>Since the database is used by everyone, it becomes cared for by no one. Startups don’t have the luxury of a DBA, and everything owned by no one is owned by infrastructure eventually.
This post was a great read.
Tangent to this, I've always found "best practices" to be a bit of a misnomer. In most cases in software and especially devops I have found it means "pay for this product that constrains the way that you do things so you don't shoot yourself in the foot". It's not really a "practice" if you're using a product that gives you one way to do something. That said my company uses a very similar tech stack and I would choose the same one if I was starting a company tomorrow, despite the fact that, as others have mentioned, it's a ton to keep in your head all at once.
> In most cases in software and especially devops I have found it means "pay for this product that constrains the way that you do things so you don't shoot yourself in the foot". It's not really a "practice" if you're using a product that gives you one way to do something.
The good thing about a lot of devops saas is that you're not paying anyone on staff to understand the problem domain and guide your team. The bad thing is that you're not paying anyone on staff to understand the problem domain and guide your team.
My company has the github page for it blocked. They block lots of AI-related things but that's the only one I've seen where they straight up blocked viewing the source code for it at work.
Hey pretty cool! I recently added a similar feature to my neovim setup. I can press a keymap and cycle through all of the unstaged git hunks with each shown in a preview window. I can also change the base branch to one that, say, I'm trying to merge into so that I can have the same workflow when doing code reviews.
People like to make fun of these models for sounding like a broken record, being over complementary, etc, but I'm actually starting to think that models having a very recognizable style is a good thing because it makes identifying AI-generated content in the wild really easy. Sure, the verbosity is annoying when I'm just trying to get a straightforward, simple answer from it. But I like that I can have a pretty good sense of when content on the Internet is low-effort AI spam. If models become too good at emulating the personality of a real human, then that gets lost.
What are folks doing who were just using it for CI/test/dev environments? Just build the image yourself? Use Garage as some have suggested? I'm curious what people see as the pros and cons.
This is pretty neat. Similarly, I feel like we are really close to smartwatches being able to replace smartphones for all essential tasks. I try to rely on my apple watch with cellular as much as I can and leave my phone at home. I can't wait until agents get a bit better at navigating the web and someone makes a killer UI for the watch. I'll be able to do everything I need to do with a much more ambient device that doesn't suck attention the way a smartphone does.
I'm a rank and file dev at a non-big tech company and I got a call from a Windsurf sales rep this week who I had connected with on LinkedIn the day before (I never gave them my number). They told me my company was in talks with Windsurf about a licensing deal but that they would give me a 30 day trial of an enterprise account for use on personal projects to let me try it in advance. I guess the idea for them is to build enthusiasm among devs in the company?
Is this a standard sales strategy for products like this? It seems pretty aggressive to me but I'm just an engineer so I wouldn't know.
Very standard yep. Sales folks are sort of trained /indoctrinated into telling white lies like that in order to get in the door. There are loads of examples of using fake momentum to close deals. If its a senior person it’s “My CEO asked me to personally reach out to you” or a fake email from the CEO forwarded by the rep. If one person at the company uses it, it’s “we’re negotiating a company wide license” or “we already have a group license with extra seats” or “one of your teammates sent us a list of priority teammates” yada yada.
As it pertains to Python in particular I think OOP is great for libraries but of limited usefulness at the application layer. Things like pytorch's nn.module IMO is a great abstraction, but every time I've tried to map some concrete business concept to an OOP construct I've regretted it.
I recently watched a talk by the author of uv that was surprisingly fascinating [1]. He goes into a few of the more notable hacks that they had to come up with to make it as fast as it is. The most interesting thing for me was that package resolution in python given constraints defined (eg. in requirements.txt) maps to a boolean satisfiability problem which is NP-complete. So uv uses a custom SAT solver to do this. I totally under-appreciated how much goes into this software and I'm bummed I have to use Poetry at work after having watched this talk.
This post was a great read.
Tangent to this, I've always found "best practices" to be a bit of a misnomer. In most cases in software and especially devops I have found it means "pay for this product that constrains the way that you do things so you don't shoot yourself in the foot". It's not really a "practice" if you're using a product that gives you one way to do something. That said my company uses a very similar tech stack and I would choose the same one if I was starting a company tomorrow, despite the fact that, as others have mentioned, it's a ton to keep in your head all at once.
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