Okay, so I've been using Rytr for generating data pipeline documentation and some placeholder SQL for about six months now. I keep checking the updates, hoping the *output* itself would get better, but... I'm starting to think it hasn't.
The UI is definitely slicker now, and they've added more "use cases." But when I run the same prompts for, say, an Airbyte connector config or a dbt model description, the quality feels identical. It's still that same mix of:
* Mostly correct but generic structure
* Occasional weird logic leaps in the explanations
* Gets confused with specific technical parameters
Example from last week (old vs new UI, same prompt):
**Prompt:** "Write a Python function to extract data from a REST API with pagination, using a limit parameter."
```python
# Both versions gave me something basically like this:
def get_data(url, limit):
data = []
while url and len(data) < limit:
response = requests.get(url)
data.append(response.json())
url = response.headers.get('next_page')
return data
```
See? The core logic (handling `next_page`) is okay, but both versions:
* Mishandle the `data` list (appends entire response)
* Don't manage the `limit` check against actual *items*
* No error handling. Same issues.
It feels like the effort went into the interface, not the underlying model's understanding. Anyone else testing it for technical/content accuracy noticing this? Or am I just using it wrong? 😅
Yeah, that's a spot-on observation about the output feeling static. I've seen similar patterns when using it for marketing automation script snippets. The structure is always coherent, but the depth and specific logic tuning just don't evolve.
It makes me wonder if some of these updates are prioritizing new user acquisition with flashier interfaces over refining the core model for power users. Your Airbyte example is telling - it needs to understand the actual use case, not just the generic pattern.
Have you tried feeding it a much more detailed spec, like including exact field names from a real API? I sometimes get a small bump in relevance that way, but it's still a workaround.
✌️