Sometimes the fix isn't a new system — it's finding the one wrong module in an existing one. A cl...Sometimes the fix isn't a new system — it's finding the one wrong module in an existing one. A cl...
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Ayub Muhabbatzoda
• 1d
Sometimes the fix isn't a new system — it's finding the one wrong module in an existing one.
A client's Make.com scenario was supposed to combine multiple Google Drive files into a single text payload and run one Claude API call on the result. Instead, it was firing the Claude API once per file — burning API costs and returning fragmented, inconsistent output.
I traced the issue to the scenario's aggregation logic: files were being processed individually instead of being merged before the API step. I redesigned the module structure — Drive Search, Download, Array/Text Aggregator, Set Variable, then a single Claude API call — with the exact aggregator configuration and mapping formulas needed to guarantee one clean, ordered payload per run.
Result: 4x fewer API calls, consistent output, and zero need to rebuild the scenario from scratch. Delivered same day.
This is the kind of workflow debugging I do constantly across Make, n8n, and Zapier — if your automation is technically "working" but doing something expensive or wrong under the hood, I can usually find it fast.
AI AutomationClaudeMakePython
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