My results after a sprint: AI assistant usage stats and perceived impact.

Hey everyone! Just wrapped up a focused, two-week "AI assistant sprint" where I tried to strictly use AI for all my coding tasks at work. I wanted to share some concrete stats and my subjective take on the impact.

**The Setup:**
- **Language:** Python (mostly data pipelines & API integrations)
- **Primary Assistant:** I used a popular cloud-based coding assistant (let's call it Assistant A).
- **Scope:** All tasks: boilerplate, bug fixes, writing tests, refactoring, and explaining legacy code.
- **Rule:** For any coding task, my first move was to ask the AI.

**Key Usage Stats:**
- **Total Prompts:** ~320 over 10 working days.
- **Breakdown:**
* Code generation: 45%
* Debugging/error explanation: 30%
* Writing tests (pytest): 15%
* Code review & refactoring suggestions: 10%
- **Perceived Success Rate (my judgment):** ~70% fully correct, ~25% needed minor tweaks, ~5% were completely off-track.

**A Concrete Example & Best Practice:**
I found it excelled at turning comments into test cases. Instead of writing the test from scratch, I'd describe the scenario.

My prompt:
```python
# Write a pytest for this function:
def process_item(item: dict) -> int:
"""Returns item['value'] if present and positive, else 0."""
# ... (implementation)
# Include edge cases for missing key, negative value, and non-dict input.
```

The assistant generated a solid test suite with parametrized tests, which I then refined. This pattern saved me a ton of time.

**Perceived Impact:**
- **Positive:** Velocity on boilerplate and repetitive tasks skyrocketed. Felt like a pair programmer that never gets tired. It was fantastic for generating fixtures and mock data.
- **Neutral:** For complex logic, it often gave a *plausible* but subtly wrong answer. I had to stay vigilant.
- **Negative:** It sometimes created a "lazy" impulse—I'd accept its first draft without deeply thinking through the design.

**My Takeaway:**
It's a powerful multiplier for a senior dev who can critically review its output, but it's not a substitute for understanding. The biggest win was offloading the "mental grunt work," letting me focus on architecture and tricky problems.

Has anyone else done a similar focused trial? I'd love to compare notes on how you structured it and what you learned!

Happy coding!