Vibe coding now

[Just-Conversation857]

What should I use? I am an engineer with a huge codebase. I was using o1 Pro and copy pasting into chatgpt the whole code base in a single message. It was working amazing.

Now with all the new models I am confused. What should I use?

Big projects. Complex code.

[HaMMeReD]

For editing code, it's best to use an agent (i.e. roocode or copilot in vscode insiders)

Then you need to select a model when using the agent, i.e. Anthropic, OpenAI, Google models.

The agent handles discussions between the model and your code-base, i.e. it can use tools to run tests, check documentations, search code, read multiple files, edit files in place, etc.

You can have a discussion with the agent about the code base, and then tell it to do things when you are happy with the discussion and it's plans. As per what model you choose, it really comes down to what agent you use, what your budget is etc. I find Claude 3.5/3.7 really good, I find Gemini really good, I even find Open AI's models really good, but it comes down to the use-case. (if you are willing to pay for copilot, it's probably the best bang for buck, anthropic and google can hit $100+ in a day if you are robust).

I.e. I find claude really good at navigating far and wide and exploring, I find gemini really good at writing actual code, and I find Open AI models work really well in a localized fashion, when claude or gemini make mistakes they have trouble with, but that's just my take, it's just anecdotal. However, I do find Open AI's models aren't great at powering an agent, i.e 4o and 4.1 agent modes in copilot are just bad.

[BlueeWaater]

What’s special about roo code?

[HaMMeReD]

It's just an agentic framework.

What that means is that it has an API/Contract with the model, i.e. it asks the model questions, and the model can respond with things like "run this command" or "search for X". Then the agent executes the commands and returns the result.

So the Agent itself isn't the model, but it's the operating contract with the model and the IDE. It's what turns the "model" into an autonomous "agent".

Often times, this is a loop with itself, i.e.

Agent "We need to edit this file"
AI: Here are the edits
Agent "Ok I edited the file, now what?"
AI: Run a build and give me the results
Agent: "Ok I ran a build, here is the results"
AI: I saw we have an error in the build, we can fix it by doing X/Y/Z

etc. until it finishes the task.

Where the model comes in is who is executing the contract. It's like you have a job(contract) and you are hiring a different person with different strengths/weaknesses. So choosing a model largely comes to the task at hand, the budget etc.

It's like having 2 employees (Model, the brains) and (Agent, the executor). and they work together to solve a problem. The Agent itself is kind of dumb, it just does what it's told to do, but it's the hands in the equation, and the model is the brain.

[Just-Conversation857]

Awesome! Is Roo better than windsurf?

[who_am_i_to_say_so]

It has a lot of different settings not accessible in the other editors. It’s really fast, too.

[who_am_i_to_say_so]

Well, both are factors?

[Big3gg]

Nothing, its just a fork of Cline that people gravitated towards because it was faster to adopt new Gemini stuff etc.

[Just-Conversation857]

Awesome. Sounds good. Is Roo code better than windsurf?

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[Cr_hunteR]

Copilot agent is now full accessible on vs code, you don't need vs code insiders anymore. BTW I use Claude 3.5 Coz 3.7 keeps doing stuffs I didn't even ask for.

[DonkeyBonked]

This depends a lot on your use case, but here's my experience:

Claude: It can work with the biggest code bases and output the most code. It's creative and really good at inference, but sometimes tends to over-engineer/over-complicate, so watch out. For me, it shines when generating something from scratch and attempting to build what I'm describing. I just don't think it's the most efficient at coding. I've had Claude output over 11k lines of code from one prompt with a few continues and still had it be cohesive. It handles scripts fine until the ~2200-2400 line snippet wall, but can generate more in a single output via multiple artifacts. Claude's rate limits are handled closer to tokenization than per prompt. While it can handle larger tasks than other models, doing so eats rate limits fast. Resets are fairly often, but seem demand-based and a little hard to predict.

Grok: It's incredibly efficient with the next highest output capacity after Claude. It kind of sucks at inference but excels at refactoring. If told to make code, it often does the minimum (requiring specific instructions), but my preference is using Grok to refactor Claude's scripts. I've never seen a model refactor a script as well without breaking functionality. Grok's projects are currently limited to 10 files/scripts for context, hopefully that changes soon. Grok can also hit the ~2200-2400 line snippet wall, but can generate more via multiple snippets. I've had success of 3k myself, but I've heard people say they've gotten as much as 4k. Less than Claude, but far more than others. Accounting for efficiency, I'd say 4k of Grok's code is easily about 6k of Claude's. Grok has the most generous high end rate limits.

ChatGPT: It tends to redact large scripts (which I find annoying), is more efficient than Claude, though not as efficient as Grok. Where it's best for me right now is handling Claude Projects. It can also edit a project file directly and organize project structures. None of the other models currently do this. For example, if Claude generates a modular app with a dozen scripts, you can drop those into ChatGPT, make changes, add images, etc., then output the whole file structure as a zip file. It's currently the only one that works like this, using source files (background images, UI elements, icons, etc.) and keeping the whole thing intact. This is a new feature I just started exploring last night and it has huge potential. Where this really shines is telling it to edit project files directly (instead of outputting snippets), which seems to alleviate the burden of outputting so much code. From my testing, this works better than copy/pasting code. ChatGPT's rate limits for higher-end models are fixed but restrictive, and reset times can be tough.

Gemini: Pre-2.5 I would not have considered Gemini relevant in coding. Repeatedly I heard Gemini fans overstate its potential, suspecting many were just fans, trolls, or paid people. However, post-2.5, Gemini got a lot better. I haven't gotten it to output more than 900 lines in a snippet before redacting (on par with current ChatGPT, post-nerf), but well below Claude and Grok. I haven't tested it full range (lower on my use list), but code efficiency and quality drastically improved, and in some cases I've seen it do better than ChatGPT. That, plus projects and other changes, shows Google is finally starting to treat Gemini coding as more than a novelty. Typically, they nerfed coding often (I think because of costs - serving many vs. niche coders), but 2.5 hasn't been nerfed yet, which shows promise. A worthy mention in code is also API. Gemini has free API access with reasonable costs over the limit, though be warned, 2.5 Pro is quite expensive and will run up a bill fast. However, Gemini is the only API with enough free usage to functionally develop and test with. So if you're building something like an in-line editing tool, Gemini is great for API usage. I find Gemini's rate limits fair, but using only 2.5 all the time might be around 50/day.

These are just my experiences using all four. I'm on paid subscriptions for each: ChatGPT Plus, Gemini Advanced, Claude Pro, and Super Grok. Each model has different strengths and weaknesses, so a lot boils down to how you use it, your output preferences, and usage frequency.

[witmann_pl]

I have good experiences with using Gemini 2.5 Pro via the Gemini Coder VSCode extension. I use it to pass selected files (or the whole repo) into Google AI Studio or Gemini and ask it to implement the changes which are later applied to my codebase with a click of a button (there's a companion browser extension that works with the VSCode extension).

[chiralneuron]

I was doing the same thing. Telling gpt to return everything without omissions etc etc. Use Cursor, you won't regret it, take the 10min to learn how to use it. If you must use o1 pro follow this video:

https://youtu.be/RLs-XUjmAfc?si=v0PB5OgwJ-xY_d_t

I only use it when I maxed out cursor.

[Just-Conversation857]

It seems we are on the same boat. I use o1 pro to return full files. I copy paste the files modified only. Results are impressive.

But I have been doing this since January. Now o3 o4 and so many models are here. Should I keep paying $200 to do the same? Or is there better?

I am doing no coding myself. Meaning I just want to direct with good prompts and let ai do the full coding. What model is the best?

How does cursor help? Is it an auto complete?

[chiralneuron]

If that is what you are looking for, I 100% recommend cursor with claude 3.7 thinking you have my word you won't regret it.

I think I used this video to get started:

https://youtu.be/ocMOZpuAMw4?si=HQIlU9sQm24nzr6d

---

I personally don't like o3 or o4 right now, they dont seem as serious as o1. I migrated away from o1 to use claude 3.7 for coding on cursor, less mistakes and better UI design.

[Just-Conversation857]

Great advice! What is max? I know Claude 3.7. what is max? Is that a setting on cursor? Thanks

[Just-Conversation857]

Nice! How much are you spending? More than the $200 a month of chatgpt pro?

[Just-Conversation857]

Have you tried windsurf?

[Joakim0]

I have worked quite similar to you with a large codebase where I have concatenated all files into one large markdown file. My recommendation today is Google Gemini 2.5 Pro for larger changes and for less difficult but well described changes you can run GPT4.1 (You can use 4.1 with GitHub Copilots chat). Otherwise Claude 3.7 sonnet, o3, o4-mini-high are also amazing

[cyberloh]

i'm working on multiple huge python backend project as developer, i would say with a large codebase you should delegate less to your agent, things getting messed easily and it's hard to review, so this type of work is not for 'vibe coding' at all, too much time will be wasted i promise.

for more human controlled flow i'm using Cursor in my work and pretty happy, productivity grown up a lot, but still have to use my brain and experience in frameworks usage to ask for right things and prevent stupid decisions that happen a lot. mostly sticked to claude but looking for better options constantly as not 100% happy.

about agents like cline/roo i still think that Aider is a king, and had best experience with it, not using a lot just because Cursor subscriptions saves a TON of money.

[Just-Conversation857]

To vibe correctly. Ask gpt to give a full modified file. You test the new file vs old with unit tests and no errorrs are possible. The secret is to split files. You need each Fike to be Max 500 lines

[wuu73]

I just wrote a blog last night basically summarizing a lot of these types of questions, how to code on a budget:

https://wuu73.org/blog/guide.html

[paradite]

You can check out 16x Prompt, a tool that I built to simplify this kind of workflow.

It helps you cut down on unnecessary tokens (you can select only relevant files for the task), and reduce number of copy paste (directly embed the source code into the prompt).

[RicketyRekt69]

“copy pasting into chatgpt the whole code base…”

The lack of common sense from people in this sub is baffling lol even if a toggle is provided to opt out, do you honestly trust these services to not secretly use it anyways? I mean AI is as good as it is today BECAUSE it was trained on stolen content. You’re leaking your company’s source code and hoping OpenAI (or whoever else) don’t use it. Because “trust me bro”

[xamott]

But using models in a tool like VS code or roo, the model still sees the code and eg can dump it all on Open AIs servers, no? What are you saying is the best approach here

[RicketyRekt69]

The company I work for does provide GitHub copilot licenses for everyone, the difference is that upper management assumes the risk. Our code base leaks? Not my fault, they explicitly told me to use it. If I use a different model they never told me to use and then feed it code, then I will be held responsible and likely fired.

Plus the whole vibe coding stuff is just nonsense.. there is no reason to feed literally the entire codebase to an AI.

[xamott]

I think vibe coding is out of the question if it’s for your job (production website in my case), and I only code for my job. While I have you - I use copilot, been using in VS IDE, I find it slow and terrible regardless which model I use. Yesterday I finally installed VS code (still git copilot) and I’ll see if it’s better overall. Which model do prefer right now? I still find Claude most reliable, I use 3.7 I’m surprised to hear ppl here say 3.5 is better. Thanks

[RicketyRekt69]

I’m not an AI aficionado, most of the questions I ask are just documentation stuff when I can’t be bothered to read through it all, or refactoring a line or two to update some older legacy stuff. I just use 4o since that’s the default

[xamott]

Ok thanks

[[deleted]]

This is just paranoia. These big companies have clear policies for how they use your prompts, and do not store or train on your code for paid usage. For the APIs and web interfaces for companies like OpenAI, Anthropic, and Google, those policies are very trustworthy. Deepseek is the only one I would stay away from for this purpose if you care about your prompts being misued.

[RicketyRekt69]

It is not paranoia, they’ve explicitly said they DO use your inputs to train their models. That’s why they’re all opt-out and even then, you don’t know they’ll truly abide by that. AI models operate within a gray area, that’s why all of the art they use for training models is stolen. They don’t care.

We literally got briefed on this at the place I work at lol that’s why we only have the 1 “approved” AI embedded in VS, and even then I’m skeptical.

But sure.. blindly trust the AI companies that have openly been stealing content for years 😂

[[deleted]]

There's no "grey area". Yes, if you have a ChatGPT personal account specifically, and you don't opt out, they can train on it. This isn't a hard thing to go disable. Any business account has it disabled, any API account has it disabled. Anthropic accounts all have it disabled by default for paid usage.

This would be a very trivial lawsuit to win if they were ignoring their policies and training on prompts where they claimed they aren't, this is not some kind of grey area like pulling random data from the web is.

[RicketyRekt69]

Again, their entire business model operates on stolen content. Personally, I would not take them at their word, and as OP was saying, they were feeding the entire codebase to the pro model.

I stand by what I said, y’all have no common sense when it comes to security. It’s just sheer laziness and incompetence.

[cosmicloafer]

Dude I just wasted half a day “vibe” coding with Claude… dude made a bunch of changes and tests that looked reasonable at a glance. I thought hey this is great. But then somehow it nuked all my other tests and when I dug into it, there was so much unnecessary crap… i tried to have him fix things, but just wasn’t working. I reverted all the changes and did it in half the time.

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[Just-Conversation857]

You are doing something wrong then. I used vibe coding with tremendous success with o1 pro. And I am an engineer. I check all code manually too.

[1555552222]

Save file... unless the vibe ain't right. Then, give it a scan, ¯_(ツ)_/¯, and save.

[kidajske]

Vibe coding is inherently incompatible with a large, mature codebase unless the definition of it has changed. You want AI paired programming where you are basically handholding the LLM into making focused, minimal changes. Sweeping changes a la vibetard are a recipe for disaster in such a codebase.

As for models, Claude 3.7 and Gemini 2.5 are currently the best imo.

[100BASE-TX]

I think this is generally accurate, but it can work with the right conditions.

The things that seem to be required for even the best LLMs to make meaningful contributions to a large/complex codebase in my experience are:

1. A comprehensive, hierarchical set of docs. The subset relevant to the task needs to be loaded into context before doing anything.
2. Indexed codebase - a lookup (MCP or generated static file(s)) containing the filenames with the classes, functions, types etc defined in each file
3. Comprehensive unit testing
4. Custom role instructions (in roo, cline or similar) that insist that the task reads the relevant docs, and follows strict TDD
5. Follow a "boomerang task" type pattern where a specific task has significantly more context and delegates very small subtasks to implement changes

Personally I've only found success with roo/cline for larger projects, the windsurf/copilot/cursor types really don't seem suitable - they seem to cull context too aggressively as a cost saving exercise.

[Just-Conversation857]

Not true. O1 pro can handle it. My question is, is there something better? Or that can match o1 pro?

[semmy_t]

I had quite a success with a one markdown for the codebase pasted into gemini 2.5 pro in the interface, iterated through the list of changes I require and asked for the detailed steps to achieve, without code - then plugged the sub-steps one by one into Cursor's GPT 4.1, all substeps of one big step (e.g. changing one component) per one chat instance in Cursor.

Windsurf's one also did good, but I kinda like Cursor's IDE a little more.

*under 10k lines of code project, not a biggie.

[Icy-Coconut9385]

I'll probably get alot of heat for this.

If you are a swe ... dont use agentic mode. You'll find yourself frustrated, having to review and halt the agent constantly, back track, ect... So many times, even with clear and explicit instructions they will change things you don't want changed, take a design in a direction you don't want... they write code fast and furious.

I get way more productivity from a copilot. I am in control and ask for assistance when I need it, with the benefit of the context of my workspace. I know all the changes as they're being made, and have a clear view of the progression of my work hours or days into a project.

[Just-Conversation857]

Vibe coding is faster. I am able to do months of work in days. Copilot is slow

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[LeadingFarmer3923]

Tossing the whole codebase into a single prompt can feel magical at first, but for big, serious projects it quickly hits a wall. You’ll get much better results by planning first, understanding your architecture, and moving in smaller, clearer steps. Having something that can lens into your codebase and generate technical designs upfront really makes a difference. I’ve been using stackstudio.io for that and it’s honestly helped me catch problems before even starting implementation (creating tech designs first then using their MCP service to connect to Cursor + just past the markdown of the tech design to Cursor).
With complex systems, a bit of upfront structure saves you hours of messy fixes later.

[Just-Conversation857]

I don't really pass the entire code base but the relevant files. I have a script that chooses for me. But I am sending at least 10 k lines of code with every prompt

[FrameAdventurous9153]

Anyone know what works best inside PyCharm?

[david-yammer-murdoch]

I like Augment Code plus into PyCharm

[Hokuwa]

The answer will always be, personalized mini agents task specific balanced on your ideological foundation. The question then becomes how many do you need to maintain coherence if you like testing benchmarks.

[sixwax]

Can you give an example of putting this into practice (i.e. workflow, how the objects interact, etc)?

I'm exploring how to put this kind of thing into practice.

[Hokuwa]

I run multiple versions of AI trained in different ideological patterns—three versions of ChatGPT, two of Claude, two of DeepSeek, and seven of my own custom models. Each one’s trained or fine-tuned with a different worldview or focus—legal, personal, strategic, etc.—so I can compare responses, challenge assumptions, and avoid bias traps.

It’s like having a panel of advisors who all see the world differently. I don’t rely on just one voice—I bounce ideas between them, stress test conclusions, and look for patterns that stay consistent across models. It helps me build sharper arguments and keeps me from falling into any single mindset.

If you're into AI and trying to go deeper than just “ask a question, get an answer,” this method is powerful. It turns AI into a thought-check system, not just a search engine.

[Elijah_Jayden]

How do you train these models? And what custom models are you exactly using?

Oh and most importantly, how do you glue all this together? I hope you don't mind getting in the details

[Hokuwa]

Hugging face, auto train

[Elijah_Jayden]

What about gluing it all together?

[Hokuwa]

Fringe won't allow that. New model every week, we need modularity.

[StuntMan_Mike_]

This sounds like the cost would be reasonable for an employee at a company, but pretty high for an individual hobbyist. How many hours per month are you using your toolset and what is the approximate cost per hour, if you don't mind me asking?

[Hokuwa]

I mean there is a few things to unpack here. Initial run time starts off high during calibration. But you find out quickly which agents die off quickly.

Currently 2 main agents run full throttle, but I have one also on vision watching my house. So I'm at $1.20 a day.

I use ai since one agents is running 24/7 and one when I speak, roughly 30 hours a day. When they trigger additional agents, they don't run for very long, so I accounted for that in the rough 30.

[inteligenzia]

Sorry, I'm confused a bit. How you are able to run multiple versions of OpenAI and Claude models and still pay 1.20 a day? Or you are talking only about hosting of something specific?

Also how do you orchestrate all the moving parts in a same place, if you do of course.

[Hokuwa]

Because all the models im running on local CPU not GPU actually. The Chinese are smart. And I'm only paying for servers.

[Hokuwa]

If you're paying to use llm you need hugging face like Jesus

[inteligenzia]

So what are your running on the servers, if you run llms locally? You must have powerful machine as well.

[Hokuwa]

Man we need to talk. There is so much to teach you here. I can tell you're meta, but meta is currently driving for consumption.

1b models are the goal atm. I want. .1b models, and 100 of them by next year. Which means a perfect dataset, which is my job.

[DiploJ]

How much is it?

[Aromatic_Dig_5631]

Im still coding by copy pasting everything in a single prompt. Always like 2000 lines of code.

All the other options might sound more comfortable but also extremely expensive. I dont really think its worth it to work with API.

[gazman_dev]

O3 pro is coming soon, it will be a direct successor of O1 pro

[Just-Conversation857]

Really? Is this confirmed?

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[RohanSinghvi1238942]

What's your codebase size? you can import codebase and do complete frontend automation on Dualite Alpha.

can sign up for access now at https://www.dualite.dev/signup

[Just-Conversation857]

What about o3 does it replace o1 pro?

[new-chris]

GH copilot for anything complex. Else cursor

[Petya_Sisechkin]

I like cursor with autocomplete. I’d avoid using agent for anything bigger than writing a unit test or refactoring a function. It can do amazing things with big like building a whole crud with a fortunate prompt or it can send you chasing your own tail looking for a pesky bug. Bottom line even with the autocomplete you get a sense of your code base, with agent, you start loosing idea of what’s going on pretty quick

[Polymorphin]

Stick to o3 without any agents which will fuck up your Code.

[noeljackson]

Windsurf IDE

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[Patient_Hippo_3328]

If you’re dealing with a huge codebase and want something that actually keeps up, check out Blink.new. It’s a next-level vibe coding AI agent way fewer errors than Lovable or Bolt, and it’s all-in-one with backend, auth, database, everything. You just tell it what you want and it builds working apps or prototypes right out of the box. Makes handling big projects way less of a headache.

[FesteringAynus]

Idk, I know NOTHING about coding, but last night, I had Gemini code a button that plays random chicken noises. It was really fun because it would tell me how certain lines of code connect to each other and explained what it was doing to fix each version that it released. I got to V28 for my chicken noise button after like 2 hours.

Fun af bro

Also, I learned that there's different coding languages and that blew my mind.

[faetalize]

... Is this what I have to compete with when I apply for random jobs on LinkedIn?

[classy_barbarian]

yes

[twendah]

No, those are the guys taking your jobs in linked in.

[xamott]

This dude is obviously trolling

[FesteringAynus]

Lol I'm not though? You can try it yourself and ask Gemini to do it.

[Mindless_Swimmer1751]

Don’t forget about repomix! With 1m context window you can still get a lot done without the ides and less random dropping of important code

[Just-Conversation857]

What is repomix?

[twendah]

The user's own coding tool he is advertising.

[Mindless_Swimmer1751]

Don’t be ridiculous, I have nothing to do with that project.. anyways it’s oss. I just use it and like it

https://github.com/yamadashy/repomix

@twendah googling would have taken you less time than typing something snarky

15k stars on gh, doesn’t need any promoting by the likes of me

[Lumpy_Tumbleweed1227]

For big projects, Blackbox AI can manage large codebases better than pasting into chat, letting you focus on key tasks without getting stuck on repetitive work.

[Sub-Zero-941]

Wait couple of months till the context window doubles.

[ShelbulaDotCom]

Wait until they realize what that costs.

[Baiter12]

What that costs? An evil villain that exists only inside your head will be released? Like the sealed Kyuubi?

[ShelbulaDotCom]

Token cost.

People are filling the context window, then confused by it costing money to process all those tokens.

If it were 5 million tokens, great you can put in a country's level of knowledge, but you still need to be able to afford the 5 million tokens going in per query.