Developer Report - Vaibhav

Analysis Period: Jan 1 — Feb 28, 2026

# Vaibhav

Android Developer • PratilipiFM, Media Player, ANR Debugging

Total Sessions
103
AI-assisted development
Code Reviews
50
Primary session type
Friction
Lowest
Smoothest sessions on team
Primary Strength: Code Review Excellence
You use the AI primarily as a code reviewer (50% of sessions), and this approach works exceptionally well. Your sessions hit the fewest blockers on the team — max friction score of just 24, compared to 60 and 143 for others.
Session Patterns
Prompt Categories
Code Review
50%
General Tasks
28%
Detailed Specs
13%
Error Fix
4%
Session Outcomes
Exploration
54%
Partial Success
32%
Full Resolution
14%

Your sessions hit the fewest blockers on the team — you keep problems well-scoped and focused.

Analysis
Work Characterization

You have a balanced, methodical approach. You're debugging ANRs, fixing main thread violations, and working with media players.

Success Pattern

Single-focus tasks succeed consistently. Your error_paste_and_fix sessions score 0.25—that's your optimal format.

Workflow Tips
1
One Objective per Session

Your scope-creep sessions often started with multiple goals. Break them apart:

- Instead: "Check this code for flaws, improve it, and complete the tracking"
- Session 1: "Review this media player code for thread safety issues"
- Session 2: "Add Amplitude tracking for playback events"

2
Verify AI Assumptions

16% of sessions had AI hallucination—wrong git flags, incorrect file paths. A quick verification helps:

`When AI suggests: git show --no-stat
Verify: Does that flag exist in git?`
3
Leverage Error-Fixing Pattern

Your error_paste_and_fix sessions perform exceptionally well (0.25 avg). Do more of this:

- Paste the full stack trace
- Include the relevant code snippet
- Ask: "What's causing this and how do I fix it?"

Notable Patterns
✓
Debugging Excellence

You're tackling Android's hardest problems: ANRs, main thread violations, media player crashes.

✓
Self-Correction Detection

12% of sessions involved AI self-correction—because you asked clear enough questions.

Android Media Player ANR Debugging Code Review