Built a mvp / prototype with Amazon Q Developer?
We'll make it production-ready.
You built a prototype with an AI tool and it works — on your machine, with your test data, for the happy path. Now you need real users to validate your idea. The goal isn't perfection — it's getting to a state where real people can use it safely and reliably. That means fixing the critical gaps without over-engineering.
MVP / Prototype challenges in Amazon Q Developer apps
Building a mvp / prototype with Amazon Q Developer is a great start — but these challenges need attention before launch.
Identifying what actually needs fixing
Not everything needs to be production-grade for an MVP. The challenge is knowing which shortcuts are acceptable (visual polish, advanced features) and which aren't (security, data loss, broken core flows). Our audit prioritizes fixes by impact.
Security minimum
Even an MVP handles user data. You need authentication that works, data isolated per user, no exposed secrets, and HTTPS. You don't need enterprise-grade security, but you need the basics done right.
Deployment
Your app runs locally but deploying it involves environment variables, domain configuration, SSL, and build optimization. First-time deployment is where most AI prototypes hit unexpected issues.
Error handling
When something goes wrong (and it will), your users should see a helpful message — not a white screen or a raw error. Basic error handling is the difference between 'this app is buggy' and 'something went wrong, please try again.'
Core flow reliability
Your main user flow (signup → core action → outcome) must work every time. Edge cases in secondary flows can wait, but the core path needs to be solid for your MVP to generate valid learnings.
What we check in your Amazon Q Developer mvp / prototype
Common Amazon Q Developer issues we fix
Beyond mvp / prototype-specific issues, these are Amazon Q Developer patterns we commonly fix.
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.
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.
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.
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.
Start with a self-serve audit
Get a professional review of your Amazon Q Developer mvp / prototype at a fixed price.
External Security Scan
Black-box review of your public-facing app. No code access needed.
- OWASP Top 10 vulnerability check
- SSL/TLS configuration analysis
- Security header assessment
- Expert review within 24h
Code Audit
In-depth review of your source code for security, quality, and best practices.
- Security vulnerability analysis
- Code quality review
- Dependency audit
- Architecture review
- Expert + AI code analysis
Complete Bundle
Both scans in one package with cross-referenced findings.
- Everything in both products
- Cross-referenced findings
- Unified action plan
100% credited toward any paid service. Start with an audit, then let us fix what we find.
Frequently asked questions
Can I build a mvp / prototype with Amazon Q Developer?
Amazon Q Developer is a great starting point for a mvp / prototype. It handles the initial scaffolding well, but mvp / prototype apps have specific requirements — identifying what actually needs fixing and security minimum — that need professional attention before launch.
What issues does Amazon Q Developer leave in mvp / prototype apps?
Common issues include: overly permissive iam policies generated with wildcard actions and resources, lambda cold start latency not addressed in generated function configurations, generated cdk code creates aws resources without cost estimation or tagging. For a mvp / prototype specifically, these issues are compounded by the need for identifying what actually needs fixing.
How do I make my Amazon Q Developer mvp / prototype production-ready?
Start with our code audit ($19) to get a clear picture of what needs fixing. For most Amazon Q Developer-built mvp / prototype apps, the critical path is: security review, then fixing core flow reliability, then deployment. We provide a fixed quote after the audit.
How much does it cost to fix a Amazon Q Developer-built mvp / prototype?
Our code audit is $19 and gives you a complete report of issues. Fixes start at $199 with our Fix & Ship plan. For larger mvp / prototype projects, we provide a custom fixed quote after the audit — no hourly billing.
Get your Amazon Q Developer mvp / prototype production-ready
Tell us about your project. We'll respond within 24 hours with a clear plan and fixed quote.