agreed. dealing with a complex polygot projeft. mumtiple mongodb, node hell, etc. hard to onboard.. or move fast

In regards to docs, data and repos. What are you looking for specifically? What entails a good vs bad architecture for a company?

A consistent and well-organised approach across the data that could be used by AI, ideally with journalling and tracking to understand how things have changed over time.

This x1000.

I’ve tried every orm in node and nothing compares to Django orm. The way you can scaffold an apps data models is amazing.

Yeah it's crazy, people use Django and they think the things that are making them productive are all these little contribs and built-ins, but the reality is it's the solid foundation that is the ORM. BTW, I discovered after writing my comment that tortoise ORM is essentially Django ORM, but written on asyncpg, making it way faster. So, if you're stuck in some other non-Django framework and would like to use the Django ORM, that's probably your closest bet.

What do you recommend as an alternative?

IMO, the consumer grade mesh systems are basically commodities at this point.

Wire still wins - especially for backhauls between endpoint. However, it’s really nice being able to stick an AP anywhere you have an outlet to extend the range. I have a few outdoor devices (speakers, lights, TV) that daisy chain though APs while getting just good enough performance for what I need.

The closest alternative is probably tplink omada.

Teltonika also has started to create a similar solution but it is not in the same level just yet.

Would love to get thoughts from others on convex who have used it.

Django, rails or laravel. Big 3? Seem to make it easy

Cool. Can you share more about the tech? Ingestion engine - is this a background task that scrapes the web? You download the mp4 and convert to transcripts then generate embeddings? For each embedding of an episode - how do you break it down? Summary the episode and embed it with metadata? Are you using pydantic ai for structured output? Celery for tasks? Just a curious dev

Ingestion engine, it is indeed a cron job that runs once a day to get the latest podcast episodes posted. Yes it scrapes the web for episodes and then populates the database. And yup yup, I transcribe the audio to text, and process the text to get the embeddings using embedding models. The secret sauce is using language models to find promising snippets within each episode by running a sliding window over the transcript. So I actually make different types of embeddings, for highlights and also for episodes. I also make use of the metadata in podcast episodes to enhance recommendations, mainly by deriving the strength of the source making the content.

You are spot on, I use celery for tasks, many different kinds of tasks actually, super handy tool to have, it truly enhances what I am able to do on Heroku. My devops life becomes much more comfy

Same. I’m using Django with fast api. Then I have a nextjs front end. I do wish I could bake it all into Django but I’ve learned that it’s best to keep Django api first unless it’s a simple site/app. But with a lot of interaction, using react helps.

Fivetran should’ve done this a long time ago. I think that both etl and reverse etl is going open source route. With this ai world we live in now. You just need dagster or temporal - and a few lines of python.

Fivetran has been great. But in this new ai world. Something like dragster + dlt and sling. You can have your own fivetran developed in house. I haven’t dove too much into reverse etl- but it would be awesome to see a dtl like open source tool for reverse etl.