[haxton]

The demos I see for these types of tools are always some toy project and doesn't reflect day to day work I do at all. Do you have any example PRs on larger more complex projects that have been written with codebuff and how much of that was human interactive?

The real problem I want someone to solve is helping me with the real niche/challenging portion of a PR, ex: new tiptap extension that can do notebook code eval, migrate legacy auth service off auth0, record and replay API GET requests and replay a % of them as unit tests, etc.

So many of these tools get stuck trying to help me "start" rather than help me "finish" or unblock the current problem I'm at.

[jahooma]

I hear you. This is actually a foundational idea for Codebuff. I made it to work within the large-ish codebase of my previous startup, Manifold Markets.

I want the demos to be of real work, but somehow they never seem as cool unless it's a neat front end toy example.

Here is the demo video I sent in my application to YC, which shows it doing real stuff: https://www.loom.com/share/fd4bced4eff94095a09c6a19b7f7f45c?...

[tyre]

This comment makes me think of Coke vs. Pepsi.

Historically, Pepsi won taste tests and people chose Coke. Because Pepsi is sweeter, so that first sip tastes better. But it's less satisfying—too sweet—to drink a whole can.

The sexy demos don't, in my opinion and experience, win over the engineers and leaders you need. Lil startups, maybe, and engineers that love the flavor of the week. But for solving real, unsexy problems—that's where you'll pull in organizations.

[brandonchen]

> The sexy demos don't, in my opinion and experience, win over the engineers and leaders you need.

Great point, we're in talks with a company and this exact issue came up. An engineer used Codebuff over a weekend to build a demo app, but the CEO wasn't particularly interested even after he enthusiastically explained what he made. It was only when the engineer later used Codebuff to connect the demo app to their systems that the CEO saw the potential. Figuring out how to help these two stakeholders align with one another will be a key challenge for us as we grow. Thanks for the thought!

[edanm]

> Historically, Pepsi won taste tests and people chose Coke. Because Pepsi is sweeter, so that first sip tastes better. But it's less satisfying—too sweet—to drink a whole can.

As a Pepsi drinker (Though Pepsi Max/Zero), I disagree with this. That's one interpretation, the other is the one Pepsi was gesturing at - that people prefer Coke when knowing it's Coke, because of branding, but with branding removed, prefer Pepsi.

I personally drank Coke Zero for years, always being "unhappy" when a restaurant only had Pepsi, until one day I realized I was actually enjoying the Pepsi more when not thinking about it, and that the only reason I "preferred" Coke was the brand. So I know that this story can also be true, at least on n=1 examples.

[reportgunner]

Watching the demo it seems like it would be more effective to learn the skills you need rather than using this for a decade.

It takes 5+ seconds just to change one field to dark mode, I don't even want to imaigne a situation where I have two fields and I want to explain that I need to change this field and not that field.

I'm not sure who is the target audience for this, people who want to be programmers without learning programming ?

[senko]

My 2c as someone who worked on a similar product:

> it seems like it would be more effective to learn the skills you need rather than using this for a decade.

Think of it as a calculator. You do want to be able to do addition, but not neccessarily to manually add 4-digit numbers in your head.

> It takes 5+ seconds just to change one field to dark mode

Our current LLMs are way too slow for this. I am chuckling every time someone says "we don't need LLMs to be faster because people can't read faster". Imagine this using Groq with a future model with similar capability level, and taking 0.5 seconds to do this small change.

People need to remember we're at the very beginning of using AI for coding. Of course it's suboptimal for majority of cases. Unless you believe we're way past half the sigmoid curve on AI improvements (which I don't), consider that this is the worst the AI is ever going to be for coding.

A year ago people were incredulous when told that AI could code. A year before that people would laugh you out of the room. Now we're at the stage where it kinda works, barely, sometimes. I'm bullish on the future.

[bambax]

Every experience I have had with LLMs generating code. LLMs tend to follow the prompt much too closely and produce large amounts of convoluted code that in the end prove not only unnecessary but quite toxic.

Where LLMs shine is in being a personal Stack Overflow: asking a question and having a personalized, specific answer immediately, that uses one's data.

But solving actual, real problems still seem out of reach. And letting them touch my files sound crazy.

(And yes, ok, maybe I just suck at prompting. But I would need detailed examples to be convinced this approach can work.)

[brandonchen]

I'm sure your prompting is great! It's just hard because LLMs tend to be very wordy by default. This was something we struggled with for a while, but I think we've done a good job at making Codebuff take a more minimal approach to code edits. Feel free to try it, let me know if it's still too wordy/convoluted for you.

[handfuloflight]

> LLMs tend to follow the prompt much too closely

> produce large amounts of convoluted code that in the end prove not only unnecessary but quite toxic.

What does that say about your prompting?

[jeswin]

> Do you have any example PRs on larger more complex projects that have been written with codebuff and how much of that was human interactive?

We have a lot of code in production which are AI written. The important thing is that you need to consciously make a module or project AI-ready. This means that things like modularity and smaller files are even more important than they usually are.

I can't share those PRs, but projects on my profile page are almost entirely AI written (except the https://bashojs.org/ link). Some of them might meet your definition of niche based on the example you provided.

[zh2408]

This is so REAL: LLMs suck probably because your modularity sucks LOL

[cratermoon]

Kind of like "please describe the solution and I will write code to do it". That's not how programming works. Writing code and testing it against expectations to get to the solution, that's programming.

[brandonchen]

FWIW I don't find that I'm losing good engineering habits/thought processes. Codebuff is not at the stage where I'm comfortable accepting its work without reviewing, so I catch bugs it introduces or edge cases it's missed. The main difference for me is the speed at which I can build now. Instead of fussing over exact syntax or which package does what, I can keep my focus on the broader implications of a particular architecture or nuances of components, etc.

I will admit, however, that my context switching has increased a ton, and that's probably not great. I often tell Codebuff to do something, inevitably get distracted with something else, and then come back later barely remembering the original task

[mathgeek]

Language is important here. Programming, at its basic definition, is just writing code that programs a machine. Software development or even design/engineering are closer to what you’re referring to.

[Aeolun]

> ex: new tiptap extension that can do notebook code eval

Claude wrote me a prosemirror extension doing a bunch of stuff that I couldn’t figure out how to do myself. It was very convenient.

[craigds]

+1; Ideally I want a tool I don't have to specify the context for. If I can point it via config files at my medium-sized codebase once (~2000 py files; 300k LOC according to `cloc`) then it starts to get actually usable.

Cursor Composer doesn't handle that and seems geared towards a small handful of handpicked files.

Would codebuff be able to handle a proper sized codebase? Or do the models fundamentally not handle that much context?

[jahooma]

Yes. Natively, the models are limited to 200k tokens which is on the order of dozens of files, which is way too small.

But Codebuff has a whole preliminary step where it searches your codebase to find relevant files to your query, and only those get added to the coding agent's context.

That's why I think it should work up to medium-large codebases. If the codebase is too large, then our file-finding step will also start to fail.

I would give it a shot on your codebase. I think it should work.

[cratermoon]

RAG is a well-known technique now, and to paraphrase Emily Bender[1], here are some reasons why it's not a solution.

The code extruded from the LLM is still synthetic code, and likely to contain errors both in the form of extra tokens motivated by the pre-training data for the LLM rather than the input texts AND in the form of omission. It's difficult to detect when the summary you are relying on is actually missing critical information.

Even if the set up includes the links to the retrieved documents, the presence of the generated code discourages users from actually drilling down and reading them.

This is still a framing that says: Your question has an answer, and the computer can give it to you.

1 https://buttondown.com/maiht3k/archive/information-literacy-...

[jahooma]

We actually don't use RAG! It's not that good as you say.

We build a description of the codebase including the file tree and parsed function names and class names, and then just ask Haiku which files are relevant!

This works much better and doesn't require slowly creating an index. You can just run Codebuff in any directory and it works.

[michaelmior]

It sounds like it's arguably still a form of RAG, just where the retrieval is very different. I'm not saying that to knock your approach, just saying that it sounds like it's still the case where you're retrieving some context and then using that context to augment further generation. (I get that's definitely not what people think of when you say RAG though.)

[brandonchen]

Genuine question: at what point does the term RAG lose its meaning? Seems like LLMs work best when they have the right context, and that context must be pulled from somewhere for the LLM. But if that's RAG, then what isn't? Do you have a take on this? Been struggling to frame all this in my head, so would love some insight.

[petesergeant]

> We build a description of the codebase including the file tree and parsed function names and class names

This sounds like RAG and also that you’re building an index? Did you just mean that you’re not using vector search over embeddings for the retrieval part, or have I missed something fundamental here?

[jahooma]

Ah yeah, that's what I mean! I thought RAG is synonymous with this vector search approach.

Either way, we do the search step a little different and it works well.

[craigds]

I'll need to get approval to use this on that codebase. I've tried it out on a smaller open-source codebase as a first step.

For anyone interested:

  - here's the Codebuff session: https://gist.github.com/craigds/b51bbd1aa19f2725c8276c5ad36947e2
  - The result was this PR: https://github.com/koordinates/kart/pull/1011

It required a bit of back and forth to produce a relatively small change, and I think it was a bit too narrow with the files it selected (it missed updating the implementations of a method in some subclasses, since it didn't look at those files)

So I'm not sure if this saved me time, but it's nevertheless promising! I'm looking forward to what it will be capable of in 6mo.

[asattarmd]

What's the fundamental limitation to context size here? Why can't a model be fine-tuned per codebase, taking the entire code into context (and be continuously trained as it's updated)?

Forgive my naivety, I don't now anything about LLMs.

[amethystcookie]

It's pretty good for complex projects imo because codebuff can understand the structure of your codebase and which files to change to implement changes. It still struggles when there isn't good documentation, but it has helped me finish a number of projects

[handfuloflight]

> It still struggles when there isn't good documentation

@Codebuff team, does it make sense to provide a documentation.md with exposition on the systems?

[jahooma]

One cool thing you can do is a ask Codebuff to create these docs. In fact, we recommend it.

Codebuff natively reads any files ending in "knowledge.md", so you can add any extra info you want it to know to these files.

For example, to make sure Codebuff creates new endpoints properly, I wrote a short guide with an example on the three files you need to update, and put it in backend/api/knowledge.md. After that, Codebuff always create new endpoints correctly!

[amethystcookie]

you can put the information into knowledge.md or [description].knowledge.md, but sometimes I can't find documentation and we're both learning as we go lmao

[SpaghettiX]

Absolutely! Imaging setting a bunch of css styles through a long winded AI conversation, when you could have an IDE to do it in a few seconds. I don't need that.

The long tail of niche engineering problems is the time consuming bit now. That's not being solved at all, IMHO.

[bung]

> ... setting a bunch of css styles through a long winded AI conversation

Any links on this topic you rate/could share?

[badestrand]

"On the checkout page at the very bottom there are two buttons that are visible when the user chooses to select fast shipping. The right one of those buttons should be a tiny bit more round and it seems like it's not 100% vertically aligned with the other button."

Takes a lot longer to write than just diving into the code. I think that's what they meant.

[fragmede]

Which IDE do you use for CSS editing/adjustment?

[SpaghettiX]

I mostly mean the text editing functionality I guess. Visual Studio Code is the IDE I use

[brandonchen]

Great question – we struggled for a long time to put our demo together precisely for this reason. Codebuff is so useful in a practical setting, but we can't bore the audience with a ton of background on a codebase when we do demos, so we have to pick a toy project. Maybe in the future, we could start our demo with a half-built project?

Hopefully the demo on our homepage shows a little bit more of your day-to-day workflows than other codegen tools show, but we're all ears on ways to improve this!

To give a concrete example of usefulness, I was implementing a referrals feature in Drizzle a few weeks ago, and Codebuff was able to build out the cli app, frontend, backend, and set up db schema (under my supervision, of course!) because of its deep understanding of our codebase. Building the feature properly requires knowing how our systems intersect with one another and the right abstraction at each point. I was able to bounce back and forth with it to build this out. It felt akin to working with a great junior engineer, tbh!

EDIT: another user shared their use cases here! https://news.ycombinator.com/item?id=42079914

[eterm]

Why not take a large and complex code-base such as the firefox source code, feed that in and demonstrate how that goes?

[echelon]

If you're not worried about showing off little hints of your own codebase, record running it on one of your day to day engineering tasks. It's perfect dog fooding and would be a fun meta example.

> To give a concrete example of usefulness, I was implementing a referrals feature in Drizzle a few weeks ago, and Codebuff was able to build out the cli app, frontend, backend, and set up db schema

Record this!

Better yet, stream it on Twitch and/or YouTube and/or Discord and build a small community of followers.

People would love to watch you.

[brandonchen]

Great idea! We were kicking around something like this, but couldn't get it ready in time for today's launch – but keep your eyes peeled! Our Discord community is a great place to stay up to date.

Yup, I had the same thought. I just ran into an issue during today's launch and used Codebuff to help me resolve it: https://www.tella.tv/video/solving-website-slowdown-with-ai-.... Next time, I'll try to record before I start working, but it's hard to rememeber sometimes.