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Show HN: Plandex – an AI coding engine for complex tasks

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Re: Show HN: Plandex – an AI coding engine for complex tasks

#61

Congrats on the launch. Can you please compare and contrast Plandex features with another similar solution like aider[1] which also helps solve similar problem. [1] https://github.com/paul-gauthier/aider

Thanks! Sure, I posted this comment in a Reddit thread a couple days ago to a user who asked the same question (and I added one additional point): First I should say that it’s been a few months at least since I’ve used aider, so it’s possible my impression of it is a bit outdated. Also I’m a big fan of it and drew a lot of inspiration from it. That said: Plandex is more focused on building larger and more complex fun…

Thank you. Branches to explore different approaches is a really good idea, since LLMs are most powerful when they are used as a rubber duck to generate boilerplate templates and this can help get multiple perspectives. Going to test it soon.

Re: Show HN: Plandex – an AI coding engine for complex tasks

#62

It's pretty annoying that every project like this lately is just a wrapper for OpenAI API calls.

Supporting more models, including Claude, Gemini, and open source models is definitely at the top of the roadmap. Would that make it less annoying? :)

I think OpenAI is still the best of the bunch. Kind of feel like the others are kind of there to make people realize OpenAI works the best. Maybe when Gemini 1.5 is released?

Re: Show HN: Plandex – an AI coding engine for complex tasks

#64

Hi! Is it possible to tell Plandex that the code should pass all tests in, e.g., `tests.py`?

Hey! Not in an automated way (yet). But you can get pretty close by building your plan, applying it, and then piping the output of your tests back into Plandex:

  pytest tests.py | plandex load
  plandex tell "update the plan files to fix the failing tests from the included pytest output"

Re: Show HN: Plandex – an AI coding engine for complex tasks

#66
post #60

Earlier quoted context omitted.

Yes, well said. Doing exactly this kind of thing for months with ChatGPT is what convinced me the idea could work in the first place. I knew the underlying intelligence was there--the challenge is giving it the right prompts and supporting infra.

Do you have any of the issues where ChatGPT tends to forget the first parts of it’s context window? It could have the information explicitly spelled out, but if it weren’t in the last 2K tokens or so it’d just start to hallucinate stuff for me.

Plandex uses gradual summarization as the conversation gets longer (the exact cutoff point in terms of tokens is configurable via `plandex set-model`). So eventually, with a long enough plan, you can start to lose some resolution. That said, assuming you use the default gpt-4-turbo model with a 128k context window, you'd need to go far beyond 2k tokens before you'd start seeing anything like that.

We don't know what ChatGPT's summarization strategy is since it's closed source, but it does seem to be quite a bit more aggressive than Plandex's.

Re: Show HN: Plandex – an AI coding engine for complex tasks

#67
post #65

Congrats! Looks great, and I can't wait to try it. Do you support AzureOpenAI with custom endpoints? Are any special settings necessary to disable telemetry or non-core network requests?

Thanks! It doesn't yet support custom endpoints, but it will soon. I'd recommend either joining the Discord (https://discord.gg/plandex-ai) or watching the repo for updates if you want to find out when this gets released.

If you self-host the server, there is no telemetry and no data is sent anywhere except to your self-hosted server and OpenAI.

Re: Show HN: Plandex – an AI coding engine for complex tasks

#68
post #37

This approach works. I just built a SPA in 3 days with GPT-4 of which about 50% was generated. My only tooling was a bash script to list all the files in the repo (with some exceptions), including a README.md planning the project, a file list, and at the end I type my task. I run about 10-15 rounds with it. At the beginning I was using GPT more heavily, but in the middle I found it easier to just fix the code myself.…

What’s your experience with API cost? I've also tried something similar, but I often end up using up my balance too quickly.

Re: Show HN: Plandex – an AI coding engine for complex tasks

#69

Congrats on the launch. Can you please compare and contrast Plandex features with another similar solution like aider[1] which also helps solve similar problem. [1] https://github.com/paul-gauthier/aider

Thanks for mentioning aider! I haven't had a chance to look closely at plandex, but have read the author's description of differences wrt aider. I'd add a few comments:

I think the plandex UX is novel and interesting. The idea of a git-like CLI with various stateful commands is a new one in this space of ai coding tools. In contrast, aider uses a chat based "pair programming" UX, where you collaborate with the AI and ask for a sequence of changes to your local git repo.

The plandex author highlights that it makes changes in a "version-controlled sandbox" and can "rewind" unwanted changes.

These capabilities are all available "for free" in aider, because it is tightly integrated with git. Each AI change is automatically git committed with a sensible commit message. You can type “/diff” to check the diff, or "/undo" to undo any AI commit that you don't like. Or you can use "/git checkout -b " to start working on a branch to explore a longer sequence of changes, etc.

All your favorite git workflows are supported by invoking familiar git commands with "/git ..." inside the aider chat, or using any external git tooling that you prefer. Aider notices any changes in the underlying repo, however they occur.

Re: Show HN: Plandex – an AI coding engine for complex tasks

#70
post #37

This approach works. I just built a SPA in 3 days with GPT-4 of which about 50% was generated. My only tooling was a bash script to list all the files in the repo (with some exceptions), including a README.md planning the project, a file list, and at the end I type my task. I run about 10-15 rounds with it. At the beginning I was using GPT more heavily, but in the middle I found it easier to just fix the code myself.…

What’s your experience with API cost? I've also tried something similar, but I often end up using up my balance too quickly.

I can generally have these tools solve a simple issue in about 0.1 USD, or "complex" issues in 1-2 USD (complex generally just means that I'm spending time prompt engineering to get the model to do the right thing).
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