Solving Problems with Scalable Solutions

Solving Problems with Scalable Solutions #

Every solution starts with a problem—and a customer experiencing it. So, let’s start with the customer.

1. Understanding the Customer #

• Who are they? What are their demographics?
• What’s their pain? How big is the problem’s impact on their life?
• What’s been tried? Why haven’t existing solutions worked?
• What’s missing? What are the perceived drawbacks of current options?

Gathering insights early is key. We aim to fix the problem as effectively and efficiently as possible.

2. Planning and Scoping #

Researching Existing Solutions #

Start by identifying existing options, especially open-source solutions. Leveraging previous work saves time and resources, letting us focus on innovating where it matters.

Matching Solutions to Scale #

Solutions must fit the customer’s size and needs. For example, if you’re a team of fewer than five, a shared Google Sheet might work better than a costly custom CRM. Scale thoughtfully—don’t burn capital where efficiency can thrive.

Key questions to answer:

• How many users?
• Peak activity times?
• Seasonal patterns or planned traffic spikes?
• What data are we storing, and what processes do we need?

3. Regulatory Considerations #

Address compliance from the start. Depending on the industry, regulations like HIPAA, 508, FEDRAMP, FINRA, or HITECH may apply. Non-compliance risks are not worth cutting corners.

4. Design Phase #

After scoping, draft user stories, mockups, and data maps. For more robust projects, include infrastructure diagrams and threat models to align the technical foundation with user needs and regulatory requirements.

Bootstrap the System #

Build from starter templates or similar implementations. A monolithic architecture is often ideal for small teams (<100 employees).

Example:
For a custom patient coordinator CRM, I’d use React.js (frontend) and Node.js (backend) with AWS for HIPAA compliance.

Break features into manageable chunks—no more than 4 hours per task:

• E.g., “Users can log in to access their dashboard and view daily patient schedules in one place.”

5. Development and Testing #

Frontend and Backend Principles #

• Keep the stack aligned (e.g., React frontend + Node or Rust backend).
• Follow KISS (Keep It Simple, Stupid): Static frontend + API + cron jobs for maintenance is often enough.

Backend Model:
Server → API ← Job

Frontend Model:
Data Mapper → Components → View → Solves Problem

Testing and Analytics #

• Prioritize E2E testing for user scenarios and unit testing for sanity checks.
• Add logging and analytics to track user behavior and system performance (e.g., load times, error rates).

6. Scaling and Reliability #

Build for scale based on:

• Active connections
• User count
• Data size per session

Plan for uptime with:

• Disaster recovery
• High availability
• Automated deployments via CI/CD pipelines and infrastructure-as-code (Terraform or Pulumi).

AWS remains a top choice for healthcare applications due to its reliability and scalability.

Final Touches #

• Styling: Stick with accessible libraries like react-508-components to maintain 508 compliance.
• Linting & Formatting: Consistency matters more than the tool—just enforce standards.

That’s the process in a nutshell. What’d I miss?