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Curated ToolThis tool is part of our curated AI directory. We only include tools that meet our standards for relevance, usability and real-world value.

Amazon CodeWhisperer

Amazon CodeWhisperer is an AI coding assistant from AWS that generates real-time code suggestions in supported IDEs based on comments and existing code. It can support code refactoring by suggesting alternative implementations and includes security scanning to help detect vulnerabilities.
Code Generation & CompletionDebugging
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FYAI Score

8.0 / 10

FYAI rating based on features, pricing and integrations

Pricing:

Freemium

Best for:

Developers building, securing, and modernizing apps on AWS

Score Breakdown

  • Ease of use7.9 / 10
  • Features8.0 / 10
  • Pricing7.7 / 10
  • Integrations8.5 / 10
  • Support7.8 / 10

PRODUCT PREVIEW

What this AI tool does

Amazon CodeWhisperer is AWS’s generative AI coding assistant, now represented in AWS product experience as Amazon Q Developer, for developers and cloud teams who want AI help across writing, reviewing, securing, and modernizing software. Amazon CodeWhisperer is especially relevant for builders working in AWS environments, because it combines code generation with cloud-aware guidance about architecture, resources, operations, and migration work. Its story began as an AI pair programmer that could suggest functions, snippets, and full blocks of code inside an IDE. Over time, the product expanded beyond autocomplete into a broader development assistant that can chat about code, explain unfamiliar projects, debug code, propose tests, and help developers move from an idea to a working implementation faster. Inside an IDE or command-line workflow, the tool is designed to meet developers where they already work. It can generate code from natural-language prompts, complete partially written logic, explain errors, and support code refactoring when a developer needs to make software cleaner, safer, or easier to maintain without leaving the development environment. For AWS teams, Amazon CodeWhisperer is best at connecting programming help with deep AWS context, including service selection, infrastructure questions, operational troubleshooting, and resource analysis. That makes it more than a generic coding assistant for organizations building on Lambda, ECS, S3, DynamoDB, IAM, CloudFormation, CDK, and other AWS services. Code quality is also central to the platform’s role in professional development workflows. Rather than only helping a developer type faster, it can assist with code review, test generation, documentation, and changes that improve maintainability, which is where code refactoring becomes part of a broader engineering process instead of a one-off cleanup task. Security support gives the assistant a practical enterprise angle. It can scan code for vulnerabilities, flag risky patterns, and suggest security remediation, which helps teams catch issues earlier in the lifecycle and align development work more closely with secure-by-design practices. Application modernization is one of the clearest ways the tool differs from many AI coding assistants. Amazon CodeWhisperer can support modernization tasks such as Java upgrades and .NET porting, helping teams understand legacy code, plan changes, and automate parts of the transformation work that usually slow down cloud migration projects. Beyond individual coding sessions, the assistant now appears across a wider set of work surfaces, including the AWS Console, Slack, Microsoft Teams, GitLab, GitHub workflows, and agentic task execution experiences. This reflects a shift from simple code suggestions toward an AI development collaborator that can participate in planning, investigation, review, and implementation. Readers looking up Amazon CodeWhisperer pricing should be aware that AWS now presents the service under the Amazon Q Developer product structure, so plan names and packaging may differ from older references to CodeWhisperer. In practical terms, Amazon CodeWhisperer remains most compelling for developers, DevOps engineers, platform teams, and enterprises that want AI coding assistance tightly connected to AWS expertise.

Use cases

Best for

Generate Code

Amazon CodeWhisperer generates code snippets in your IDE or CLI from comments and context, including AWS SDK and infrastructure patterns.

Code Review

It reviews pull requests in GitHub or GitLab workflows and flags security issues and risky patterns with suggested fixes.

Code Refactoring

It refactors code by proposing safer, cleaner implementations and modernization changes, such as Java upgrades and .NET porting guidance.

ANALYSIS

Strengths & limitations

Strengths
  • Best suited to AWS-heavy teams because its deep cloud context supports architecture guidance, resource analysis, troubleshooting, and modernization work alongside coding help.
  • Useful across development workflows because it works in IDEs, the command line, AWS Console, chat tools, and GitHub or GitLab processes.
  • Strong fit for teams that want more than autocomplete because it combines code generation with chat, security scanning, code review, refactoring, testing, and agentic task execution.
Limitations
  • Less suitable for teams with little or no AWS footprint because its strongest differentiation is tied to AWS-specific context and operational guidance.
  • Teams using unsupported editors, custom workflows, or tightly restricted environments may face adoption friction because the product is designed around specific IDEs, terminals, cloud, chat, and repository integrations.
  • The freemium model can limit broader team rollout because higher-volume, advanced, or organizational use is likely to require a paid plan.

Evaluation

FYAI score breakdown

Our structured evaluation across five key criteria

8.0 / 10

Overall score

FYAI rating based on features, pricing and integrations

  • Ease of use7.9 / 10
  • Features8.0 / 10
  • Pricing7.7 / 10
  • Integrations8.5 / 10
  • Support7.8 / 10

What users say

Findings from public reviews, documentation and community sources.

  • Ease of use

    The AWS CodeWhisperer page tells users to “Download a plugin or extension” for JetBrains, VS Code, Visual Studio, command line, or Eclipse and says users can “get started on the Amazon Q Developer Free Tier in a few minutes.”

  • Features

    The AWS CodeWhisperer page says Amazon Q Developer “writes, debugs, and refactors code” and lists real-time suggestions, inline chat, vulnerability scanning, and unit tests.

  • Pricing

    The AWS CodeWhisperer pricing page states a “perpetual Free Tier” with “50 agentic chat interactions per month” and “up to 1,000 lines of code per month” for transformations.

  • Integrations

    The AWS CodeWhisperer page names integrations or placements for JetBrains, IntelliJ IDEA, Visual Studio, VS Code, Eclipse preview, CLI, AWS Console, GitLab, Microsoft Teams, Slack, GitHub.com, and GitHub Enterprise Cloud.

  • Support

    The AWS CodeWhisperer page surfaces “installation instructions,” a “getting started page,” “pricing,” and “Documentation” resources for setup and usage.

Who is this for?

Best for developers who want coding assistance inside common development environments, the AWS CodeWhisperer page tells users to “Download a plugin or extension” for JetBrains, VS Code, Visual Studio, command line, or Eclipse. Less suited to buyers who need all paid-tier details on the CodeWhisperer page, paid-tier detail is handled via the broader Amazon Q Developer pricing path rather than fully surfaced in the page text.

PRODUCT PREVIEW

Feature highlights

AWS-aware coding help

Generate code and get guidance tailored to AWS services and patterns.

Security scanning

Detect risky code and get fixes to reduce vulnerabilities early.

Modernize & refactor

Upgrade Java, port .NET, refactor, and create tests with AI help.

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Ship better code faster with Amazon CodeWhisperer—get help from idea to implementation and stay confident in what you deploy. Start building with AWS-ready guidance today.

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FAQ

Frequently asked
questions

Everything you need to know about this AI tool,
its features, pricing, use cases, and limitations.

Who is Amazon CodeWhisperer best suited for?
Amazon CodeWhisperer is best suited for developers and engineering teams that want AI help writing, reviewing, testing, securing, and modernizing code, especially in AWS-heavy environments. It is relevant for software developers, DevOps engineers, cloud engineers, and teams working in IDEs, terminals, AWS Console, GitHub, GitLab, Slack, or Microsoft Teams.
Is Amazon CodeWhisperer free, or do teams need a paid plan?
Amazon CodeWhisperer follows a freemium pricing model through its current Amazon Q Developer positioning. Teams can typically start with a free option, while broader business features, administrative controls, identity integration, and advanced development capabilities may require paid access. Buyers should confirm current plan limits on the official AWS pricing page.
How does Amazon CodeWhisperer compare with other AI coding assistants?
Amazon CodeWhisperer stands out most for teams that build, operate, and troubleshoot software on AWS. Compared with general AI coding assistants, its strengths include AWS guidance, IDE and CLI support, vulnerability remediation, test generation, code review, refactoring, and operational workflows. The best choice depends on stack, budget, governance needs, and preferred developer tools.
How quickly can a team get started with Amazon CodeWhisperer?
The main trade-off is that Amazon CodeWhisperer is now presented through Amazon Q Developer rather than as a standalone product on its original URL. Its strongest differentiation is tied to AWS workflows, so non-AWS teams may find less value in some features. Some capabilities are also preview features or limited to specific environments.
What should teams check about privacy and compliance before using Amazon CodeWhisperer?
Teams should review how Amazon CodeWhisperer handles source code, prompts, repository context, identity permissions, logging, and administrative controls before adopting it. Security-conscious buyers should also confirm current AWS documentation for data retention, access controls, compliance certifications, vulnerability scanning behavior, and whether usage aligns with internal policies for proprietary code.