Amp (Research Preview)
ExtensionFreeThe frontier coding agent.
Capabilities8 decomposed
multi-model agentic code generation with mode-based routing
Medium confidenceGenerates new code from natural language requests by routing to different LLM backends based on user-selected mode: 'smart' mode uses Claude Opus 4.6 or GPT-5.4 for complex reasoning, 'rush' mode uses Claude Haiku 4.5 for fast execution, and 'deep' mode uses GPT-5.3 Codex with extended thinking for complex problem-solving. The agent maintains conversation threads within VS Code, allowing users to iteratively refine generated code through multi-turn dialogue without losing context.
Implements mode-based model routing (smart/rush/deep) within a single extension, allowing developers to toggle between speed and reasoning depth without switching tools or losing conversation context. The 'deep' mode with extended thinking is explicitly designed for complex problem-solving, differentiating from simpler code completion tools.
Offers built-in mode selection for speed vs. quality tradeoffs without requiring manual model switching, whereas GitHub Copilot uses a single model per request and Cursor requires separate configuration for different reasoning modes.
codebase-aware multi-file code modification with human review workflow
Medium confidenceModifies existing code across multiple files in the user's codebase by analyzing project structure and context, then presenting all proposed changes in a built-in review panel before application. The agent understands the full codebase scope (not just the current file) and can coordinate edits across related files. Changes are held in a staging state until the user explicitly approves them, preventing accidental overwrites.
Implements a mandatory human review panel for all multi-file changes before application, combined with codebase-wide context awareness. This differs from Copilot (which applies edits immediately in some modes) and Cursor (which has optional review). The agent maintains full project context rather than operating on isolated files.
Provides safer multi-file editing than Copilot by requiring explicit approval before changes are written, while maintaining codebase-wide context that Copilot lacks in many scenarios.
persistent conversation threading with code context preservation
Medium confidenceMaintains multi-turn conversation threads within the VS Code sidebar, allowing users to iteratively refine code generation and modification requests while preserving full context across turns. Each thread stores the conversation history, generated code, and applied changes, enabling users to reference previous requests and build on prior work without re-explaining context. Threads can be saved and shared (mechanism undocumented).
Implements persistent conversation threads as a first-class feature within the VS Code sidebar, allowing full context preservation across multiple code generation/modification requests. This differs from stateless code completion (Copilot) and from chat-based tools that don't maintain codebase context across turns.
Preserves both conversation history and code context across turns better than Copilot's stateless completions, while integrating directly into the editor sidebar rather than requiring a separate chat window like ChatGPT or Claude.ai.
extended-thinking code reasoning for complex problem-solving
Medium confidenceActivates a 'deep' mode that routes requests to GPT-5.3 Codex with extended thinking capabilities, enabling the agent to reason through complex coding problems step-by-step before generating solutions. This mode is designed for problems that require multi-step reasoning, architectural decisions, or deep analysis of existing code. Extended thinking adds latency but produces higher-quality solutions for difficult problems.
Explicitly exposes extended thinking as a selectable mode ('deep') within the agent, allowing developers to opt-in to slower but more thorough reasoning for complex problems. This is distinct from tools that use extended thinking transparently or not at all.
Provides explicit control over reasoning depth (smart/rush/deep modes) whereas Copilot uses a single model per request, and Cursor requires separate configuration or prompting to trigger deeper reasoning.
terminal-integrated coding agent with undocumented context passing
Medium confidenceIntegrates with the VS Code terminal to enable the agent to receive context from terminal output, error messages, and command execution results. The agent can use this terminal context to generate fixes, debug issues, or provide recommendations based on actual runtime behavior. The specific mechanism for passing terminal context to the agent is completely undocumented.
Explicitly mentions terminal integration as a core feature ('coding agent for your editor and terminal') but provides zero documentation on implementation, creating a significant gap between advertised capability and documented behavior.
Attempts to bridge editor and terminal contexts in a single agent, whereas Copilot and Cursor primarily operate on code files without explicit terminal integration.
opinionated agent design with no backward compatibility guarantee
Medium confidenceImplements an explicitly opinionated design philosophy that prioritizes forward progress and feature iteration over backward compatibility. The agent makes specific architectural choices about which features to include/exclude and explicitly states 'No backcompat, no legacy features' as a design principle. This allows rapid iteration and feature changes but means breaking changes can occur between versions without deprecation warnings.
Explicitly embraces breaking changes and lack of backward compatibility as a design principle, differentiating from most production tools that prioritize stability. This is a meta-capability about the tool's evolution strategy rather than a user-facing feature.
Prioritizes innovation velocity over stability, whereas Copilot and Cursor maintain backward compatibility and stable APIs for enterprise customers.
freemium model with undocumented paid tier and quota system
Medium confidenceOffers free access to the agent with an undocumented pricing model for advanced features or higher usage. The free tier provides access to the agent's core capabilities, but specific quotas, rate limits, and paid tier features are not documented. The extension is installable at no cost, but usage-based or feature-based pricing may apply.
Offers free access to a frontier coding agent without documented pricing or quota limits, creating uncertainty about long-term cost of ownership. This is unusual for AI-powered tools that typically have clear pricing from the start.
Free entry point is more accessible than GitHub Copilot ($10/month) or Cursor (paid), but lack of pricing transparency makes it harder to evaluate total cost of ownership.
vs code sidebar-based agent ui with activity bar integration
Medium confidenceProvides a dedicated sidebar panel in VS Code for agent interaction, accessible via an Amp icon in the activity bar. The sidebar serves as the primary UI for issuing natural language requests, viewing conversation threads, and managing agent state. This integration keeps the agent accessible without requiring separate windows or applications.
Integrates agent as a native VS Code sidebar panel rather than a separate window or external application, keeping the agent context within the editor environment. This is similar to Copilot Chat but distinct from external tools like ChatGPT or Claude.ai.
Keeps agent interaction within VS Code sidebar, reducing context switching compared to external chat tools, while providing more persistent visibility than Copilot's inline suggestions.
Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.
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[Discord](https://discord.gg/pAbnFJrkgZ)
Codebuddy
Codebuddy AI-assistant.
copilot
Best For
- ✓solo developers building features quickly
- ✓teams wanting to standardize on Claude or GPT models without managing separate API keys
- ✓developers who want to toggle between fast iteration and deep reasoning without context loss
- ✓teams requiring code review workflows before AI-generated changes are applied
- ✓developers working on large codebases where single-file edits are insufficient
- ✓projects where accidental overwrites are high-risk (production code, shared files)
- ✓developers building features incrementally over multiple requests
- ✓teams documenting how code was generated for knowledge transfer
Known Limitations
- ⚠Model selection mechanism is undocumented — unclear if modes are user-selectable per-request or globally configured
- ⚠Model names (GPT-5.4, Claude Opus 4.6) do not match current public model naming conventions, suggesting documentation may be aspirational or outdated
- ⚠No documented support for custom models or local LLM backends
- ⚠Conversation threads are stored server-side with unknown retention policy and privacy guarantees
- ⚠Research Preview status means API and model routing logic may change without notice
- ⚠Review panel UI/UX details are undocumented — unclear how diffs are visualized or how granular approval is (per-file, per-change, all-or-nothing)
Requirements
Input / Output
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The frontier coding agent.
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