AI Engineering Buildcamp: from RAG to Agents Cohort 3
Homework 5: Monitoring Statistics
Distribution of scores and reported study time for this homework.
Score distribution
All values are points.
| Metric |
Min |
Q1 |
Median |
Average |
Q3 |
Max |
| Questions score |
5 |
5.8 |
6.5 |
6.3 |
7.0 |
7 |
| Learning in public score |
- |
0.0 |
0.0 |
0.0 |
0.0 |
- |
| Total score |
5 |
5.8 |
6.5 |
6.3 |
7.0 |
7 |
Questions score
- Min
- 5
- Median
- 6.5
- Max
- 7
- Q1
- 5.8
- Avg
- 6.3
- Q3
- 7.0
Learning in public score
- Min
- -
- Median
- 0.0
- Max
- -
- Q1
- 0.0
- Avg
- 0.0
- Q3
- 0.0
Total score
- Min
- 5
- Median
- 6.5
- Max
- 7
- Q1
- 5.8
- Avg
- 6.3
- Q3
- 7.0
Time distribution
All values are hours reported by students.
| Metric |
Min |
Q1 |
Median |
Average |
Q3 |
Max |
| Lectures |
0.8 |
1.4 |
2.0 |
2.3 |
3.0 |
4.0 |
| Homework |
1.0 |
2.1 |
3.3 |
2.9 |
4.0 |
4.0 |
Lectures
- Min
- 0.8
- Median
- 2.0
- Max
- 4.0
- Q1
- 1.4
- Avg
- 2.3
- Q3
- 3.0
Homework
- Min
- 1.0
- Median
- 3.3
- Max
- 4.0
- Q1
- 2.1
- Avg
- 2.9
- Q3
- 4.0
Question breakdown
Correctness and answer distribution per question.
1. Create and Run the Agent
8 / 8 correct
(100.0%)
1
get_categories
8 (100.0%)
2
get_questions
0 (0.0%)
3
get_trivia
0 (0.0%)
4
fetch_questions
0 (0.0%)
2. Set Up Monitoring
6 / 8 correct
(75.0%)
1
trivia agent
1 (12.5%)
2
agent run
6 (75.0%)
3
pydantic_ai.agent
1 (12.5%)
4
openai.chat
0 (0.0%)
3. Play a Full Session
8 / 8 correct
(100.0%)
1
1
0 (0.0%)
2
3
0 (0.0%)
3
6
8 (100.0%)
4
10
0 (0.0%)
4. Grouping Traces
5 / 8 correct
(62.5%)
1
Less than 2,000
1 (12.5%)
2
2,000 - 10,000
5 (62.5%)
3
10,000 - 20,000
2 (25.0%)
4
More than 20,000
0 (0.0%)
5. Get Trace IDs with SQL
8 / 8 correct
(100.0%)
| Answer |
Count |
| 019e3ceede9548d50cfa17984228e77d |
1 |
| 019e4b755c0ce5de750f77b1eb8eeb19 |
1 |
| 019e47557826eb59c16d5e7e47e0bb63 |
1 |
| 019e0802a67c0875b0ca29a2a402ac12 |
1 |
| 019e7a3196dd38df24ba6b24334dda85 |
1 |
| 019e31593d952633d7a3b53c02917b42 |
1 |
| 019e26cbd5b227a975eb2d22894520b1 |
1 |
| 019e283fe0cca0caf25daa2431884c38 |
1 |
6. Reconstruct Runs and Calculate Costs
8 / 8 correct
(100.0%)
1
Less than $0.01
8 (100.0%)
2
$0.01 - $0.05
0 (0.0%)
3
$0.05 - $0.10
0 (0.0%)
4
More than $0.10
0 (0.0%)
7. Feedback Tracking
7 / 8 correct
(87.5%)
1
By using logfire.attach_context() with the session context
7 (87.5%)
2
By storing feedback in the agent output
0 (0.0%)
3
By creating a new Logfire project for each run
0 (0.0%)
4
By using logfire.error() instead of logfire.info()
1 (12.5%)
Calculated:
11 June 2026, 20:15