The 5-Day Roadmap for Building a Production-Ready Full-Stack Web App

This five-day plan is a practical, high-impact roadmap for developers—from ambitious beginners to experienced engineers—who want to build and deploy a modern full-stack web application. With AI-assisted development, solid DevOps habits, and AWS cloud services, you can ship a real MVP and level up your engineering toolkit at the same time.

Day 1: Environment setup (estimated: 7 hours)

Establish a foundation: version control, cloud account hygiene, containers, AI-assisted IDE workflow, and hosting plus serverless scaffolding.

• Git (~15 min): Initialize Git, branch habits, and push to GitHub. Wire webhooks for CI/CD later.
• AWS account setup (~15 min): IAM roles, billing alerts, and least-privilege admin for deploy roles.
• Docker (~30 min): Local reproducibility; same image shape you can reuse for Lambda containers or ECS later.
• Cursor + Claude (~1 hour): Scaffold projects, generate boilerplate, and iterate with inline reviews—keep prompts tied to requirements, not vague vibes.
• AWS Amplify (~2 hours): Connect the GitHub repo, env vars, previews, SSL, and optional custom domains for the frontend.
• AWS SAM (~3 hours): Install SAM CLI, author template.yaml, deploy Python Lambda behind API Gateway, validate with a guided tutorial run on Linux runtime.

Day 2: UI development (estimated: 8 hours)

Build the visual and interactive layer first so you have something to point the API at on day three.

• Framework init (~30 min): Bootstrap with React, Next.js, or Vue—sane defaults beat bespoke bundlers for a week sprint.
• Frontend features (~7 hours): Components, flows, responsive layout. Use AI for drafts, but manually verify accessibility (labels, focus, contrast). Skip deep backend wiring for now.
• API Gateway prep (~30 min): Sketch routes that will later hit Lambda—path naming, CORS, and auth placeholders.

Day 3: Backend development (estimated: 8 hours)

Server-side logic, Lambda handlers, and honest TODOs for caching and persistence.

• SAM config (~1 hour): Resources, IAM, environment variables, and function triggers in template.
• First Lambda (~1 hour): Parse input, return JSON, prove end-to-end from the UI or curl.
• AI-assisted implementation (~6 hours): Validation, error shapes, auth stubs. Mark durable improvements (caching, idempotency) as tracked TODOs, not silent debt.

Optional: FastAPI-style routing if you outgrow thin handlers; SQS between API Gateway and workers when concurrency spikes matter.

Day 4: Data storage configuration (estimated: 8 hours)

• Database provisioning (~1 hour): DynamoDB table in SAM—partition/sort keys aligned to real access patterns.
• Schema + integration (~5 hours): Model entities, CRUD through Lambda, retries and conditional writes where needed.
• Independent testing (~2 hours): Contract tests per endpoint; CloudWatch logs for failures you can replay.

Optional: RDS when relational constraints dominate; S3 for uploads; Redis/Kafka when you need cache or streaming—skip until the MVP path is green.

Day 5: Deployment, monitoring, and final test (estimated: 7 hours)

• Frontend deploy (~1 hour): Amplify production branch, env parity with staging, smoke-test critical path.
• Backend deploy (~3 hours): sam deploy, versioned stacks, container images if you need native deps.
• CloudWatch (~3 hours): Alarms on errors/latency, log groups per function, trace a failing request end-to-end.

Optional: Grafana boards or AWS X-Ray for traces across services once traffic justifies it.

Final thoughts

You leave with more than an MVP: a repeatable build-measure-deploy loop—AI in the editor, serverless backend, managed hosting. Reuse the blueprint for hackathons, portfolio upgrades, or product validation.

How Ambitology can help

Document the build in your knowledge base, turn outcomes into resume bullets with the project-to-résumé guide, and stress-test wording in the resume analysis lab.