What's a good place to start for a completely naive but interested user?

I'm on the free plan and have been using it via GitHub copilot instead, as the current project is a work one and they pay for that.

Before this I did a small project and I hit the 50 free tier limit through Zed by the time I was about 90% done. It was a small file drop app where internal users could create upload links, share them with people who could use them to upload a file. The internal user could then download that file. So it was very basic, but it churned out a reasonable UI and all the S3 compatible integration, etc.

I had to intervene a bit and obviously was reviewing everything and tweaking where needed. But I was surprised at how far I got on the 50 free prompts.

It's hard to know what you really get for that prompt limit though as I probably had a much higher number of actual prompts than they were registering. It's obviously using some token calculation under the hood and it's not clear what that is. All in all I probably had about 60-70 actual prompts I ran through it.

My gut says 500/mo would feel limited if I was going full "vibe" and having the LLM do basically everything for me every day. That said, this is the first LLM product I'm considering personally paying for. The integration with Zed is what wins for me over Claude, where you'd have to pay for API credits or use Claude Code. The way they highlight code changes and stuff really is nice.

Bit of a brain dump, sorry about that!

I have used Zed's plane with Claude and also Claude Code. They are very different experiences. Zed's agent work is very much a set it, go away, review, give some tips to it, iterate. As long as you use the Sonnet and absolutely avoid the burn mode (formerly max mode), it should do a lot of work for you. The main limitation I hit is the context window. As the codebase gets larger, it takes more context for it to get going and then it tends to have a hard time finishing. I find that about 4 prompts works for a feature that would take me a few hours to code.

For Claude Code, the limit is reset every 5 hours so if you hit it, you rest a bit. Not that big a deal to me. But the way it works I find much more stressful. It is reviewing just about everything it is doing. It is step-by-step. Some of it you can just say Yes, do it without permission, but it likes to run shell commands and for obvious reasons arbitrary shell commands need your explicit Yes for each run. This is probably a great flow if you want a lot of control in what it is doing. And the ability to intercede and redirect it is great. But if you want more of a "I just want to get the result and minimize my time and effort" then Zed is probably better for that.

I am also experimenting with OpenAI's codex which is yet a different experience. There it runs on repos and pull requests. I have no idea what their rate/limit stuff will be. I have just started working with it.

Of the three, disregarding cost, I like Zed's experience the best. I also think they are the most transparent. Just make sure never to use the burn mode. That really burns through the credits very quickly for no real discernible reason. But I think it is also limited to either small codebases or prompts that limit what the agent is going through to get up to speed due to the context window being about 120k (it is not 200k as the view seems to suggest).

It's not the long tail. It's that the HEAD of packages in Elixir are also often poorly maintained or not maintained. The fundamental question for any developer: can I be productive quickly? Despite all that Elixir has going for it, the answer is often "no."

Want a first-party client library for the service you're using? Typically the answer is "too bad, Elixir developer." And writing your own Finch or Req wrapper for their REST endpoint simply isn't a valid answer.

>For its size, Elixir is doing quite well.

I'm actually arguing the opposite. Elixir is not doing well because of its size. So how can that be influenced and changed?

Most languages require maintenance.

Some languages—Clojure is a good example—have packages from 10 years ago, entirely unmaintained, that still work great because no maintenance is needed.

You must never have been a Ruby developer. “I notice this library hasn’t been updated in 8 days, is it still being maintained?”

good news, "immutable" is pretty much the only way that elixir is "functional" except for lambdas being first class datatypes (which is almost every language now)

This one?

https://www.youtube.com/live/V2b6QCPgFTk

But the models can run tools, so wouldn't they just run the code, not get the expected output, and then exclude the bad code from their training data?

For what its worth, AI already has subpar data. Atleast this is what I've heard.

I am not sure, but the cat is out of the box. I don't think we can do anything at this point.