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, I just ended up with a ranking in my head. It just happened — one small decision at a time, until one day you noticed you have an entire unconscious hierarchy, and you can't fully explain how it got built.
Here's mine, laid bare.
The IDE has its own pecking order
I use Antigravity as my AI IDE now — GitHub Copilot went pay-to-use, so that door closed. Inside Antigravity, I don't use one model. I use two, and which one shows up depends on what's actually at stake.
Claude Opus gets the hard stuff: planning, and the UI bugs that don't have an obvious cause. Gemini 3.1 Pro gets everything else — the routine work, the smaller changes.
Here's the part I only admitted to myself recently: Gemini 3.1 Pro hallucinates more than Opus does in that context. I know this. I use it anyway, for most of my day-to-day work, partly because it has more usage headroom than Claude does inside Antigravity. So the model doing the bulk of my actual coding isn't the one I trust most — it's the one I trust enough, running more often because I can afford to run it more often. I hadn't said that sentence out loud until I wrote it just now.
The chatbots are a completely separate hierarchy
Outside the IDE, on the plain chatbot websites, the routing rules are different again:
- ChatGPT is my "is this even possible" AI. Syntax checks, rubber-duck debugging, quick throwaway questions. Free tier, small model, fast answer — I'm not trying to get something profound out of it, I just want an answer in the next ten seconds.
- Claude is my quick-draft AI — names, ideas, urgent doc edits when something needs to sound right in the next two minutes.
- Gemini gets a strangely specific and non-negotiable job: PYQ (previous year question) and calculation-heavy problems. I have never once seen it give me a wrong answer there. Not "usually right" — never wrong, in that specific lane. Ask it something about code or general facts and it can absolutely be off. Ask it to trace through a calculation and I don't double check anymore.
That's not "I like Gemini." That's a very narrow, very specific trust — earned in one lane, and it doesn't transfer to any other lane.
The moment that gave the whole system away
I only really noticed I had a system when it broke in a small, dumb way.
I asked Antigravity's agent to look at the final draft of a post I was about to publish — just check if everything was aligned, bolds in the right place, tags correct. A one-glance job. Instead, the agent opened a browser, took a screenshot, entered the URL, took another screenshot, moved the cursor, tried to click something, took a third screenshot, and kept going — burning a chain of actions and tokens on a task that needed about two seconds of looking at a page.
I stopped the execution mid-loop. Then I did what I always do for that exact task: opened ChatGPT and asked it to just look at the draft. Done in one reply.
That's when it clicked that my routing isn't really about "which AI is smartest." It's about matching the shape of the tool to the shape of the task. An agent that can act in the world was simply overkill for something that needed a two-second glance. More capability didn't help. It just made the mistake more expensive.
It's not just work, either
The hierarchy follows you into conversations that have nothing to do with code.
Cricket is huge where I'm from, and there's a test I didn't design on purpose, it just kept happening. If I open a chat and say something as lazy as "man, [team] isn't winning today" — zero context, zero setup — Gemini goes and figures out who's actually playing, pulls their current form, checks the squad, and gives me an actual case for why they can or can't pull it off. If the match is live, it grabs the live score in the same breath. ChatGPT, given the exact same one-line prompt, asks me what the score is.
Same lazy prompt, two completely different experiences. One feels like talking to someone who was already watching the match. The other feels like I have to catch it up before we can even start.
I don't think that means Gemini is smarter. It just needs less hand-holding in that particular situation, and apparently that's enough to make me reach for it more.
The funny part is I never consciously chose any of these roles. I just kept coming back to the tool that annoyed me the least for each kind of conversation.
What this actually says, if I'm honest
I never wrote any of these rules down. I just kept using whichever tool annoyed me the least for a particular job, until those choices turned into a system.
So — genuinely asking, not rhetorically:
What's your hierarchy for different AI usecases? Which AI gets your real work, which one gets your throwaway questions, and was there a specific moment that revealed the system to you the way the screenshot loop revealed mine?
Top comments (61)
Okay, now I’m genuinely curious 😂
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? 👀
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 Curious😅
No problem! For the images/Gifs, I just search them on the internet (Google specifically). Nothing really fancy though :)
I have noticed a pattern for my workflow. It is roughly:
Claud CLI/code until I run out of credits, because it's the only one im paying for. It has historically been able to crunch some tough problems for me as well as turn data into nice graphs and charts right in the chat for me, including full static diagrams with an interactive/click able overlays with fairly good precision.
Github copilot CLI is nearly neck and neck with claude. When claude becomes frustrating, I have found copilot CLI picks on the slack in an unquestioning, no nonsense way.
Gemini excellent tremendously at video and image generation for supporting documents.
Ollama: Child has taken over my personal computer. Protect fancy requests at all costs. 🤣✨️🦚. Ollama is also great for locally structure workflows that are repetitive like testing. I have used it extensively and am extremely thankful for the open source models for learning.
I’m a much simpler guy than that; I don’t use an IDE by default—I do my programming using CLI-based tools. Since I have company subscriptions to ChatGPT and Copilot, I use one of those. If I really need an editor, I use Vim. For the corporate Confluence, there’s a tool called Roboto that I use to generate key company documents. I also subscribe to Gemini, but mostly just for the Google storage space; I do use it to make 10-second videos occasionally—maybe one or two a week. Of course, lately I haven’t felt the urge to program as a hobby—why burn energy on AI? Maybe in the winter, I’ll pick up a long-cherished project again.
I think you really missed one big LLM i.e the real, natural human brain😁
Unfortunately, the folks who are heavily using or leveraging AI tools are outsourcing their thinking and some even forget they are alive 🤣
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?🤣
I relate to this so much. I definitely have a “serious work” AI and a “just vibing” AI without ever consciously deciding to set it up that way.
Claude Opus is usually my serious work model, especially when I’m 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 I’m 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. It’s not always about which model is technically “best.” 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 you’ve accidentally become your own AI router.
Great! Its just that I'm a student and I have no premium subscription so I don't get to try a lot of stuff but I use antigravity cause its free for students😅
I have Antigravity for students too! I have to pay for Claude and Codex though if I want to use those.
Love this post. My hierarchy is pretty simple: Claude for serious work and personal projects, Gemini for playing around, and a rotating cast of other AIs for experiments that never quite graduate to real work.
The trust thing you described is exactly it. It's not about which one is best overall, it's which one I'd let near something that actually matters.
Currently trying antigravity cli. Not for serious work but for boring repetitive tasks! 😄
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 stuck in a tool that an agent does not understand or even know where it lives?
Remember that a lot of these tools came from CLI or sandboxes; using native tools for native agents is much more controllable.
I have been using, for example, a lot of new desktop apps where the agents finally told me, "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 did not really know about and cannot control the application you are using. Ask Claude Code in a desktop app,
"OK, create me a new project, call it Project 2." It will never be able to do it. If the native agents do not have an MCP of their own application, it is impossible for them to control it, so they are stuck inside their CLI. It is the same as if you use NIM on Claude Code CLI and you create a command; ask Nemotron to use this command, and it will have to figure out where it lives, what tools it has access to, and how to use them.
Sir, 1st I don't understand what english you've written here.
2nd: using NIM API, you get almost all models including the deepseek and Ollamas and Qwen too. And all claude skills!
The line that hit me: "I just kept using whichever tool annoyed me the least for a particular job, until those choices turned into a system."
I'm a beginner — I started learning Python about two weeks ago and I've been writing tutorials about it. I don't have an Antigravity setup or a model pecking order. But I do have exactly one rule, and I didn't realize it was a rule until I read this.
I use ChatGPT for syntax and quick "what does this error mean" checks. Fast, throwaway, no attachment.
And I use it for absolutely nothing else. Not for learning concepts. Not for understanding why code works. Because the one time I tried to learn a Python topic entirely through ChatGPT, I realized a week later that I couldn't explain any of it back. I'd read good answers and retained nothing.
So now I only use AI after I've tried to figure it out myself. And if I'm learning a new concept, I read documentation first and ask AI second.
It's not a hierarchy of models. It's a hierarchy of moments. AI is the second opinion, never the first.
That's not a smart system. It's just the thing I landed on because everything else annoyed me more. Which is exactly what you're describing.
Great post. Made me realize I do have a system — I just never named it.
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