This is exactly the CLI I'm referring to, whose name implies it's for playing around with "vibe-coding", instead of helping professional developers produce high quality code. It's the opposite of what I and many others are looking for.
Claude Code not good enough for ya?
Still, I do use Claude Code and Codex daily as there is nothing better out there currently. But they still feel tailored towards vibe-coding instead of professional development.
I find the flow works bc if it starts going off piste I just end it. Plus I then get my pre-commit hooks etc. I still like being relatively hands on though.
Trying to follow along better is exactly the opposite of what I'd advocate - it's a waste of time especially with Claude, as Claude tends to favour trying lots of things, seeing what works, and revising its approach multiple times for complex tasks. If you follow along every step, you'll be tearing your hair out over stupid choices that it'll undo within seconds if you just let it work.
Err, doesn’t it have /review?
Imagine a GUI built around git branches + agents working in those branches + tooling to manage the orchestration and small review points, rather than "here's a chat and tool calling, glhf".
All of the models that can do tool calls are typically good enough to use Git.
Just this week I used both Claude Code and Codex to look at unstaged/staged changes and to review them multiple times, even do comparison between a feature branch and the main branch to identify why a particular feature might have broken in the feature branch.
But again, it's the "user message > llm reason > llm tool call > tool response > llm reason > llm response" flow I think is inefficient and not good enough. It's a lazy solution built on top of the chat flow.
What I imagined would exist by now would be something smarter, where you don't say "Ok, now please commit this" or whatever.
I already have a tool for myself that launch Codex, Claude Code, Qwen Code(r?) and Gemini for each change I do, and automatically manage them into git branches, and lets me diff between what they do and so on.
Yet I still think we haven't really figured out a good UX for this.
While True:
0. Context injected automatically. (My repos are small.)
1. I describe a change.
2. LLM proposes a code edit. (Can edit multiple files simultaneously. Only one LLM call required :)
3. I accept/reject the edit.
The chat interface is optimal to me because you often are asking questions and seeking guidance or proposals as you are making actual code changes. On reason I do like it is that its default mode of operation is to make a commit for each change it makes. So it is extremely clear what the AI did vs what you did vs what is a hodge podge of both.
As others have mentioned, you can integrate with your IDE through the watch mode. It's somewhat crude but still useful way. But I find myself more often than not just running Aider in a terminal under the code editor window and chatting with it about what's in the window.
> The chat interface
Seems very much not, if it's still a chat interface :) Figuring out a chat UX is easy compared to something that was creating with letting LLM fill in some parts from the beginning. I guess I'm searching for something with a different paradigm than just "chat + $Something".
It's all very fluffy and theoretical of course.
"I want you to do feature X. Analyse the code for me and make suggestions how to implement this feature."
Then it will go off and work for a while and typically come back after a bit with some suggestions. Then iterate on those if needed and end with.
"Ok. Now take these decided upon ideas and create a plan for how to implement. And create new tests where appropriate."
Then it will go off and come back with a plan for what to do. And then you send it off with.
"Ok, start implementing."
So sure. You probably can work on this to make it easier to use than with a CLI chat. It would likely be less like an IDE and more like a planning tool you'd use with human colleagues though.
So you'd write a function name and then tell it to flesh it out.
function factorial(n) // Implement this. AI!
function factorial(n) {
if (n === 0 || n === 1) {
return 1;
} else {
return n \* factorial(n - 1);
}
}
I'm really curious to try Mistral's vibe, but even though I'm a big fanboi I don't want to be tied to just one model. Aider lets tier your models such that your big, expensive model can do all the thinking and then stuff like code reviews can run through a smaller model. It's a pretty capable tool
Edit: Fix formatting
Very much this for me - I really don't get why, given a new models are popping out every month from different providers, people are so happy to sink themselves into provider ecosystems when there are open source alternatives that work with any model.
The main problem with Aider is it isn't agentic enough for a lot of people but to me that's a benefit.
If you babysit every interaction, rather than reviewing a completed unit of work of some size, you're wasting your time second-guessing that the model won't "recover" from stupid mistakes. Sometimes that's right, but more often than not it corrects itself faster than you can.
And so it's far more effective to interact with it far more async, where the UI is more for figuring out what it did if something doesn't seem right, than for working live. I have Claude writing a game engine in another window right now, while writing this, and I have no interest in reviewing every little change, because I know the finished change will look nothing like the initial draft (it did just start the demo game right now, though, and it's getting there). So I review no smaller units of change than 30m-1h, often it will be hours, sometimes days, between each time I review the output, when working on something well specified.
What kind of hardware do you have to be able to run a performant GPT-OSS-120b locally?
There are many platforms out there that can run it decently.
AMD strix halo, Mac platforms. Two (or three without extra ram) of the new AMD AI Pro R9700 (32GB of RAM, $1200), multi consumer gpu setups, etc.
This is what we're building at Brokk: https://brokk.ai/
Quick intro: https://blog.brokk.ai/introducing-lutz-mode/
A surprising amount of programming is building cardboard services or apps that only need to last six months to a year and then thrown away when temporary business needs change. Execs are constantly clamoring for semi-persistent dashboards and ETL visualized data that lasts just long enough to rein in the problem and move on to the next fire. Agentic coding is good enough for cardboard services that collapse when they get wet. I wouldn't build an industrial data lake service with it, but you can certainly build cardboard consumers of the data lake.
But there is nothing more permanent that a quickly hacked together prototype or personal productivity hack that works. There are so many Python (or Perl or Visual Basic) scripts or Excel spreadsheets - created by people who have never been "developers" - which solve in-the-trenches pain points and become indispensable in exactly the way _that_ xkcd shows.
"There is nothing more permanent than a temporary demo"
What matters is high quality specifications including test cases
In my mind, it's somewhat orthogonal to code quality.
Waterfall has always been about "high quality specifications" written by people who never see any code, much less write it. Agile make specs and code quality somewhat related, but in at least some ways probably drives lower quality code in the pursuit of meeting sprint deadlines and producing testable artefacts at the expense of thoroughness/correctness/quality.
Says the person who will find themselves unable to change the software even in the slightest way without having to large refactors across everything at the same time.
High quality code matters more than ever, would be my argument. The second you let the LLM sneak in some quick hack/patch instead of correctly solving the problem, is the second you invite it to continue doing that always.
I have a feeling this will only supercharge the long established industry practice of new devs or engineering leadership getting recruited and immediately criticising the entire existing tech stack, and pushing for (and often succeeding) a ground up rewrite in language/framework de jour. This is hilariously common in web work, particularly front end web work. I suspect there are industry sectors that're well protected from this, I doubt people writing firmware for fuel injection and engine management systems suffer too much from this, the Javascript/Nodejs/NPM scourge _probably_ hasn't hit the PowerPC or 68K embedded device programming workflow. Yet...
I'm a bit saddened by the name of the CLI tool, which to me implies the intended usage. "Vibe-coding" is a fun exercise to realize where models go wrong, but for professional work where you need tight control over the quality, you can obviously not vibe your way to excellency, hard reviews are required, so not "vibe coding" which is all about unreviewed code and just going with whatever the LLM outputs.
But regardless of that, it seems like everyone and their mother is aiming to fuel the vibe coding frenzy. But where are the professional tools, meant to be used for people who don't want to do vibe-coding, but be heavily assisted by LLMs? Something that is meant to augment the human intellect, not replace it? All the agents seem to focus on off-handing work to vibe-coding agents, while what I want is something even tighter integrated with my tools so I can continue delivering high quality code I know and control. Where are those tools? None of the existing coding agents apparently aim for this...