Amazon Q Developer

Amazon Q Developer is AWS's AI coding assistant, launched in April 2024 as a rebrand and significant expansion of Amazon CodeWhisperer. It covers inline completions, an agentic chat interface in VS Code, JetBrains, Visual Studio, Eclipse, and the AWS Console, plus a CLI integration for terminal-first developers. The tool's clearest edge over general-purpose coding assistants is its depth of AWS knowledge: it knows IAM policy syntax, Lambda handler patterns, CloudFormation resource types, and the Well-Architected Framework out of the box. A Code Transformation feature automates Java version upgrades and .NET Windows-to-Linux migrations at a scale that's hard to match manually. The free tier is genuinely useful, and the Pro plan at $19/user/month sits at the same price as GitHub Copilot Business.

If your team runs on AWS, the question isn’t whether Amazon Q Developer is the best AI coding assistant in general. It isn’t. The question is whether its AWS-specific depth justifies adding it alongside, or replacing, whatever general-purpose tool you’re already using. That’s a narrower and more useful question, and for a specific kind of team the answer is yes. Q Developer has earned a real place in the AWS developer’s toolkit, but it earns it on a particular axis, and knowing which axis matters for your work is the whole decision.

Quick verdict

Amazon Q Developer is the right tool if AWS infrastructure code is your daily reality. Its inline completions know IAM, Lambda, and CloudFormation at a level general models can’t match, and Code Transformation for Java upgrades is genuinely impressive. Where it loses ground is on everything else: for greenfield web apps, non-AWS backend work, or complex multi-file agentic tasks, Cursor and Claude Code are clearly ahead. Think of Q Developer as a specialist, not a generalist.

What is Amazon Q Developer, exactly?

The product has a predecessor worth knowing. Amazon CodeWhisperer launched in 2022 as a VS Code and JetBrains extension focused on inline completions, with particular attention to AWS API calls. It built its reputation on contextual awareness: suggesting boto3.client('s3') when you were clearly writing S3 code rather than offering generic filler.

In April 2024, AWS retired the CodeWhisperer brand and launched Amazon Q Developer. The rename wasn’t cosmetic. The new product absorbed CodeWhisperer’s completion engine and added an agentic chat interface, CLI completions, architecture guidance tied to the Well-Architected Framework, code transformation for migrations, and security scanning. It launched in direct competition with GitHub Copilot Business at the same $19/user/month price.

What makes it distinct is that it was built by the company that runs the platform it’s advising you on. When it suggests an IAM policy, it’s drawing on the same knowledge base that wrote the IAM documentation. General AI models trained on AWS documentation can approximate that knowledge; Q Developer’s model was built around it.

The product supports VS Code, JetBrains, Visual Studio, and Eclipse, and it lives inside the AWS Management Console, which no other mainstream coding assistant can say.

The features that earn the AWS-native label

Inline completions tuned for AWS code

The core completion engine is where Q Developer’s CodeWhisperer origin shows most clearly. Completions are solid across supported languages, but the difference from general tools shows the moment you’re writing AWS service code. Type const s3 = new AWS.S3() and the suggestions that follow know the S3 API in detail, including pagination behavior that trips up SDK newcomers. Write a Lambda handler stub and it’ll complete the correct event structure for the trigger type it infers from context.

It’s a model fine-tuned with AWS service knowledge as a priority. For teams spending most of their time on Lambda, DynamoDB, CloudFormation, or Step Functions, that focus pays off in fewer wrong completions and fewer trips to the docs. Reference tracking and public code suppression ship on the free tier.

Q chat in your IDE

The chat interface in Q Developer follows the pattern every coding assistant now offers: a panel in your IDE where you can ask questions, request edits, and get explanations. What differentiates Q’s chat is the AWS context it can pull in. Ask it to review your CloudFormation template for cost optimization issues and it’ll apply Well-Architected Framework principles. Ask it to explain why your Lambda is cold-starting slowly and it’ll give answers grounded in how Lambda actually allocates compute, not generic advice.

The agentic version of this goes further. Q Developer’s agentic mode can read and write files, generate code diffs, and run shell commands to accomplish longer tasks. AWS reports that Q Developer ranks on SWE-Bench leaderboards for agentic capability. In practice, the agentic mode works well for AWS-scoped tasks and reasonably well for general coding, though complex multi-file refactors still feel less polished than what Cursor offers in its composer or Claude Code handles in the terminal.

The free tier limits agentic chat to 50 interactions per month. That sounds like a lot until you’re using it seriously, at which point it disappears fast.

Code Transformation for Java and .NET

This is Q Developer’s most distinctive feature and the one that has no real equivalent anywhere else in the category.

Code Transformation automates two migration workflows. The first is upgrading Java 8 or Java 11 codebases to Java 17. Java’s long-term support release cadence has left a lot of enterprise codebases stuck on versions AWS would rather you migrate off, and doing it manually across a large codebase is tedious, error-prone work. Q Developer analyzes your project, builds a dependency graph, identifies compatibility issues, and generates a migration plan it then applies as a diff you can review. The second workflow ports .NET Framework applications from Windows to Linux, which matters for teams trying to move Windows Server workloads to Amazon Linux on EC2 or containers on ECS.

A codebase upgrade that would take a developer several weeks becomes something you can review and approve over a few days. The output isn’t always perfect and you’ll need to validate it, but the time savings on boilerplate migration work are real.

Free tier users get 1,000 lines of transformation per month. Pro users get 4,000 lines pooled across their account, with additional capacity at $0.003 per line submitted.

CLI, console, and IDE coverage

Most coding assistants live in your editor and stop there. Q Developer also runs in the terminal with completions and natural-language-to-bash translation: describe what you want and it suggests the right aws CLI command with the correct flags and parameter values. For developers who spend significant time in the terminal, this integration is genuinely useful and not well replicated elsewhere.

The AWS Console integration is the other coverage advantage. Q Developer answers questions inside the console itself: ask about a specific resource, a cost anomaly, or a service configuration without switching to your editor. No other mainstream coding assistant is embedded in the cloud console of the platform it’s advising you on.

Security scanning baked in

Q Developer includes a security scanner that checks code for OWASP Top 10 vulnerabilities and AWS-specific security issues like overly permissive IAM policies, hardcoded credentials, and S3 bucket misconfigurations. It runs without a separate subscription or plugin. For security-conscious teams, having this integrated into the same tool that writes the code reduces the friction of acting on findings.

The scanner isn’t a replacement for a dedicated SAST tool at the depth of Snyk or Semgrep, but it catches a meaningful class of issues that pure AI completion tools wouldn’t flag.

Pricing

Q Developer’s pricing is straightforward.

The free tier costs nothing and doesn’t expire. It includes inline completions, 50 agentic chat interactions per month, and 1,000 lines of monthly code transformation. The 50-interaction cap is the main constraint: in serious daily use it gets reached by mid-month. Inline completions don’t carry a stated hard cap, which makes the free tier viable as a completions-only tool.

The Pro plan is $19 per user per month, billed through your AWS account. It removes the agentic request cap (subject to fair-use limits), raises the transformation allowance to 4,000 lines pooled per AWS payer account, adds an admin dashboard with user management and policy controls, IP indemnity protection, and automatic opt-out from data collection.

Extra transformation beyond the monthly allocation costs $0.003 per line submitted. On a large migration project, that adds up, so estimate your line count before starting.

At $19/user/month, Q Developer Pro sits at the same price as GitHub Copilot Business. That makes the comparison between them a feature decision rather than a price decision.

Where Q Developer wins and where it doesn’t

Q Developer wins on any task involving AWS service code. IAM policy generation, CloudFormation and CDK templates, Lambda functions with the right event types, DynamoDB access patterns, Step Functions state machines: these are where its domain knowledge makes suggestions reliably better than a general model would produce.

Code Transformation has no peer in the AI coding space. If you’re managing a Java 8 or .NET migration project, that feature alone may justify the subscription.

Where Q Developer loses ground is on general coding work: a React frontend, a Python data pipeline, a TypeScript service with no AWS involvement, or complex multi-file agentic edits. The agentic mode benchmarks well, but in daily IDE use it doesn’t yet match the planning depth of Cursor’s composer or the terminal-native power of Claude Code for large-scope changes.

AWS made a deliberate bet on deep domain expertise over broad capability. That bet pays off for the developers it was designed to serve and falls short for everyone else.

Who Q Developer is built for

The clearest fit is an AWS backend team: developers writing Lambda functions, platform engineers managing CloudFormation and CDK stacks, or DevOps teams working on IAM and networking. If AWS infrastructure code is the majority of your daily work, Q Developer is the most capable tool available for that job.

The second clear fit is any team sitting on a legacy Java 8 or Java 11 codebase that needs to move to Java 17, or a .NET shop moving Windows workloads to Linux on AWS. For those teams, Code Transformation alone justifies the evaluation.

The tool is less compelling for frontend-heavy teams, full-stack developers with a limited AWS footprint, or anyone whose primary productivity constraint is complex multi-file agentic work rather than service-specific code quality.

Q Developer vs the alternatives

vs GitHub Copilot

These two products share a price point and broad IDE coverage, which makes the comparison direct. Copilot has a larger community, a multi-model picker with access to Claude and GPT-5, and tighter GitHub integration for teams using pull requests and Actions. Q Developer has better AWS-specific completions, Code Transformation, and Console integration. If you’re an AWS shop, Q Developer’s domain depth is the clearer advantage. If your work spans multiple clouds or is mostly application code, Copilot’s flexibility wins. The two tools can also run in parallel in VS Code if you want both.

vs Cursor

Cursor is optimized for the agentic multi-file editing workflow where you describe a change and watch it execute across your codebase. It’s better than Q Developer on complex refactors, new feature scaffolding, and exploratory coding where you need the AI to hold context across many files at once. Q Developer is better on AWS service code quality and runs inside your existing IDE without switching editors. Teams that do serious AWS work often evaluate both and choose based on which workflow dominates their day.

vs Claude Code

Claude Code is a terminal-native agentic tool built on Anthropic’s Claude models. It’s the strongest current option for long-horizon agentic tasks, and its general code quality and reasoning depth are ahead of Q Developer for non-AWS work. Q Developer closes the gap significantly on anything AWS-related, and it runs embedded in your IDE rather than requiring a terminal session. For teams that want to use the best AI agent for coding across the full stack, the two tools solve different problems. For AWS specialists who want IDE integration and AWS Console access, Q Developer is the more practical daily tool.

Q Developer and Amazon Bedrock Agents serve different audiences entirely: Bedrock Agents is a platform for building and deploying AI agents on AWS infrastructure, while Q Developer is a developer productivity tool. They complement each other in a mature AWS AI stack rather than compete.

Getting started

Install the Amazon Q extension from the VS Code marketplace or the JetBrains plugin repository, sign in with a free AWS Builder ID (no credit card required), and completions start immediately. The free tier activates with no configuration.

Start with something AWS-specific: paste in an IAM policy and ask Q to review it for least-privilege issues, or ask it to generate a Lambda function for a specific trigger type. That’s where the advantage shows most clearly.

For Code Transformation, open the transformation panel, point it at your project directory, select your source and target versions, and let it run. Reviewing the diff is the main time investment.

Pro billing runs through AWS, so you can add a user and test with a real workload for one month. Just note the full monthly fee applies even if you cancel mid-month, so plan your trial timing accordingly.

The bottom line

Amazon Q Developer is a specialist tool that excels at a specific job: helping developers write better AWS service code, migrate legacy Java and .NET applications, and catch AWS-specific security issues without leaving their IDE. It’s the strongest coding assistant available for that particular scope, and Code Transformation is a feature with no real competition.

What it’s not is a replacement for Cursor or Claude Code on general agentic coding work, and it’s not trying to be. AWS made a deliberate choice to build deep rather than broad, and that choice reads clearly in the product. For AWS-heavy teams, the evaluation is straightforward: Q Developer earns its place in the toolbox. For everyone else, it’s a specialist that may not match your primary needs.

Key features

• Inline code completions with AWS API and service awareness built in
• Agentic chat in VS Code, JetBrains, Visual Studio, Eclipse, and the AWS Console
• Code Transformation for Java 8/11 to 17 upgrades and .NET Windows-to-Linux migration
• CLI completions with natural-language-to-bash translation
• Security scanning for OWASP Top 10 and AWS-specific misconfigurations
• Architecture guidance aligned to AWS Well-Architected Framework
• Reference tracking and public code suppression on all tiers

Pros and cons

Who is Amazon Q Developer for?

• AWS backend teams writing Lambda functions, CloudFormation stacks, and IAM policies daily
• Platform engineers who need automated Java 8/11-to-17 upgrades across large codebases
• .NET shops migrating Windows workloads to Linux on AWS
• Security-conscious organizations that need vulnerability scanning integrated into the IDE

Alternatives to Amazon Q Developer

If Amazon Q Developer isn't quite the right fit, the closest alternatives are github-copilot , cursor , and claude-code . See our full Amazon Q Developer alternatives page for side-by-side comparisons.