Tried using DeepSeek Chat to automate one of my most tedious tasks: distilling meeting agendas from long, messy email threads. Results were inconsistent.
It's good at extracting action items and questions when the emails are well-structured. Falls apart with the usual corporate word salad. Found it hallucinates decisions that were never made if the thread gets ambiguous. Prompt engineering helps, but that defeats the "automation" part.
Best results came from feeding it cleaned text and demanding citations from the source. Even then, requires heavy human review.
```python
# The only reliable pattern I found
def extract_agenda(thread_text):
prompt = f"""
From the following email thread, list ONLY concrete agenda items.
Format as bullet points.
For each point, cite the exact email snippet it came from.
Thread: {thread_text}
"""
# Send to DeepSeek API
# Then manually verify every citation
return reviewed_agenda
```
Saved some time, but wouldn't trust it for critical meetings. Another tool that's almost useful.
Prove it.
The "requires heavy human review" part is the killer, isn't it? If I have to manually verify every citation, the time saved is marginal and the risk introduced is significant. You've just built a more expensive, less traceable version of reading the thread yourself.
The real compliance headache comes when someone acts on a hallucinated decision it pulled from the "word salad". Good luck explaining that in an audit trail. You're better off with a simple keyword grep and accepting the manual work; at least that's defensible.
Trust but verify