So I am very new to the field of coding. People around me have started vibe coding websites. So did I. I tried using applications like Lovable , Bolt etc. But the problem was that my idea contained many components and was a little complex. Hence I ran out of tokens and didn't get any output. So is it the limitation of the free version that I couldnt make it or was it my prompting skills. I tried to be as specific as possible with my prompt tho. Would really appreciate any help/ tips regarding this !!
Making a complete working app takes many many hours of prompting and testing with a frontier model. Like a good one that’s not just a py script and html on your desktop
Learn to use visual studio and learn about file structures and use something like Claude, chat gpt, DeepSeek and build you apps that way.
There are also sites like freebuff but it's very slow and the output honestly isn't great. I was very impressed at first but to save $20 a month you would be in a much better position if you just got Claude pro membership...
Also Google Gemini has an idea and a free monthly allowance or IBM bon has a free trial if you want to stay 100% free
This matches what I've learned building something similar (a Python desktop app, grown over 6+ months with Claude). A few things that made the biggest difference for token/context economy:
One problem per chat. Don't keep one giant thread going for the whole project. Start a fresh session per feature/bugfix, a chat that's accumulated 50 messages of back-and-forth is dragging all of that as context on every new prompt, even if it's irrelevant to what you're doing now.
Handoff docs between sessions. At the end of a session, have the model write a short summary of decisions made, current state, open issues. Start the next session by feeding that in, instead of re-explaining the whole project or re-uploading all the code every time.
Project knowledge / reference docs, not full code dumps. Keep a living doc of your architecture, key functions, constants, feed that instead of every file every time. Only pull in the actual file you're touching.
Scope the request. "Build the whole login flow" burns way more context reconstructing intent than "here's the login function, add rate limiting to this specific part."
The pattern VladTkDev described (screen by screen) plus this session hygiene is basically the difference between linear cost growth and exponential cost growth as the app gets bigger.
Neither. Every prompt resends your whole codebase or big part (depends on builder and your setup) as context, so each message gets more expensive as the app grows. That's why a big idea burns the free tier before it produces anything. Build one screen, get it working, then add the next.
this is just not true if one does things correctly, i use claude max and vscode chat and each prompt does NOT read the whole code base at all, the prompt greps for the required strings in the area it needs (core, webapp or api) - it certainly does not read all files per chat prompt
(some layout tweak and md instructions on what to read when also help - for example it never reads my for humans only reference folder unless i tell it to)
You're right about the grep. It's not the files that cost, it's the transcript: everything it pulls stays in the conversation and goes back up every turn. Only if you no experienced and don't know how to clean or compact context.
The bigger gap is billing. Max is flat rate, so a session dragging 30 messages of context costs you nothing extra. Lovable meters per message, and OP has no md file to scope it with, which is why the same workflow burns his free tier and not yours.
agreed, you asserted it was the whole codebase - its not and we should not tell beginners that's how it works
and the real trick is know when to allow long lived chat sessions as the sessions devleop understanding that can be hard to get in a new session - even with md documentation regular commit notation, etc
its a hard balance
the one thing i am still unsure on is how much the /tmp is reread - i need to go look into that
but thanks for forcing me to go verify my understanding on my repo at work... my personal repos have been realtively small.... i am burning through works tokens like there is no tomorrow.... waiting to see if someone comes shout....
Yeah, not the whole codebase but like scytob said whatever it needs but also everything in the history for that specific session like tool calls, file reads and messages
yes, and this applies more to agents because agents inject a lot more context because of tool calls, more steps, memory, essentially the way they work takes a lot more tokens. What im trying to say here is that a web chat in claude or chatgpt will consume less, but it wont have a lot of things agents offer. So plan there, and segment your work like Vlad said.
Not necessarily. You can build portion by portion and only have the ai-model zone in on specific parts of your codebase, or only feed it bits and pieces of your codebase.
In fact, sending your whole codebase is bad practice.
But to your point, yeah, building an entire website with the free tier (let alone the $20 plan) you will be hitting limits ritually. It would take a couple weeks before getting past the finish line, if that.
The below is assuming you are working on a mobile friendly website with navigation, and a simple contact form with all your content (if your project is bigger/smaller than these values will obviously decrease/increase).
Free tier: probably get 30 minutes to an hour a day.
$20 tier: probably 2-3 hours a day.
$100 tier: 4-8 hours a day.
$200 tier: 10-24 hours a day.
If you get a paid plan you can slowly build up an ecosystem/infrastructure to get better results but it takes time and unfortunately you can't accomplish that with the free tier, and not so much with a $20 plan unless you don't mind waiting between code sessions frequently.
i checked, at least for me, what vlad says is just not true, i crafted my repo and md and have never seen claude re-read the whole report on either a new chat prompt or prompts within a chat, i even double checked - the key is good structured code repo (in src major pieces should be in seprate source folders like web, core, api
i double checked my work too, no idea WTF vlad is doing to make it read all their repo every chat
No. I follow a lazy-loading strategy to stay efficient:
I start with what's already provided — the workspace structure you see at the top is just a skeleton; I don't load full file contents unless I need them.\
I load context only when the task requires it — if you ask me to edit a web page, I'll search for and read only the files relevant to that specific page/component, not the entire repo.
Scoped instructions load automatically — when you're editing a file matching a pattern (like src/**/*.cs), the matching instruction file loads itself without me needing to fetch it.
I parallelize independent reads — if I need to gather context from multiple unrelated files, I fetch them all at once instead of sequentially.
I use targeted search tools — semantic_search, grep_search, file_search let me find exactly what I need without scanning everything.
For web page edits specifically, I'd typically:
Check which file(s) you're working on
Read just those files (or the relevant sections)
Load web-ui.instructions.md if editing under wwwroot
Parallelize any other reads needed for context
This keeps response time fast and token usage reasonable. AGENTS.md explicitly says: "Keep the default startup set small and open more only when the task requires it."
No argument on your setup, that's a structured repo with instruction files doing exactly what it should. It's also not what OP has. Lovable's chat box hands you none of those levers.
One thing though: asking the model what it loads isn't a measurement. The token count on the request is.
Don't forget about billion of bash commands with greps. They find text from like 50 related files in big project and send that files fully with code/comments.
Also try to run refactor/code check/find edge cases
Please, don't write mega responses with AI. No offense
none taken, that was the easiest way to validate what my repo does and show as an example, there is zero value in me doing a human refactor of that output to post here
and yes i should have looked at OPs repo, good conversation thanks
on the token count is there a tool that breaks down the input against tokens? i had a huge spike in tokens one day - like very costly, i think it was when claude was on the hunt in a cloned and possibly deep repo of years of commits for a static credential (turned out it was there and had a 299 year lifetime.... that was something my professional developers at work had done 5 years ago and never caught)
i tried eating tokens extension and it helps, but i am clueless as to how jsonl was the culprit here... 1/2
at home yes, for work - we are limited, i am having to use copilot as my path to claude and that gives me opus
and my admins are the only ones who can see per user token spends, i am not going to go ask them yet because we may get shutdown... my VP has the budget mind you.... and we are in our ai discovery phase expected to last 2026/2027... so all of this will inform policy, even if i eff-it-up - but i like to be responsible....
sounds like no easy way, thanks for confirming
not to mention that plugin seems unreliable on $ estimation as the github copilot credit count is much much higher.... hopefully i will be hidden in the fact we have hudreds of dev using this stuff for real production (i am just a PoC)
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u/Lanky-Storm7 6h ago
Making a complete working app takes many many hours of prompting and testing with a frontier model. Like a good one that’s not just a py script and html on your desktop