> Privacy is kinda big because of the client data but I can scrub local stuff if needed Honestly, I've been in that exact spot with a big fintech client last year. One tiny slip up with a data leak and you're basically cooked professionally. In my experience, even if you try to scrub things, sending your whole logic flow to some cloud model feels sketchy. Over the years I've learned that safety beats speed every time, tho I get the deadline pressure. I eventually settled on JetBrains PyCharm Professional Edition combined with the JetBrains AI Assistant Subscription. It fits right in your budget at around $25 a month for the assistant part. The thing is, PyCharm has been indexing Python code for ages. It actually understands your SQLAlchemy graph and your async workers because it uses the IDE internal symbols, not just some fuzzy context window. It doesn't just hallucinate methods as much because it knows your exact venv library versions. If you're really worried about that Seattle client's privacy, you might also look at the Continue.dev VS Code Extension paired with a local model using Ollama Local LLM Runner. You can run it on your own hardware so zero data leaves your machine. It's a bit of a steeper learning curve to set up but it is the only way I sleep at night when handling multi-tenant pipelines. Don't trust the hype of the web-only tools for stuff this complex... you need something that actually knows what a Python type hint is.

Honestly, if you are hitting that wall with Copilot, I would strongly suggest you look into Cursor AI Code Editor. I have been using it for a complex Django and Celery stack recently and the codebase indexing feature is a game changer for project-wide context. Be careful though, you really need to make sure you enable the indexing manually sometimes or it might miss those deep SQLAlchemy relationships you mentioned. I would suggest trying it specifically with the Anthropic Claude 3.5 Sonnet model instead of GPT-4o. In my experience, Sonnet handles those nested Python logic blocks and async tasks with way fewer hallucinations. Just a heads up, the privacy mode is decent but you should still double check your local settings if you are handling sensitive client schemas. It can be a bit heavy on system resources during the initial index, so just keep an eye on that... it can be quite resource intensive.

Finally someone says it. Ive been thinking this for a while but wasnt sure.

Re: "Honestly, if you are hitting that wall with..." - man, I've been through the ringer with these tools lately too. I spent a small fortune on different subscriptions last year only to find out they were mostly just hype when it came to actual production-level Python. I had such a bad experience with some of the premium assistants just totally losing the plot on my async logic and nested mappings. It was honestly such a letdown after hearing all the praise. I eventually tried out Sourcegraph Cody and was pretty surprised. It is way cheaper than those $20+ tiers elsewhere and actually seems to try harder with project-wide context by using local embeddings. If you're really trying to stay under that $30 budget, you should definitely check out the Continue extension for VS Code too. I've been pairing it with a DeepSeek Coder V2 API key and it costs me pennies compared to a flat monthly fee. It is not perfect and sometimes it still misses the mark on those deep SQLAlchemy joins, which is super frustrating, but at least I am not paying a premium price for those mistakes. It is kinda disappointing how much hand-holding these smart tools still need tho...

Building on the earlier suggestion, I remember when I finally hit that wall where my scripts turned into actual architecture and my tools just couldnt keep up. I spent weeks messing with different plugins until I just went all-in on a dedicated environment.

• Honestly, just go with the JetBrains AI Assistant and use it inside their Python-specific environment.
• The indexing is way more robust because the IDE already knows the project structure before the AI even gets involved.
• I found it handles those deep SQLAlchemy joins way better because it sees the whole schema, not just the file you are currently editing. It basically solved my reliability issues when I was migrating a bunch of legacy data pipelines last year. Its not perfect but it definitely feels more professional and less like a toy than some other extensions. If you are already used to something like JetBrains PyCharm Professional, the transition is basically seamless and handles those complex dependencies without breaking a sweat.

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