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Amp Review: Sourcegraph's Agentic CLI That Thinks Like a Senior Engineer

Amp is Sourcegraph's terminal-native agentic coding tool, built to navigate and modify large codebases with the precision of a senior engineer. It leverages code intelligence to reason about your entire repository before touching a single line.

reviewed by Raşit Akyol April 15, 2025 updated September 5, 2026

Documented evidence

rubric editorial-review-v1

This review is grounded in documented sources and repository analysis. It does not claim a unique hands-on reproducibility record.

Sources checked

Verdict

Amp's code intelligence foundation makes it the most precise agentic coding CLI for large codebases — if you live in the terminal and work on complex systems, it is the tool to beat.

85/100

overall

Speed87
Privacy83
Dev Experience84

What Amp Does

Sourcegraph has spent over a decade building some of the most sophisticated code intelligence infrastructure in the industry. Their universal code search and code navigation products power developer workflows at some of the largest engineering organizations in the world. Amp is what happens when a company with that depth of codebase understanding turns its attention to building an AI coding agent. The result is a tool that approaches your codebase differently than any other agent on the market.

Code Intelligence and Architecture

Amp is a command-line tool. This is an intentional, principled choice, not a resource constraint. Sourcegraph's thesis is that the terminal is where developers have the most control and context about their environment. In a terminal, you are already in the right directory, already authenticated to your services, already operating in your chosen shell with your aliases and environment variables. An agent that lives in the terminal inherits all of that context automatically.

The core differentiation of Amp is its use of Sourcegraph's code intelligence layer. Before Amp writes a single line of code, it uses precise code navigation — go-to-definition, find-references, call graphs, type hierarchies — to build a mental model of the relevant parts of your codebase. This is qualitatively different from how most AI agents approach codebases. Other tools either read every file (expensive and often irrelevant) or rely on fuzzy semantic search (fast but imprecise). Amp uses the same symbol-level precision that Sourcegraph's search product is known for.

Getting Started, Planning, and Execution

Starting Amp is as simple as running `amp` in your project directory. A conversational interface appears in the terminal where you can describe what you want to accomplish. Amp acknowledges the request, asks any clarifying questions it needs, and then begins its investigation phase — navigating the codebase to understand the context before proposing a plan. The investigation is visible: you can watch Amp trace symbol definitions, read file contents, and build its understanding in real time.

The planning phase is Amp's most distinctive feature. Before making any changes, Amp produces a structured plan: which files will be modified, what changes will be made to each, and why each change is necessary. The plan is presented in the terminal and you can approve, modify, or reject it before execution begins. This plan-then-execute approach means you are never surprised by the changes Amp makes — you understand the full scope of the operation before a single file is touched.

Plan execution is careful and methodical. Amp makes changes file by file, running any validation it can after each change. If your project has a TypeScript compiler, Amp will run `tsc` after each file modification to check for type errors. If you have a test suite configured, Amp can run relevant tests as it goes. This incremental validation means errors are caught immediately, while the context of what caused them is still fresh, rather than discovering a cascade of failures at the end.

Polyglot Codebase Understanding

Amp's understanding of codebases with polyglot architectures is a notable strength. Modern applications often combine a TypeScript frontend, a Python backend, and Go services, all within the same repository. Amp handles cross-language features gracefully — it can trace a data model from a TypeScript API client through a REST API contract to the Python implementation and the underlying database schema, understanding all the translations that happen along the way.

Diff Review and Git Integration

The diff review workflow in Amp is designed for developers who take code quality seriously. After executing a plan, Amp presents the full diff in a unified format before finalizing. You can review every change, ask Amp to explain specific decisions, request modifications, or approve the entire changeset. Amp supports iterative refinement — if you want a different approach to a specific part of the implementation, you can say so and Amp will revise that section while keeping the rest of the changeset intact.

Git integration is tight and considered. Amp respects your git configuration, understands branch contexts, and can generate commit messages that accurately describe the changes it made. When working on a feature that touches multiple logical concerns, Amp can split its changes into multiple focused commits rather than one monolithic commit. For teams that practice atomic commits for bisectability and code review clarity, this feature alone has significant practical value.

Sourcegraph Platform Integration

Amp's integration with the broader Sourcegraph platform unlocks capabilities not available to standalone agents. If your organization uses Sourcegraph Enterprise, Amp can leverage your company's code graph — searching across all internal repositories, not just the one currently checked out. This means Amp can find examples of how your team has solved similar problems before, reference internal libraries you might not have known about, and avoid duplicating patterns that already exist in your codebase.

Performance and Pricing

Performance is one of Amp's genuine strengths. The code intelligence layer is highly efficient — rather than loading large amounts of code into context, it uses precise symbol navigation to pull in exactly the relevant code. This means Amp's responses are fast, its token usage is efficient, and it can work effectively on large codebases that would cause other tools to struggle with context limits.

Pricing is consumption-based, tied to the underlying model usage plus Sourcegraph's code intelligence services. There is a free tier with limited monthly credits that allows meaningful evaluation. Individual paid tiers start at $20 per month, with team plans providing additional credits, collaboration features, and the option to connect to Sourcegraph Enterprise for cross-repository intelligence. The consumption model means heavy users should budget carefully, as complex multi-file operations can consume significant credits.

Limitations and Setup

There are real limitations to acknowledge. Amp's terminal-only interface is a genuine barrier for developers whose workflow is deeply integrated with a graphical IDE. Reviewing diffs in the terminal is workable but less comfortable than the side-by-side diff views available in editors like Cursor or VS Code. Developers who rely heavily on visual debugging, graphical profilers, or designer collaboration features will find Amp's terminal focus constraining.

The setup process, while not difficult, requires more configuration than installing a plugin. Amp needs to be told about your project's structure, test commands, and build processes during initial setup. This configuration pays dividends in the quality of Amp's subsequent behavior, but it is an investment that needs to be made upfront. Teams adopting Amp at scale will want to establish standard configuration templates to reduce per-developer setup friction.

Competitive Positioning

Comparing Amp to other agentic tools reveals its distinctive positioning. Against Claude Code, Amp's code intelligence layer gives it a precision advantage in navigating large codebases, while Claude Code benefits from Claude's broader reasoning capabilities. Against Devin, Amp is more lightweight and developer-controlled — Devin aims for full autonomy, while Amp keeps the developer in the loop at every decision point. Against Aider, Amp offers more sophisticated codebase navigation at the cost of less configurability.

The Bottom Line

Amp is a tool for a specific kind of developer: one who values precision over convenience, who works in large and complex codebases, and who wants an agent that understands code the way a senior engineer does — by tracing definitions, reading types, and following call chains — rather than by pattern-matching against training data. If that describes your work, Amp is likely the most technically capable agent available for your use case. The combination of Sourcegraph's code intelligence heritage and modern LLM reasoning creates an agent that genuinely elevates what's possible in automated software development.

Pros

  • Code intelligence enables precise symbol-level codebase navigation
  • Plan-then-execute approach prevents unexpected changes
  • Polyglot codebase support is best-in-class
  • Incremental validation catches errors immediately during execution
  • Cross-repository intelligence available with Sourcegraph Enterprise
  • Efficient token usage through targeted code retrieval

Cons

  • Terminal-only interface is limiting for GUI-heavy workflows
  • Initial configuration requires meaningful upfront investment
  • Credit-based pricing can get expensive for complex operations
  • Smaller community and ecosystem than more established tools

View Amp on aicoolies

Pricing, platforms, and community stacks — explore the full tool page

Comparisons with Amp

Amp logo
Amp
vs
goose ai
Goose

Amp vs Goose — Multi-Surface Agent or Open Local MCP Agent?

Amp and Goose both help developers run agentic coding workflows, but they emphasize different product shapes. Amp is Sourcegraph’s multi-surface coding agent spanning terminal, web, macOS/iOS, and IDE-connected threads, with freemium plans and BYOK options. Goose is Block’s AAIF-aligned open-source local agent — Desktop and CLI — built around MCP extensions, recipes, and model-agnostic BYOK or Ollama. Existing Scores: Amp overall 85 (Score date 2026-03-25); Goose overall 84 (Score date 2026-03-29). Overall is close; choose on multi-surface commercial agent vs open local MCP depth. Treat the scoreboard as review evidence with those dates, not the whole decision.

Amp logo
Amp
vs
Grok logo
Grok Build

Amp vs Grok Build — Code-Intelligence CLI or xAI Terminal Agent?

Amp and Grok Build both compete as terminal-native coding agents, but they optimize different desks. Amp is Sourcegraph’s agentic coding tool for local and remote threads — codebase-aware edits plus Orbs remote machines and Dial mode switching. Grok Build is xAI’s terminal-first coding agent with TUI/CLI controls, subagents, worktrees, headless runs, and cross-session Memory. Use Amp when you want Sourcegraph-line code intelligence plus Orbs/Dial workflows. Use Grok Build when you want an xAI-native shell agent. Existing aicoolies Scores: Amp overall 85, speed 87, privacy 83, developer experience 84 (Score date 2026-03-25); Grok Build overall 82, speed 84, privacy 72, developer experience 80 (Score date 2026-05-28). Choose on product shape and ecosystem fit first; the scoreboard is secondary review evidence with those dates.

Amp logo
Amp
vs
Cline logo
Cline

Amp vs Cline — Terminal Code Intelligence or Open-Source VS Code Agent?

Amp and Cline both deliver agentic coding help, but they live in different shells. Amp is Sourcegraph’s commercial agentic coding tool with local threads, Orbs remote machines, and Dial modes. Cline is an Apache-2.0 VS Code coding agent that reads/edits files, runs commands, and asks for explicit approval unless auto-approve is on, on a BYOK model path. Use Amp when you want Orbs/Dial and Sourcegraph-line code intelligence. Use Cline when you want an open-source VS Code agent with human-in-the-loop control. Existing aicoolies Scores (both Score-dated 2026-03-25): Amp overall 85, speed 87, privacy 83, developer experience 84; Cline overall 84, speed 78, privacy 88, developer experience 86. Overall is nearly tied — choose on product shape, licensing, and current surfaces first; the scoreboard is secondary review evidence with those dates.

Amp logo
Amp
vs
Codex logo
Codex

Amp vs Codex — Terminal Code Intelligence or OpenAI Multi-Surface Agent?

Amp and Codex both compete as AI coding agents, but they start from different desks. Amp is Sourcegraph’s agentic coding tool for large-repo edits with Orbs remote machines and Dial mode switching. Codex is OpenAI’s coding agent across app, editor, terminal, and cloud-style surfaces, usually via ChatGPT plans or API-key CLI/SDK paths. Use Amp when you want Sourcegraph-line code intelligence plus Orbs/Dial. Use Codex when you want OpenAI’s multi-surface loop. Existing aicoolies Scores (both Score-dated 2026-03-25): Amp overall 85, speed 87, privacy 83, developer experience 84; Codex overall 80, speed 72, privacy 68, developer experience 79. Choose on product shape and current surfaces first; the scoreboard is secondary review evidence with those dates.

View 2 more comparisons

Alternatives to Amp

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Codex

Top Pick

OpenAI coding agent for app, editor, terminal, and cloud work

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paid

Open-source autonomous coding agent for VS Code

Cline is an Apache-2.0 open-source AI coding agent runtime for editor, terminal, and SDK workflows. It reads and edits files, runs commands, uses browsers, plans then acts, and requires explicit approval for each step unless users enable auto-approve. Current Cline sources show 8M+ installs, 63.6k+ GitHub stars, BYOK/provider flexibility, local model support, MCP, plugins, hooks, and Enterprise governance.

Open Source
Claude Code logo

Claude Code

Top Pick

Anthropic's agentic coding CLI

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freemium
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Cursor

Top Pick

The AI-first code editor

AI-first code editor built as a VS Code fork that deeply integrates LLMs into every part of the development workflow. Features Tab autocomplete with multi-line predictions, Cmd+K inline editing, AI chat with full codebase awareness, and Agent mode for autonomous multi-file edits with terminal execution. Supports GPT-4, Claude, and more with automatic context from project files and docs. Includes privacy mode for SOC 2 compliance. The leading AI-native IDE with 100K+ paying users.

freemiumTelemetry

AI pair programming in your terminal

Terminal-based AI pair programmer with deep git integration. Auto-commits changes with meaningful messages and creates repository maps for navigating large codebases. Works with Claude, GPT, DeepSeek, and local models. One of the most popular open-source AI coding tools, known for its reliability, broad model support, and seamless command-line workflow.

Open Source

Open-source extensible AI agent by Block

Autonomous coding agent from Block (Square) that works with any LLM through MCP-first extensibility. Apache 2.0 licensed with 47K+ GitHub stars and a Linux Foundation AAIF founding project. Designed for terminal-based workflows with deep tool integration, making it a strong open-source option for developers who want agent-assisted coding without vendor lock-in.

Open Source

FAQ

How does Amp's terminal agent integrate with Sourcegraph Code Graph?

Pairs terminal CLI execution with Sourcegraph's Code Graph API, querying cross-repository AST symbol definitions and call hierarchies to inject precise context.

How does Amp execute multi-step code synthesis and verification?

Generates localized AST unified diffs, running local linters and compiler tests after edits to catch errors and repair code iteratively before finalizing patches.

How does Amp differ from Cursor and Aider?

Runs directly in local developer terminals with native compiler access, leveraging Sourcegraph SCIP indexing to handle massive enterprise monorepos without hallucination.

How does Amp optimize tokens in large monorepos?

Filters context through SCIP precise code intelligence, including only related function signatures and interface contracts instead of dumping raw whole files.

Sources & verification

Sources checked
Content verified

Verification dates are editorial checks. Routine CMS saves and automatic updatedAt timestamps do not advance them.