Augment Code
4.9Freemium400
Editorial matchup · June 2026
Augment Code vs Sourcegraph: Which AI Tool Is Better in 2026?
Side-by-side comparison of Augment Code and Sourcegraph — pricing, features, and use cases. Reviewed by our editorial team in Jun 2026.
Use-case score 2–2Updated Jun 2026
Developer Tools
Sourcegraph
4.9Paid450
Augment Code optimizes for semantic understanding while Sourcegraph Cody optimizes for integration with existing search infrastructure. Both are enterprise-focused tools, but they approach large codebase intelligence from fundamentally different angles.
Augment Code treats context as an execution problem, loading up to 400,000 to 500,000 files into active memory and indexing changes in real time, with autonomous agents that can reason across the entire system, open coordinated pull requests, and handle orchestration of complex changes.
Sourcegraph Cody builds on its semantic code graph using embeddings to map every definition and reference in your codebase; when you ask where a function is called, you get pinpoint matches across repositories in milliseconds.
Starting in July 2025, Sourcegraph made a strategic market decision to completely terminate Cody Free and Cody Pro plans and pivot into a pure enterprise tool, fundamentally narrowing its addressable market.
This pricing shift matters: Augment offers entry paths at the Indie tier, while Sourcegraph now requires enterprise commitment.
For teams managing legacy systems or coordinating changes across microservices, Augment's autonomous agents and cross-repository context provide clear value when your team's velocity gets limited by coordination overhead; if developers spend significant time manually orchestrating changes or waiting for cross-team reviews, the orchestration capabilities can dramatically improve cycle times.
For teams whose primary challenge is exploration and navigation, Sourcegraph Cody is the choice when discovery and navigation within complex codebases is the main pain point.
Both hold comparable security certifications—Augment Code claims ISO/IEC 42001 and SOC 2 Type II certifications with flexible deployment options, while Sourcegraph provides ISO/IEC 27001:2022 certification that is independently audited.
The decisive factor remains architectural fit: Augment shines when autonomous multi-file reasoning across 400K+ file codebases is the blocker; Cody excels when deep search and context retrieval from a well-indexed infrastructure is already in place.
Multi-service refactoring at scale
Augment Code
Augment Code's Context Engine analyzed the auth service, mapped the token flow across three microservices, identified that the checkout service used a different JWT validation library, and suggested where to add logging in two minutes versus three hours of manual debugging.
Code search and discovery in existing infrastructure
Sourcegraph
Cody supports multi-repository context, allowing search across up to 10 repositories simultaneously for relevant information, with flexibility to get comprehensive and accurate responses by leveraging information across multiple codebases.
Team coordination and agent orchestration
Augment Code
Intent by Augment Code stood out for keeping multiple agents aligned because its living spec acts as a shared, continuously updated plan, and required the least manual reconciliation when parallel work touched shared contracts.
Section 01
Best for what
5 use cases scored. Augment Code wins 2, Sourcegraph wins 2.
- Augment CodePricing value
Augment Code publishes a starting price of $30; Sourcegraph does not.
- Augment CodeFree tier
Augment Code offers a free tier; Sourcegraph is paid only.
- EvenUser ratings
Both sit near 4.9 / 5 across user reviews.
- SourcegraphReview volume
Sourcegraph has 207 ratings vs 182 on the other.
- SourcegraphEditorial standing
Sourcegraph ranks in our Rising tier; Augment Code sits in the unranked tier.
Section 02
Pros & cons
Where each tool earns its rating — and where it falls short.
Augment Code
Developer ToolsPros
- Augment's Context Engine understands entire codebases including architecture, dependencies, and legacy code across up to 500,000 files, enabling autonomous agents to reason about cross-service dependencies that simpler keyword search misses.
- Agent analyzes your request against your codebase and creates an actionable plan; every action is visible and reversible, with checkpoints saving work at every step.
- In Augment's benchmarks, improved agentic coding performance exceeded 70% across Claude Code, Cursor and Codex.
- Delivers enterprise-grade security with SOC 2 Type II, ISO/IEC 42001, zero data retention, CMEK encryption, and on-prem deployment options.
- Adding Context Engine improved agent performance by 70%+ across Claude Code, Cursor, and Codex, and works with any MCP-compatible agent.
- Switch between Claude, GPT, and other frontier models based on the task without changing workflow.
Cons
- At Standard tier pricing, it's worth it only if you work across large codebases and actively optimize model selection; for everyone else, Copilot Pro at lower cost is the smarter starting point.
- Credit system burns fast; the pricing model migration eroded trust, and moderate users feel penalized.
- No data available regarding credit consumption rates, making it impossible to determine whether tiers provide adequate coverage for typical usage patterns, and risks significant overage charges at premium rates for power users.
- Supports VS Code and JetBrains IDEs; requires managing plan tiers and credits.
- Entry-level Indie plan's 40,000 monthly credits may constrain teams doing consistent agentic work.
- Standard and Max plans share a hard 20-user ceiling; teams planning to scale beyond this must negotiate Enterprise regardless.
Augment Code
Developer ToolsPros
- Augment's Context Engine understands entire codebases including architecture, dependencies, and legacy code across up to 500,000 files, enabling autonomous agents to reason about cross-service dependencies that simpler keyword search misses.
- Agent analyzes your request against your codebase and creates an actionable plan; every action is visible and reversible, with checkpoints saving work at every step.
- In Augment's benchmarks, improved agentic coding performance exceeded 70% across Claude Code, Cursor and Codex.
- Delivers enterprise-grade security with SOC 2 Type II, ISO/IEC 42001, zero data retention, CMEK encryption, and on-prem deployment options.
- Adding Context Engine improved agent performance by 70%+ across Claude Code, Cursor, and Codex, and works with any MCP-compatible agent.
- Switch between Claude, GPT, and other frontier models based on the task without changing workflow.
Cons
- At Standard tier pricing, it's worth it only if you work across large codebases and actively optimize model selection; for everyone else, Copilot Pro at lower cost is the smarter starting point.
- Credit system burns fast; the pricing model migration eroded trust, and moderate users feel penalized.
- No data available regarding credit consumption rates, making it impossible to determine whether tiers provide adequate coverage for typical usage patterns, and risks significant overage charges at premium rates for power users.
- Supports VS Code and JetBrains IDEs; requires managing plan tiers and credits.
- Entry-level Indie plan's 40,000 monthly credits may constrain teams doing consistent agentic work.
- Standard and Max plans share a hard 20-user ceiling; teams planning to scale beyond this must negotiate Enterprise regardless.
Sourcegraph
Developer ToolsPros
- Uses Sourcegraph's advanced Search API to pull context from both local and remote codebases, providing context about APIs, symbols, and usage patterns from across entire codebase.
- Built with LLM choice in mind versus locked into a single proprietary LLM; allows enterprises to choose from multiple LLM options and deploy them in secure environments via bring-your-own-key.
- Multi-repository context allows searching up to 10 repositories simultaneously for relevant information, with flexibility for comprehensive responses across multiple codebases.
- VS Code and JetBrains plugins integrate without requiring IDE changes; Web IDE access adds flexibility for code review scenarios during pull request reviews.
- Supports cloud, self-hosted, and air-gapped deployments with zero-retention policy where LLMs do not retain data from user requests beyond time required to generate output.
- Successful deployment to enterprises with large, complex codebases such as Palo Alto Networks and Leidos.
Cons
- Completely terminated Cody Free and Cody Pro plans as of July 23, 2025, requiring enterprise commitment with no individual on-ramp.
- No agentic coding capabilities for terminal execution or browser automation; tools like Cline or Cursor Agent mode are ahead.
- Enterprise tier at stated pricing per user is expensive, and outside of large-codebase scenarios, the core coding experience does not stand out against cheaper tools.
- Retrieval quality depends heavily on existing Sourcegraph indexing configuration; teams with well-tuned deployments see immediate benefits but teams new to Sourcegraph face a learning curve.
- Sourcegraph's main forward investment is Amp, so Cody is targeted at enterprise buyers, and value shows up at enterprise codebase scale.
- G2 users report infrastructure constraints with rate-limiting issues from LLM providers resulting in gateway errors, slow performance causing frustration due to delays and frequent crashes, and poor UI design creating adoption friction.
Section 03
At a glance
Every spec on one page. Live-pulled from each tool's detail page.
- PricingFree trial; Developer plan from $30/month; Pro and Team plans for higher usage; Enterprise with SSO, audit logs, and on-prem options. Augment Code is the software agent company, used by serious engineering teams.Inquire
- Pricing modelFreemiumPaid
- Free tierYesNo
- Free trialNoNo
- Rating4.9 / 5 (182 ratings)4.9 / 5 (207 ratings)
- Saves400450
- CategoriesDeveloper Tools, ProductivityDeveloper Tools
- VerifiedYesYes
- Top 100 tier—Rising
- Last updatedJun 2026Jun 2026
Frequently asked
Augment Code vs Sourcegraph FAQs
Quick answers to the questions readers ask before picking between these two.
Does Augment Code work as a Cody replacement if we already use Sourcegraph?
Partially. Augment optimizes for semantic understanding, Cody for integration with existing search infrastructure. If your team already uses Sourcegraph heavily, Cody is the natural choice. However, Augment's Context Engine is available as an MCP service for any MCP-compatible agent, improving performance by 70%+ and can connect to Augment's hosted MCP for context across all repositories, so you can add Augment's semantic search layer without replacing Cody.
What's the real cost difference between Augment and Cody once we scale?
Augment uses credit-based consumption pricing that varies by model and task complexity; a single small task on Sonnet 4.5 costs approximately 293 credits. Cody Enterprise is per-user annual pricing with no usage overage. At enterprise scale, neither vendor publishes detailed pricing, so actual costs require direct negotiation with sales teams for reliable comparison.
Can Cody open pull requests autonomously like Augment Code agents?
No, not in native Cody. The 2026 direction is from tool that posts comments to agent that takes actions, and the next generation of AI code review tools won't stop at flagging a missing test but will write it, open a follow-up pull request, and run it through CI. Sourcegraph former Pro customers received credits toward Sourcegraph's newer agentic product, Amp, which has those capabilities, but Cody remains primarily a chat and completion assistant.
Which tool is better for onboarding new developers to a large codebase?
Cody is better for everyday coding with deep codebase awareness, making it the natural fit for answering questions and exploration during onboarding. Augment excels at tasks where the developer already understands the problem and needs execution help. For pure discovery and questions, Cody's search-based architecture wins; for implementing changes that ripple across services, Augment wins.
Do both tools require a Sourcegraph instance to work?
Only Cody requires Sourcegraph infrastructure; it's built on top of Sourcegraph's code intelligence platform. Retrieval quality depends heavily on existing Sourcegraph indexing configuration. Augment is a standalone platform that integrates with existing toolchains independently. Augment's Context Engine MCP can connect remotely for context across all repositories without requiring Sourcegraph.
Which tool handles Python and TypeScript better?
Both tools support all languages equally well through their LLM backends. The difference lies in context retrieval, not language support. Cody works for any programming language because it uses LLMs trained on broad data and works great with Python, Go, JavaScript, and TypeScript code. Augment's Context Engine similarly handles all languages; the advantage comes from understanding cross-service dependencies, not from language-specific logic.
Bottom line
Choose Augment Code if your team manages 400K+ file codebases with complex cross-service dependencies, frequently coordinates multi-file changes across microservices, or needs autonomous agents to execute refactoring that currently requires manual orchestration.
The Context Engine's semantic understanding of architectural relationships delivers measurable value in legacy modernization, monorepo-to-microservices migration, and multi-repository dependency management. Teams at companies like Webflow, Kong, and Pigment depend on this capability.
Augment's credit-based pricing rewards efficient context retrieval and lets you start at the Indie tier, though Standard and Max tiers require careful credit management and planning.
Choose Sourcegraph Cody Enterprise if your organization has already standardized on Sourcegraph's code search and intelligence infrastructure, your primary challenge is helping developers navigate and ask questions about vast codebases (not autonomously refactoring them), and you need verified enterprise compliance with transparent security documentation.
Cody's 10-repository simultaneous search and deep integration with Sourcegraph's indexed infrastructure make it the logical choice for organizations already investing in that platform.
However, the July 2025 discontinuation of Free and Pro tiers means this is now an enterprise-only decision; there's no path for individuals or small teams to trial at scale.
If your team is smaller than 20 developers, working on a single repository, or lacks existing Sourcegraph infrastructure, neither tool is the natural fit. If you're evaluating from scratch, GitHub Copilot (broader IDE support, lower entry cost) or Cursor (faster autocomplete, simpler pricing) may prove more practical.
If you're an enterprise with teams already using both Sourcegraph search and needing autonomous agents, consider a hybrid approach: Cody for search and discovery, Augment's Context Engine as an MCP service for your existing agents (Cursor, Claude Code) to gain semantic understanding without full Augment adoption.
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