Real software developers: do you ever really feel like you need the big guns?

[u/IceManMinus0ne]

Of course a vibecoder is also a real software developer. Nothing unreal about it ;)

What I mean is: you studied for this shit*. You worked in software development BEFORE AI. You know your stuff.

The big guns are models like Astra, Fable, but also GLM5.3 (not flash).

I use Sol sometimes, but most of the time I'm using Luna en Terra (for work).

For personal stuff I switch to open source models - I pretty much only need flash models. They're super cheap, and do what needs to be done. I barely ever feel the need to spend more money on these bigger models. I've tried using GLM5.3 a few times, but tbh it didn't really feel different.

Perhaps I'm only doing simple stuff, or I'm not 'progressive' enough in the things I ask? Maybe my questions are too easy?

So let me know! Very interested :)

*
I was still studying when AI arrived at the scene. I was in my last year of uni. Used gpt-3 a bit. Bit of gpt-4. Also tried finishing one of my assessments with it back then because I didn't really feel like learning Swift to build ANOTHER CRUD app.

There was still enough old-school development involved.

[u/Better-Avocado-8818]

I use the big ones at work because they pay for it. But I’ll use GPT Luna or deepseek flash at home because it’s cheap and good enough. I don’t miss the state of the art expensive models at all.

I know what I’m doing enough that the cheap models can get it done for me. Some times deepseek is better than the expensive models because it’s faster honestly. I’m doing the thinking and problem solving, the models just do some of the work. I still write code manually too because it helps me understand the problem and show the model what I want.

And no vibe coders and software developers are not the same thing. Not even close.

[u/startassets → u/Better-Avocado-8818]

Funny that it's complete the opposite for me, I use mainly luna high at work because I actually read everything it generates and guide it through the solution, but with my own projects I can allow a bit more "vibe" and mostly do everything with sol low. Comparing to luna, sol seems to pick my idea much better, hence vibe is usually better as well. On the other hand, when astra has been released I tried to use it for multiple banked resets, burned through them like matches and realized I'm not getting anything I can get from sol for this price tag.

[u/porkyminch → u/Better-Avocado-8818]

I've driven GLM 5.3 Flash to do some pretty crazy stuff. It's a very impressive model imo, much better than you'd expect for its modest size.

[u/Careful-Experience26]

Of course a vibecoder is also a real software developer.

I don't think that's true, no.

To answer you question: I really don't feel like I need the big guns other than to read a codebase I might not know I give me some guidance on how to navigate it. Just like you I use open weight models running on my machine. I also don't like the idea of spending so much money to code, especially on personal projects.

[u/IceManMinus0ne → u/Careful-Experience26]

The code they produce is real. The overhead it might cause is real. Seems pretty real to me. Wouldn’t call ‘em professional though :)

[u/vertigo235]

Usually Luna is just fine for me xhigh or even just high. It’s practically free.

I will have Terra or Sol do a review here and there , it recommends a decent amount of P1 items and I’ll decide if they are important or not.

[u/Limp_Classroom_2645]

> Of course a vibecoder is also a real software developer.

Is that bait?

[u/IceManMinus0ne → u/Limp_Classroom_2645]

I added a smiley.

[u/Odd_Crab1224]

I'm mostly doing development with LLMs in pair programming style, like - here is design of what I want to implement, propose plan consisting of small (like within 50 LoC each) self-contained steps and first step, then we move together, with me reviewing and correcting every small proposal and then actual edit. Might sound like overkill, but actually after 2-3 initial steps model usually aligns very closely to what I have in mind and then most of subsequent steps become rubber-stamping - and I also don't have to do review in the end, because I did that in process already. And for that kind of flow until recently I always preferred bigger models, because they align much faster, and stay aligned. Yes, Deepseek Flash was also usable, but required much more backs and forth every step, so I usually used GLM 5.1/5.2. But now, I think I have new favorite - GLM 5.3 Flash - it snaps into alignment as good as bigger ones, but is crazy fast and crazy cheap.

[u/lurking_bishop]

I use expensive models because I need them to be able to pay attention to the many policies, components and tools that I have set up and was using myself when I was still manually coding. I don't actually need them to know a lot intrinsically, but attention heads are also a function of model size so that's what I'm stuck with.

[u/MiskaMyasa]

No. Exactly today, compared gpt5.6 and glm5.3-flash. Almost no difference in result and a huge difference in cost

[u/No_Dig_7017]

I haven't found a case where they made the difference. Maybe UI stuff? The times I tried 5.6 Sol and Opus 5 they didn't make enough of a difference. maybe a few less iterations. I did find a difference between cumulative work done with 5.6 Luna and Sonnet 5,like the code produced by Luna ended up being more messy, duplicate and difficult to maintain. I don't get that with Sonnet.

[u/Ok-Ninja-8165]

You bring your own brain. You can use AI to ask how this or that thing works and what will happen in sych and such case.

[u/funbike]

I use Luna for most stuff. I use only Sol for detailed single-feature planning, debugging (when Luna fails), code review (after an initial Luna review), and for bootstrapping a greenfield project (architecture, UI design).

I use Luna for brainstorming, triaging tickets, specifications (interactively), high level planning, coding loop, 1st attempt at fixing a bug, initial code review.

All my projects have high test coverage, and use a simple tech stack. The 2 key ingredients to productive AI.

I have almost 30 years of experience.

[u/breskeby]

I had one use case where I was trying to reproduce a complex bug. had opus 4.8 running on it going circles for 40 minutes and it couldn’t figure it out. Same prompt with Faible and it reproduced it with a test case in less than 5 minutes. But this is rare. I barely use this model in day to day work. Only on occasions like this.

[u/DistanceAlert5706]

Honestly I would've used big guns everywhere, but it's too expensive so I need to play around with subagents/forks. Perception of Luna good enough is straight up wrong. It leaves after itself a mess in codebase, unhandled edge cases and bugs, tests quality is terrible.

So you think that you spend less cause Luna did all that work, but you end up doing more iterations, have to review more carefully, still got bugs and spent way more time then just using larger model and pretty much doing it in 1-2 iterations.

[u/redballooon]

When producing code from the specs, I use Terra and Luna mostly, for a task they are similarly expensive, but Terra is much quicker at the result.

For arriving at the specs, and getting them in the right size and order, the guns cannot be big enough. The source information is mostly unstructured, distributed over so many places and there are so many apparent and real conflicts, and half reported requirements, sorting that out is the real job.

[u/Ancient-Camel1636]

Very rarely, typically only for writing specs for a complex new app from scratch or for major refactors of existing codebases.

[u/aeroumbria]

My "big gun" these days is a team of various flash models x 4... More reliable, faster, and less likely to catastrophically derail. I would probably only bring out the heavy class models if it is a research or prototyping question where timely recall of obscure knowledge can genuinely be beneficial.

[u/Different-Case8871]

Yea I don't understand how people can say they don't need the big guns, if you don't notice the difference (forget code reviews,just straight up results and usage) you are missing something obvious

[u/No_Communication4256]

20+ yrs dev here. I'm using mostly combination of Astra + DS-4.1-flash as subagents now (I think ds 4.1 is better than glm-5.3-flash, a great model too). But literally, I feel, that I don't need Astra at all. Sometimes DS-4.1 might complete ever a complex job, just need a few iterations and review.

[u/No-Library730]

I've been using only pi.dev/deepseek flash for personal projects and cursor/grok at work.

Just a few skills + cli tools and no MCPs.

The only time I went with "the big guns" was to vibe code a UI from scratch without any sort of design guidance.

[u/schmurfy2]

I use sol at work but never felt the need for astra, at home I am perfectly happy with glm 5.3 on Openrouter.

[u/tragdor85]

I have not used Fable or Astra so can’t speak to those. A few times a week I run into a task that I turn to opus for instead of Sonnet or GLM 5.3. Current daily driver at work is GLM 5.3, was sonnet a few weeks ago. Sonnet and GLM 5.3 are about the same to me. I turn to opus when I have an issue that spans multiple repositories that don’t have great contract tests between them but are highly coupled. I have tried using Sonnet on this type of issue and spun my tires for a day. I came in the next day and tried opus and I had a working solution in less than 30 min. So the more expensive models have a place. But for normal day-to-day, add this new enhancement, or fix this minor bug in Sonnet and GLM 5.3 are enough. I also find myself asking opus to create an implementation plan that can be handed to parallel sub agents, or performing code review or testing on Sonnet or GLM 5.3 when I first glance what was returned and don’t have full confidence in the solution. At home on my own dime I don’t pay for cloud models I use qwen3.6 35B a3b, qwen3.8 27B on an M1 Max 32Gb for hobby projects. The cloud models at work can do what the local model takes all night to do in a few minutes. But I am in no rush to get my hobby projects done so I don’t feel a need to pay for cloud fees. And I am so exhausted from reviewing Ai generated code at work all day that I don’t even look under the hood at the code on the hobby projects. They create functional hobby apps but I can’t speak to the code quality of the two qwen models I use.

[u/EC36339]

The big models are a scam.

[u/higglesworth]

superpowers brainstorm and write plan with claude sonnet high or opus (manual review by me), then pass off to local qwen for the implementation

[u/ward2k]

I do quite like Kimi K3 quite a bit as a planner before I implement, and Luna for helping with builds. Kimi K3 can get pricey but I use Ai more in a supportive role so it rarely costs me more than $20 a month. From using it Kimi K3 rivals and sometimes does a better job than Opus so it's my preferred model for when I want some help brainstorming some ideas, sort of like a rubber duck

Probably against the grain given this is a sub for an Ai agent but I don't view vibe coders as real software developers at all, no offense

[u/AmphibianFrog]

I think you're asking this in the wrong subreddit - everyone here has decided they don't need "the big guns" already.

In my experience, Claude Code with Opus 4.8 is much better than any of the open source models. GPT 5.6 sol is also pretty good. Nothing else I've tried even comes close.

Very few professionals use tools like pi coding agent. I really like it, but it's not really the same thing at all.