Hi Guys!!! As you know I wasn't good for well, a week and Now.....
Let's Dive In!!!
I never consciously decided which AI gets which job. Somehow...
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Okay, now Iβm genuinely curious π
I clearly have a whole AI hierarchy that I never consciously created.
Do you have one too?
Which AI gets the serious work, which one gets the dumb little questions, and which one do you trust for one oddly specific thing for absolutely no logical reason? π
I just bounce around different AI models if anything. I don't really have a specific one that is task on a specific thing. It's more of using it as a good search tool more than writing code since it's very useful of finding information on what I need.
I tend not to use it as much of relying on the AI to do coding because it removes my ability to think critically whenever I am solving a problem. A good methodology is not having to do too much and too little of anything.
Yeah yeah cool. Neither do we since you know start of campus placement season, we don't use AI for coding but you know we do it for hacks as students, cause there the goal is to be generally good.
But thanks for the detailed write-up. But Sir, I'd like to know where do you get this great gifs and images from? Just Curiousπ
No problem! For the images/Gifs, I just search them on the internet (Google specifically). Nothing really fancy though :)
I think you really missed one big LLM i.e the real, natural human brainπ
Unfortunately, the folks who are heavily using or leveraging AI tools are outsourcing their thinking and some even forget they are alive π€£
TBH I'm no longer surprised from this
Recently saw someone online explaining that they created an ai in their brain so when they aren't in situation to open an ai platform, they ask to ai in brain, what to do? And I'm like bro? Did you just learn to think?π€£
I relate to this so much. I definitely have a βserious workβ AI and a βjust vibingβ AI without ever consciously deciding to set it up that way.
Claude Opus is usually my serious work model, especially when Iβm planning something complicated, debugging a weird issue, or working on something where I really care about the reasoning and details. Then I use Antigravity with Gemini 3.8 Flash for smaller changes, experiments, quick ideas, or when Iβm basically just poking at something to see what happens.
I also use Codex with GPT-5.6 Sol for some oddly specific things, especially documentation and little repetitive fixes that come up often. Codex has the best memory for that kind of stuff in my experience, so if I run into the same issue again, I can usually just ask it to fix it and it already knows exactly what I mean. That makes it ridiculously useful for those recurring tasks.
And I think you nailed the reason why this happens. Itβs not always about which model is technically βbest.β You start learning which one you trust for certain kinds of work, which one is fast enough, which one has enough usage available, and honestly which one annoys you the least for a particular task.
At some point you realize youβve accidentally become your own AI router.
Gemini into antigravity IDE or the windows app... There is a difference where the IDE of course feel more like a complete final product over a web app transfert to a Windows app for Exemple...The IDE is very good... And of course the pro plan of Gemini is one of the best for tokens... I use also Ollama deepseek 4.1 flash on a 100$ plan give you for 300$ credits so far I didn't even using half... Yertarday... Ollama or DS was getting a higher price per tokens usage.. They have reset my monthly usage back from 0 to 300 for no additional cost... For this use it's a win win.. Using it into Hermes desktop... Is a good duoo for casual and heavy work!!
Yeah, but can't you use the NVIDIA NIM API and run that free claude code server locally? Or is it just good enough for prototyping and not in production? Cause my friends use these models like this way only.
Why do you want to get stock into a tool that an Agent doesnt understand or even know where he ''life'' on ....
remember something a lot of these tools came from CLI -p or sandbox .... using native tools for native agent are much more controllable .... Ive been using for exemple a lot of new desktop app where the agents was finaly told me like .. I am in Hermes CLI .. or codex .. or claude code ... remember that ... and this is always something I build my tools on that even Claude Code desktop ... didnt really know about ... and cannot control the application you are using ...
Ask Claude Code in desktop app ... ok .. create me a new project .. call it Project 2 ....
He will never been able to do it ..
If the native agents doesnt have an MCP of there own application ... its impossible for them to control it .. so they are stock inside there CLI ....
Same as if you use NIM on Claude code CLI ... and you create / command .... ask like Nemetron ... use / this / command ... he will have to figured out where he life in .... what tools he have access to and how to use them ...
What I find interesting is that this eventually becomes less about model preference and more about risk-based routing. A quick formatting task and a production-facing architectural change shouldn't need the same level of reasoning, verification, or tool access. The useful question may be βwhat is the cost of being wrong here?β rather than βwhich model is smartest?β That could lead to a more deliberate routing system where low-risk tasks get fast, inexpensive models, while high-impact tasks automatically trigger stronger reasoning, additional verification, or human review. The hierarchy people develop informally today could eventually become an explicit policy layer around their AI workflows.
I'm a creature of habit, I Started using Antigravity And Now With Gemini 3.8 it's Just Great. Sometimes I Use Opus, almost Never. On The Chat I use gemini web And ChatGPT web, I tried To Change All That Flow a lot of Times But I Always Come Back π
This is so real π
I definitely have a "don't waste Claude credits on this" brain now. Half the time I'm not even picking the smartest model, I'm picking the one that's the least effort for that task.
Somehow they all ended up with different jobs without me ever deciding it.
Gemini for throwaway (the web interface is great for picking up old questions), Qwen 3.8 flash (qoder efficient) for bulk work, Qwen 3.8 max for serious thinking. Gemini pro for 'double check qwen's work', Claude Opus for 'I seriously need to make sure they didnt screw up'. Though most of the time, I actually trust Qwen more than I trust Opus, idk, for me even 3.8 Flash thinks 'smarter' for me, it pre-optimizes further than Opus and just sticks to better design principles imo.
Glad you're back bro! good post and good GIF!
Thanks! That's from friends btw but you wouldn't know thatπ.
HA HA. talk about post, not unnecessary stuff! But that's good cause we all default back to chatgpt just cause its fast.
Well for exam notes. Not for hackathon stuff, who uses antigravity there huh?π
What do you use as the check when Gemini gives a calculation answer you no longer double-check?
Actually you always have answer keys to PYQs, so ....
GIF xD
Nice write-up Dhruv :D
Thanks di!π
The split between "serious work" and "vibing" AI use is something I see in my own workflow. I use a coding agent for structured tasks and a conversational agent for brainstorming, and the two rarely overlap. The interesting part is that the "vibing" use case often leads to the most creative insights, even though it feels less productive. How do you think about evaluating the quality of unstructured AI interactions?
Great topic and text