost to reduce per-task expenses by 20-30% compared to running every agent on the same model. The multi-agent architecture is particularly powerful for complex tasks: while one agent implements a component, another can be writing tests, and the Coordinator can be refining the next task. In practice, sessions that might take minutes in a single-agent setup can complete in parallel. What Augment Code does well. Context at scale. This is Augment's defining advantage. On a large codebase - 500K+ lines of code, dozens of services - Augment's context engine provides understanding that tools like Cursor simply don't offer out of the box. When you ask it to add a feature, it already knows which other components will be affected. When you ask it to explain a bug, it can trace through multiple layers without being prompted. For enterprise teams where onboarding takes months because the codebase is so interconnected, Augment can dramatically reduce that ramp time. Multi-agent parallelism. Intent's isolated git worktree approach means multiple agents can work simultaneously without stepping on each other. A complex feature that touches five areas of the codebase can be implemented in parallel rather than serially. The quality bar also rises: the Verifier agent catches issues that a single-agent pass often misses. Prism model routing. Automatically matching model choice to task complexity means you're not paying GPT-4 prices for tasks that a cheaper model handles equally well. The 20-30% cost savings compounds over a busy week. Enterprise codebase focus. If your codebase is the kind that makes generic AI tools guess wildly, Augment is the most credible alternative in 2026. The context engine is its genuine differentiator. What Augment Code does less well. Credit costs on heavy sessions. Augment adopted credit-based pricing after retiring flat-rate plans in June 2026, and the community response has been mixed. A typical Coordinator + three Implementor session on Sonnet costs around 1,200-1,500 credits; on Opus, 2,500-3,000+. For heavy users, this adds up meaningfully. The Prism router helps, but Intent can still be expensive for complex multi-agent sessions. macOS only for Intent. Intent is a macOS desktop application. Windows and Linux developers are excluded from the multi-agent workflow, which is a significant limitation for enterprise teams with mixed operating systems. Steep learning curve. The multi-agent, worktree-based workflow is more complex than Cursor's straightforward chat interface. There's a setup cost to understanding how Coordinator, Implementor, and Verifier interact, how to structure requests for best results, and how to monitor agent sessions effectively. Overkill for small codebases. If your codebase is under 50K lines and relatively well-organized, Augment's context engine advantage shrinks considerably. The premium cost is harder to justify when Cursor's standard context window handles your codebase fine. Pricing. Augment Code's pricing shifted significantly with the June 2026 changes. Current structure: | Plan | Price | Notes | | Community | Free (limited) | Basic features, context limited | | Pro | ~$20/mo | Core context engine + Intent access | | Business | Custom | Team pricing, priority support | Credit consumption for Intent sessions: * Sonnet-based session: ~1,200-1,500 credits * Opus-based session: ~2,500-3,000+ credits * Typical savings with Prism router: 20-30% per session See its Augment Code Pricing 2026 breakdown for full details on credit costs and plan comparisons. Augment Code vs Cursor. | / | Augment Code | Cursor | | Best for | Large enterprise codebases | Daily editing, all codebase sizes | | Context depth | Whole codebase, indexed | Open files + limited context window | | Multi-agent | Yes (Intent) | Yes (up to 8 parallel) | | macOS only | Intent yes | No (cross-platform) | | Pricing | Credit-based | Subscription | | Learning curve | Higher | Lower | | Ecosystem | Smaller | Large | Cursor is the better default for most developers. Augment Code makes sense when codebase size and complexity make Cursor's context insufficient. The two tools appeal to different ends of the complexity spectrum. Who should use Augment Code? Use Augment Code if: * Your codebase is large (200K+ lines) and interconnected * You work on enterprise software where AI context confusion is a daily friction * You're on macOS and can access Intent's multi-agent workflow * Your team is willing to invest in a higher learning curve for better results on complex tasks Look elsewhere if: * Your codebase is small or medium-sized * You're on Windows or Linux (Intent is macOS only) * You need a simple, fast daily coding tool * You're sensitive to per-session credit costs on heavy workloads Verdict. Augment Code is the strongest option in 2026 for developers working in large, complex codebases where standard AI tools lose context. The Context Engine is a genuine differentiator, and Intent's multi-agent workflow with Prism model routing is technically impressive. The catches: credit pricing that can add up for heavy Intent users, macOS-only access for the multi-agent product, and a higher learning curve than simpler tools. For small-to-medium codebases, Cursor is a better default. Rating: 4.0/5 - Excellent for its target audience (large enterprise codebases), overengineered for everyone else. Last reviewed and updated: September 7, 2026 Pricing and feature information may change. Visit the official product website for the latest details. Find the best tool for you. Compare features, pricing, and reviews to find the perfect tool for your workflow.