AWS-native AI coding assistant for cloud-first development

Built with Amazon Q Developer?
Let's make sure it's production-ready.

AWS's AI coding assistant that generates code optimized for AWS services including Lambda, DynamoDB, S3, and CDK. Integrated into VS Code, JetBrains, and the AWS console, with deep knowledge of AWS APIs and best practices. We help non-technical founders identify and fix the issues AI tools leave behind.

PythonTypeScriptJavaAWS CDKCloudFormation

Common issues we find in Amazon Q Developer code

These are real problems we see in Amazon Q Developer projects during our audits — not hypotheticals.

highSecurity

Overly permissive IAM policies generated with wildcard actions and resources

Amazon Q often generates IAM policies with `*` wildcards for actions or resources as a starting point, which violates the principle of least privilege. These policies should be scoped to specific actions and resource ARNs before being applied in production.

highPerformance

Lambda cold start latency not addressed in generated function configurations

Generated Lambda functions use default memory and timeout settings without considering cold start impact. Functions with heavy initialization code (loading models, establishing DB connections) need provisioned concurrency or memory tuning, which Amazon Q does not configure.

mediumDeployment

Generated CDK code creates AWS resources without cost estimation or tagging

Amazon Q CDK suggestions deploy resources without cost-tracking tags or budget guardrails, making it easy to inadvertently provision expensive resources (NAT gateways, multi-AZ RDS instances) without visibility into the cost impact.

mediumPerformance

DynamoDB access patterns generated without consideration for partition key hot spots

Generated DynamoDB table designs and query patterns sometimes use partition keys that distribute poorly under load — such as a status field with few values — creating hot partitions that throttle at scale.

mediumCode Quality

Vendor lock-in from AWS-specific code that is difficult to migrate away from

Amazon Q naturally generates AWS SDK calls, CDK constructs, and service-specific patterns that tie your application tightly to AWS. Moving to another cloud or even running locally for testing becomes harder as AWS-specific code accumulates.

mediumTesting

Generated code lacks unit tests that work outside the AWS environment

Test suggestions for AWS Lambda and service integrations often require real AWS services to run, rather than mocking the SDK. This makes the test suite slow to run locally and impossible to run in CI without AWS credentials.

mediumDeployment

CloudFormation templates generated without drift detection or stack policies

Generated CloudFormation templates deploy successfully but lack stack policies that prevent accidental deletion of stateful resources like DynamoDB tables or RDS instances, and do not enable drift detection.

lowBugs

Hardcoded AWS region strings in generated Lambda and SDK code

Amazon Q sometimes generates code with hardcoded region strings like `us-east-1` rather than reading from environment variables or the Lambda execution context, making the code fail when deployed to other regions.

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In-depth review of your source code for security, quality, and best practices.

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  • Dependency audit
  • AI pattern analysis
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Both scans in one package with cross-referenced findings.

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100% credited toward any paid service. Start with an audit, then let us fix what we find.

How it works

1

Tell us about your app

Share your project details and what you need help with.

2

Get a clear plan

We respond in 24 hours with scope, timeline, and cost.

3

Launch with confidence

We fix what needs fixing and stick around to help.

Frequently asked questions

Is Amazon Q Developer free and what is included in the free tier?

Amazon Q Developer has a free tier that includes inline code completions and chat for individual developers. The Pro tier adds features like security scanning, code transformation, and higher usage limits. For startup use, the free tier is sufficient for getting started — Pro is worth considering when you have a team and need security scanning integrated into your workflow.

How does Amazon Q handle our AWS credentials and source code security?

Amazon Q does not use your code for model training by default in the Pro tier. Code snippets are sent to AWS for processing but are covered by the AWS data processing agreement. Your AWS credentials are not sent to the model — Q uses your existing AWS CLI profile for service interactions. Review the Amazon Q data handling FAQ for specifics on your deployment region.

Can Amazon Q help with non-AWS code or is it only useful for cloud infrastructure?

Amazon Q is useful for general code generation in Python, TypeScript, and Java, not just AWS infrastructure. Its AWS knowledge is a differentiator, but it is a capable general-purpose assistant for application code. It integrates with VS Code and JetBrains, making it usable in any project, though its suggestions will lean toward AWS-compatible patterns.

How should we scope IAM policies that Amazon Q generates?

Treat every Amazon Q IAM policy as a starting point, not a final output. Replace wildcard `*` resources with specific ARNs for your actual resources. Replace `*` actions with the specific actions the Lambda or service actually calls. Use AWS IAM Access Analyzer to verify policies are least-privilege before applying them. This step is critical — overly permissive IAM is one of the most common AWS security issues.

Does Amazon Q help with migrating existing applications to AWS?

Yes — Amazon Q has a dedicated code transformation feature that can help migrate Java applications between versions and assist with moving code to AWS Lambda or containers. This is one of its more unique capabilities compared to general AI assistants. The quality varies by application complexity, but it can significantly accelerate migration analysis and initial code changes.

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