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Agent Development Log

Agent Development Log

This document tracks the AI-assisted development history of this portfolio project, including the system prompts, research methodologies, and custom tools used throughout the development process.

Initial System Prompt (Eno Reyes Persona)

The project was initiated with a specialized AI persona designed to embody the principles of a Factory Reliability Engineer (FRE) with a focus on:

  • Measurable Results: All changes must be quantifiable and verifiable
  • Standards Compliance (Pillar 8): Adherence to established coding standards and best practices
  • Comprehensive Observability (Pillar 6): Structured logging and monitoring across all features
  • Multi-Breakpoint Verification: All UI/UX changes tested across mobile (320px), tablet (768px), and desktop (1280px)
  • Test-Driven Development: New features paired with unit tests

Core Persona Attributes

Role: Factory Reliability Engineer (FRE)
Focus Areas:
  - Performance Optimization (LCP, CLS, FID)
  - Security Best Practices
  - Observability & Monitoring
  - Responsive Design Standards
  - Version Control & Documentation

Structured Research Prompts

The development process utilized XML-structured prompts to guide the AI model through complex, multi-phase implementations:

Phase A: UI/UX Standards and Fluidity

<PHASE name="UI/UX Standards">
  <OBJECTIVE>Implement modern typography and responsive layout</OBJECTIVE>
  <ACTIONS>
    - Font Standard Implementation (Inter via next/font/google)
    - Responsive Layout Alignment (Tailwind breakpoints)
    - Content Alignment (optimal line length 50-75 chars)
  </ACTIONS>
  <VERIFICATION>
    - Visual testing across 3 breakpoints
    - Zero CLS with font optimization
  </VERIFICATION>
</PHASE>

Phase B: Resume Hosting and Documentation

<PHASE name="Resume Infrastructure">
  <OBJECTIVE>Secure resume hosting with version tracking</OBJECTIVE>
  <ACTIONS>
    - Create /resume route with PDF viewer
    - Implement version utility (src/utils/resume-version.ts)
    - Add unit tests for version validation
  </ACTIONS>
  <VERIFICATION>
    - Version format validation (semantic versioning)
    - Unit test coverage
  </VERIFICATION>
</PHASE>

Phase C: Analytics and Learning Dashboard

<PHASE name="Analytics Infrastructure">
  <OBJECTIVE>Multi-metric analytics dashboard</OBJECTIVE>
  <ACTIONS>
    - Analytics data collection endpoint
    - Instrumentation via structured logger
    - Visualization page with placeholder components
  </ACTIONS>
  <VERIFICATION>
    - Event tracking validation
    - Data payload structure documentation
  </VERIFICATION>
</PHASE>

Custom Tools and Configurations

1. Structured Logger (src/lib/logger.ts)

  • Purpose: Centralized, context-aware logging for production observability
  • Features:
    • Log levels (ERROR, WARN, INFO, DEBUG)
    • Automatic context capture (timestamp, userAgent, URL)
    • Event tracking for analytics
    • Development vs. production behavior

2. Version Tracking Utility (src/utils/resume-version.ts)

  • Purpose: Centralized resume version management
  • Features:
    • Semantic versioning validation
    • Formatted version strings
    • File path resolution
    • Unit test coverage

3. Analytics Instrumentation

  • Integration Points:
    • ContactList component (link clicks)
    • Resume page (downloads, views)
    • Future: Page views, interaction metrics

Development Milestones

Milestone 1: Foundation (Initial Setup)

  • Next.js 14 with App Router + Pages Router (Nextra docs)
  • Tailwind CSS configuration
  • Vitest + React Testing Library (14/14 tests passing)
  • Structured logging infrastructure

Milestone 2: UI/UX Optimization

  • Inter font implementation (zero CLS)
  • Responsive layout refactoring
  • Fluid typography across breakpoints
  • Consistent spacing and padding

Milestone 3: Resume Infrastructure

  • Version-tracked resume hosting
  • Secure PDF viewer at /resume
  • Unit tests for version utility
  • Download tracking via logger

Milestone 4: Analytics Foundation

  • Event tracking infrastructure
  • Analytics page structure
  • Component instrumentation
  • Documentation for data integration

Future Enhancements

Planned: Learning Dashboard

A comprehensive learning progress tracker with:

  • Data Model: LearningActivity, GoalProgress entities
  • Verification Gates: Unit tests for progress calculations
  • Routing Strategy: /dashboard, /dashboard/progress
  • Integration: Structured logger for activity tracking

See LEARNING_DASHBOARD_BLUEPRINT.mdx for detailed architectural plan.

Lessons Learned

  1. Structured Prompts: XML-formatted prompts with clear phases improved AI comprehension and execution
  2. Incremental Development: Breaking complex features into phases enabled better verification
  3. Test-First Approach: Writing tests alongside features caught edge cases early
  4. Observability First: Structured logging from day one simplified debugging and analytics

References

Last Updated: 2024-11-29 Maintained by: Abishek Maharajan

Deployment