Amp

Agentic coding assistant for terminals and editors, powered by multiple frontier models.

5.0 (4)

レビュー: Daniel Nikulshyn·更新 2026年5月

Editor Integration CLI Coding Assistant Multi-Model Agentic AI Developer Tools Pay-As-You-Go

概要

Amp is an agentic coding tool that runs in your terminal and integrates with popular code editors, helping developers plan, write, refactor, and debug code through autonomous task execution. Instead of relying on a single model, it routes work across several frontier LLMs to pick capable models for different coding tasks. The service offers a free daily grant of $10 in usage credits, with pay-as-you-go pricing beyond that, so developers can experiment without an upfront subscription. It is aimed at engineers who want an AI collaborator embedded directly in their existing development workflow rather than a separate chat window.

主な機能

Agentic task execution for coding workflows
Terminal-based interface
Editor integrations
Multi-model routing across frontier LLMs
Daily free usage credits
Usage-based billing

ユースケース

Autonomous Refactoring from the Terminal

Engineers can delegate multi-step refactoring tasks to Amp directly from their terminal, letting the agent plan and execute changes across files without leaving the CLI.

In-Editor Debugging Assistance

Developers use Amp's editor integrations to diagnose and fix bugs inline, with the tool routing the task to a frontier model suited for code reasoning.

Low-Commitment AI Coding Trials

Teams evaluating agentic coding tools can leverage the $10 daily free credit and pay-as-you-go billing to experiment without committing to a subscription.

Multi-Step Feature Implementation

Amp can plan, write, and iterate on new features autonomously, picking capable models per subtask to handle planning, code generation, and testing steps.

メリット & デメリット

メリット

Works in both terminal and editors
Uses multiple frontier models for varied tasks
$10/day free usage grant to get started
Pay-as-you-go pricing with no fixed subscription
Designed for agentic, multi-step coding work

デメリット

Costs can scale with heavy usage
Requires comfort with CLI workflows
Quality depends on underlying third-party models
Less predictable billing than flat-rate tools

レビュー

5.0

4件の評価の平均。

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Tomáš Novák

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on daily free usage credits, and designed for agentic, multi-step coding work caught me off guard. still, I'd recommend giving it a real trial.

Margaret Whitfield

Does the job

Pretty happy overall. Editor integrations just works and pay-as-you-go pricing with no fixed subscription. but no dealbreakers — I'd recommend it to a friend without hesitating.

Joanna Kowalski

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on usage-based billing, and works in both terminal and editors caught me off guard. still, I'd recommend giving it a real trial.

Tariq Aziz

Skeptical, then convinced

I went in skeptical — most tools in this space overpromise. It actually delivers on daily free usage credits, and uses multiple frontier models for varied tasks caught me off guard. Less predictable billing than flat-rate tools is why this isn't a perfect score, still, I'd recommend giving it a real trial.

Q&A

How does Amp's pricing work and is there a free tier?

Amp uses pay-as-you-go, usage-based billing with no fixed subscription. Every day you get a $10 free usage grant to experiment, and you only pay beyond that. Costs can scale with heavy use, making billing less predictable than flat-rate tools.

Where does Amp run — terminal, editor, or both?

Amp runs in your terminal and also integrates with popular code editors, so it lives inside your existing development workflow rather than a separate chat window. This makes it well-suited to engineers comfortable with CLI-based tools.

What coding tasks is Amp designed for?

Amp is built for agentic, multi-step coding work — planning, writing, refactoring, and debugging code through autonomous task execution. It routes tasks across multiple frontier LLMs to pick capable models for different coding jobs.