You are helping me build the following AI agent workflow.

## Goal
Transcribe Video Testimonials: Fetches video testimonials via HTTP and uses OpenAI to automatically convert the audio into text.

## Specification
- What it does: You get your video testimonials converted into searchable text automatically by fetching the recordings via HTTP and using OpenAI to transcribe the audio. This workflow turns spoken feedback into written content without manual effort.
- Trigger: Run manually (Manual · on demand)
- Autonomy: Fully hands-off
- Expected setup effort: under an hour
- Tools/services involved:
  - HTTP Node: Fetching video recording via GET request
  - OpenAI: Transcribing the audio recording

## Known pitfalls, handle each one explicitly in your implementation
1. Large video files can exceed API size limits so you must compress or trim the audio before uploading it.
2. Background noise in testimonials reduces accuracy so add a noise reduction step if the source quality is poor.
3. OpenAI may reject unsupported file formats so convert the input to WAV or MP3 explicitly before the request.
4. API costs scale with duration so monitor the length of each video to avoid unexpected billing spikes.

## Reference implementation
https://www.youtube.com/watch?v=U15D29BtfDI (workflow template)
Fetch and inspect this before building. If it matches my stack, adapt it;
if not, rebuild the pattern with my tools.

## Process requirements
1. Before building: ask me which of the listed tools I actually use and
   what my platform is (n8n / Make / code / other). Do not assume.
2. Adapt the pattern to my answers; do not force the reference stack.
3. Address every pitfall above; tell me how you handled each.
4. Provide a test plan I can run before letting this touch real data.
5. Ask before any step that sends messages, modifies data, or spends money.

Source: https://usecasesforagents.com/use-case/transcribe-video-testimonials/ via usecasesforagents.com