7 Our minimum viable product

This chapter moves from research spikes to a cohesive Minimum Viable Product that demonstrates real value while enabling validated learning. It clarifies MVP versus adjacent “minimums,” then focuses on integrating prior work into a usable ACH dashboard that lets users upload a file, parse and store it, and visualize results. The emphasis is on assembling, not expanding, functionality—balancing speed with quality, avoiding scope creep, and using the MVP to solicit early feedback that will guide the next iterations.

On the implementation side, the team aligns the FastAPI backend, Postgres schema, and Next.js UI: refining the /files endpoint, enforcing numeric types in the database, and introducing Pydantic response models and better documentation. They add an API for batches using a test-first approach, reconcile snake_case and camelCase across services, and transform raw responses into UI-friendly structures. The dashboard gains a direct file upload flow, while the deployment is hardened with Docker-based configs (CORS tuning, split dev/prod requirements and TypeScript configs, environment variables), basic authentication via NextAuth, optional token checks on the API, and TLS offload through an Nginx reverse proxy. The team also builds a BDD-driven ACH file generator to create targeted, safe test data.

Testing spans unit, BDD-style integration, and end-to-end coverage with Playwright, using accessible selectors and explicit waits for reliable automation. The chapter closes with pragmatic troubleshooting across the stack—CORS misroutes, Pydantic validation mismatches, SQL join pitfalls, selector ambiguity, missing Docker files, exposed ports, and dependency conflicts—cementing practices that keep the MVP stable. With APIs, UI, security, packaging, and tests in place, the MVP is ready to demo, ship for feedback, and evolve quickly in subsequent sprints.

The pieces and parts feeding into the MVP

The sample POST request

Data being returned but displayed incorrectly.

Our API now has documented fields and examples.

Updated component for Recent ACH Uploads

OpenAPI documentation for retrieving ACH batches.

Docker Setup for ACH Dashboard MVP

Our list of defined APIs

Process of adding functionality to our MVP

Login Sample Page

Showing the Authorize Button and Popup

Screen not completely rendered when we do not wait.

• Over previous sprints, we explored using Generative AI and technologies like Python/FastAPI, Postgres, Docker, and Next.js to expedite software development for our ACH Dashboard MVP.
• The MVP focuses on allowing users to upload and parse ACH files, store them in a database, and visualize the results on a dashboard.
• Different minimum concepts include MVP, MLP, MMP, and MMF, each serving unique purposes from testing assumptions to delivering features.
• Preparing for an MVP involves integrating components like the ACH parser, APIs, database design, and UI to function cohesively.
• Developing the /files APIs ensures alignment between the backend and UI, focusing on data accuracy and seamless functionality.
• BDD and TDD approaches help integrate APIs with the UI, ensuring accurate data responses and interactions.
• Refactoring interfaces and schemas improves code maintainability, readability, and flexibility when consuming APIs.
• Supporting ACH Batches API integration into the dashboard requires updating data structures and transforming responses to match UI needs.
• Upload functionality from the dashboard simplifies user interaction, but highlights development considerations, like code duplication and user feedback upon file upload.
• Deployment in Docker involves cleaning up configurations for production readiness, ensuring seamless communication between containers, and addressing common troubleshooting issues.

FAQ