afterbuild/ops
ERR-693/stack trace
ERR-693
Lovable burning through credits with no progress? How to stop the spiral

Lovable burning through credits with no progress? How to stop the spiral

Last updated 15 April 2026 · 9 min read · By Hyder Shah
Direct answer

If your Lovable project is spending credits to fix something it just told you it fixed, you’re in the regression loop. Other users in your seat have reported multi-million-token auth spirals and 400 credits burned in two weeks on a Pro plan. The fix isn’t better prompts — it’s stopping your AI, locking your architecture, and patching by hand. Below: the 6-step escape.

Quick fix for Lovable burning through credits with no

Start here

Stop editing with the AI. Right now.

Every additional prompt in a regression loop makes things worse. Close the Lovable editor tab. You’re in the slot-machine pattern: each spin feels like it might be the fix, and it won’t.

Deeper fixes when the quick fix fails

  1. 02

    Export to GitHub and pin the last working commit

    In Lovable, use Project → GitHub → Export. Clone locally. Identify the most recent commit where the app actually worked (usually 5-20 commits back). Tag it last-known-good.

  2. 03

    Diff the breakage

    Run git diff last-known-good HEAD. You will usually see the AI re-wrote a file 3+ times, each time undoing prior fixes. This is your evidence for what to keep vs. revert.

  3. 04

    Hand-patch the one actual bug

    Ignore everything the AI added after the first breakage. Open the single file with the original bug, fix it by hand (or in Cursor/VSCode), commit.

  4. 05

    Add a regression test

    The reason the loop existed is there was no test catching the regression. Add one with Vitest or Playwright. If the AI breaks it again later, CI will fail loudly instead of charging you credits.

  5. 06

    Decide: keep using Lovable, or move to Cursor

    Lovable is fine for greenfield UI. Once you have paying users, switch to Cursor/Claude Code against the GitHub repo. You pay a flat $20-40/month, not per-token.

Why AI-built apps hit Lovable burning through credits with no

Lovable charges you per AI action. Every regeneration you trigger costs credits whether it works or not. When the Lovable agent on your project breaks something else while fixing the thing you asked for, each loop you run costs you money and gives you net-zero progress.

Your root cause is context loss. By the time your Lovable agent has edited 6-7 files in your project, it has forgotten the architectural decisions it made back in file 2. It starts contradicting its own patterns, and the contradictions in your codebase compound.

Bolt.new ate tokens like a parking meter eats coins.
Medium reviewer — Vibe Coding in 2026[source]

Diagnose Lovable burning through credits with no by failure mode

Match your pattern to one of these to know where to stop first.

SymptomWhat's actually happeningFirst fix
Same bug keeps returning after every 'fix'Regression loop — AI is forgetting prior editsExport to GitHub, stop AI edits
One prompt costs 500k+ tokensContext window filling with noiseTrim files, reduce attachments
App was working, now 4 things are brokenCascade regression across filesRoll back to last good commit
Credits gone, app still half-builtScope creep + stacked promptsFreeze feature scope, ship v1

Related errors we fix

Still stuck with Lovable burning through credits with no?

Emergency triage · $299 · 48h turnaround
We restore service and write the root-cause report.

If you’ve burned more than 100 credits on one feature, the answer isn’t more prompts.

  • You've spent $100+ on one bug
  • The same error keeps coming back
  • You want off the credit meter
start the triage →

Lovable burning through credits with no questions

How do I stop Lovable from burning credits?+
The fastest answer is: stop prompting. Every prompt while the app is broken makes it worse. Export to GitHub, roll back to the last commit that worked, and patch the bug by hand. Credits only drain while you're using the AI — the moment you switch to Cursor or VSCode, the meter stops.
Why does every Lovable action cost so many credits?+
Lovable sends your entire project context to Claude or GPT on every prompt. Once your project has >2,000 lines of code, that's hundreds of thousands of tokens per action. The AI also self-corrects mid-action — which means extra round-trips you're billed for. Larger projects cost exponentially more per prompt.
Is there a way to use Lovable without the credit spiral?+
Yes: treat Lovable as a prototype tool, not a production tool. Use it for the first 2,000 lines to get scaffolding and UI. Export to GitHub. Do all further work in Cursor or Claude Code, which have flat pricing. We do this transition as a fixed-price service.
How much are Lovable credits really costing me?+
Users on Trustpilot report 400 credits (≈$100) burned in two weeks on a Pro plan while making no progress. Others report multi-million-token auth spirals (≈$60-100 of raw API cost) trying to fix a single auth bug. If you're past 100 credits on one feature, you're in the spiral — stop and hand-patch.
Can you help me get off Lovable and stop the credit burn?+
Yes. Our migration service is $2,999 fixed price: we export your Lovable project to GitHub, set up Cursor, remove the credit billing, add tests so regressions can't come back, and deploy to Vercel. Turnaround is 7 days. Free 30-minute diagnostic first.
Does the Lovable free tier cause the same spiral?+
Worse, actually. The free tier runs out faster per action and forces you to upgrade mid-bug-hunt. The regression loop is the same. If you're getting throttled on free, the right move isn't upgrading — it's exporting to GitHub and fixing by hand.
Next step

Ship the fix. Keep the fix.

Emergency Triage restores service in 48 hours. Break the Fix Loop rebuilds CI so this error cannot ship again.

About the author

Hyder Shah leads Afterbuild Labs, shipping production rescues for apps built in Lovable, Bolt.new, Cursor, Replit, v0, and Base44. our rescue methodology.

Lovable burning through credits with no experts

If this problem keeps coming back, you probably need ongoing expertise in the underlying stack.

Sources