This week focused on backend development fundamentals, API testing, and early-stage research into AI action verification systems. I also explored tools and frameworks for building and validating server-side applications.
What I Worked On
Node.js and API development.
Explored Node.js and Nodemon to understand how server-side applications are built and executed efficiently. Used Postman to test API endpoints and validate responses. Built a simple web application to apply and reinforce these concepts through hands-on practice.
AI Action Verification system research.
Conducted research on Google Business Profile API webhooks and automation tools such as Puppeteer and Playwright for tracking AI recommendation compliance. Focused on understanding how actions can be monitored and verified in a closed-loop system.
Prepared documentation in Markdown outlining:
- Technology capabilities and limitations
- Practical usage examples
- Potential implementation approaches
Proposed schema structures for src/models/ to support:
- Current state tracking
- New state comparison
- Verification status logging
Summarized findings to support the design of an automated AI recommendation verification workflow.
Workforce accountability research.
Conducted preliminary research related to workforce accountability and attendance systems to explore potential integration or tracking mechanisms.
What I Learned
- Node.js provides a flexible foundation for backend development, especially when paired with tools like Nodemon for rapid iteration
- Postman is essential for validating API behavior before integrating into larger systems
- Designing verification systems requires thinking in terms of state tracking, not just actions
- Early documentation helps clarify system design before implementation begins
Next Week
- Continue building backend applications using Node.js
- Prototype basic API integrations based on research findings
- Further refine the AI action verification system design and schema structure