Thanks, that means a lot coming from someone who has clearly evaluated many of these stacks.
A few notes:
Celery is completely optional, it's there if you need background jobs, but the core app runs fine without it. Same with Redis, it falls back to filesystem sessions in development. The idea is to add complexity only when you actually need it.
And that is the beauty of open source. If you don't like Celery, swap it for RQ, Dramatiq or whatever fits your workflow. It's your code.
The stack is opinionated, but the opinion is simple, pick boring, battle tested tools and stay lean. No webpack, no heavy build chains, no node_modules black hole. Vue and Vuetify load from CDN in development and that is perfectly fine. It ships products just as well.
Django is fantastic, and if you're productive there, there is no reason to switch. But if you ever want something lighter where you wire up only what you need, give it a try.
Thanks for the kind words and thoughtful suggestions!
On the repos, they're intentionally separate projects. Enferno stays as a minimal Flask framework with fewer dependencies, ideal for anyone who wants a clean starting point. ReadyKit builds on top of Enferno with SaaS-specific features like workspaces, Stripe billing, and team collaboration. I plan to maintain both:
* Enferno: lean framework for general Flask projects
* ReadyKit: batteries-included SaaS template
This gives users the freedom to choose the level of complexity they need.
On the redirect, good point. I'll set that up so enferno.io links don't cause confusion.
On dark mode, fair feedback. I can add a dark mode toggle and will work on that.
But is it really vibe coding if you’re carefully building step by step and checking everything along the way? I feel like the kind of vibe coding people usually mean is more about blindly iterating until things work and patching bugs as they pop up—where you eventually get an app that runs, but it’s so messy that even a senior dev would struggle to audit or fully understand it.
The truth is I don't check everything along the way! That's part of my high scale, I can now work on a dozen projects instead of a couple because I'm freed up from having to read all of the code. A huge shift in mindset for sure, but it's been working great.
"Nosy Agent": A stateful life-optimization AI built on Anthropic’s API with a “Memory Trinity” (SQLite, ChromaDB, evolving brain files), time-aware context and secure CLI/Telegram interfaces; it proactively reminds you of projects, learns your energy rhythms and adapts its tone, dynamically evolves its memories and goals..
Unfortunately uWSGI (one of the most important libraries) is fundamentally incompatible with uv. had to roll back all my apps that use custom uWSGI for that reason.
I am using uwsgi with uv. This is not to say the problems you are facing are not real, but it cannot be a 'fundamental incompatibility' if it is working in my case.
Here is an example of a CLI invocation I am using for quick testing:
They are significantly better! IDEs aren’t just like LLMs; they transform your codebase into embeddings (knowledge), giving them a much greater advantage in understanding larger contexts and effectively acting on the code. Plus, they come with proper tool integrations, allowing them to apply changes seamlessly while including fallback mechanisms to handle any issues during the process.
>they transform your codebase into embeddings (knowledge), giving them a much greater advantage in understanding larger contexts and effectively acting on the code.
Is this true? Isn't the context size controlled by the model? Is there any difference (outside convenience) to pasting your code in the web interface?
Sure thing! They can’t just dump all the code from your repository into the context.
The first step is identifying the relevant code in your repo, likely using an indexed vector database. They probably transform your question or prompt into an embedding as well to enhance accuracy. Once they’ve pinpointed the relevant sections, they send those specific parts of your code to the LLMs for processing. I actually wrote an article diving deeper into this concept—check it out!
Anyone else feeling this weird vibe in the age of AI? You get a cool new idea, but then you think about how easy it is for someone else to replicate it, and you end up not doing it.
Often multiple times a day, but on top of that concern, also throw in various ethical concerns and a few questions about if it actually has value or should exist
A few notes:
Celery is completely optional, it's there if you need background jobs, but the core app runs fine without it. Same with Redis, it falls back to filesystem sessions in development. The idea is to add complexity only when you actually need it.
And that is the beauty of open source. If you don't like Celery, swap it for RQ, Dramatiq or whatever fits your workflow. It's your code.
The stack is opinionated, but the opinion is simple, pick boring, battle tested tools and stay lean. No webpack, no heavy build chains, no node_modules black hole. Vue and Vuetify load from CDN in development and that is perfectly fine. It ships products just as well.
Django is fantastic, and if you're productive there, there is no reason to switch. But if you ever want something lighter where you wire up only what you need, give it a try.
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