How to Automate Podcast Clips to Social Media

Neden podcast bölümlerini sosyal medya için yeniden kullanmalıyız

Podcasters put hours into every episode, but audio lives on platforms that reward loyalty over discovery. New listeners rarely stumble onto a podcast the way they find a TikTok or Instagram Reel. Short video clips are how people discover podcasts now.

A 60 minute interview can easily yield 10 to 20 standalone clips. Each one is a chance to reach a different audience on a different platform. TikTok favors raw, personality-driven moments. Instagram Reels rewards polished visuals. LinkedIn loves insightful takes from industry experts. YouTube Shorts drives subscribers to your full episodes.

The problem is distribution. Uploading each clip to five platforms manually, with different captions and optimal timing, takes longer than recording the episode. The social media posting API from Upload-Post handles that entire last mile. You focus on the content; the API handles delivery.

Podcast\'ten sosyal akışa

The complete pipeline has four stages:

1. Bölümünüzü kaydedin and export the audio (or video if you record with cameras).
2. Öne çıkanları çıkarın. Manually pick the best moments, or use AI tools like Whisper for transcription and Gemini or ChatGPT to identify the most engaging segments.
3. Video klipler oluştur. Turn each audio segment into a vertical video with waveforms, captions and speaker visuals. Tools like FFmpeg, Headliner, Descript and Opus Clip handle this.
4. Tüm platformlara dağıtın. Upload each clip to TikTok, Instagram, YouTube, LinkedIn and X in a single API call.

Upload-Post handles step 4 entirely. Combined with the FFmpeg entegrasyonu, it can also handle step 3. And with n8n workflows, you can automate the full pipeline end to end.

Tüm platformlara bir podcast klibi yükle

Once you have a video clip ready, send it to every platform with a single request. This cURL command posts to multiple platforms at once:

curl -X POST https://api.upload-post.com/api/upload \
  -H "Yetkilendirme: Apikey your-api-key-here" \
  -F "[email protected]" \
  -F "user=mypodcast" \
  -F "title=The biggest mistake new founders make" \
  -F "platform[]=tiktok" \
  -F "platform[]=instagram" \
  -F "platform[]=youtube" \
  -F "platform[]=linkedin" \
  -F "platform[]=x" \
  -F "media_type=REELS" \
  -F "async_upload=true"

The response comes back immediately because of async_upload=true:

{
  "status": "success",
  "message": "Yükleme talebi alındı",
  "request_id": "req_abc123xyz",
  "platforms": ["tiktok", "instagram", "youtube", "linkedin", "x"],
  "async": true
}

Five platforms handled in one call. No individual OAuth flows, no per-platform SDKs, no format juggling.

Altyazı ve ses grafikleri ekleyin

Raw audio doesn\'t perform well on visual platforms. You need video, and the most common approach for podcasts is the audiogram: a vertical video with a waveform animation, burned-in captions, and optionally the speaker\'s face or a branded background.

Several tools generate these clips:

• FFmpeg for full control over waveform overlays, text rendering and cropping. Use the Upload-Post FFmpeg API to run these commands in the cloud.
• Başlık for quick audiograms with templates and automatic captions.
• Descript metin seçebileceğiniz ve alt yazılı ilgili klibi dışa aktarabileceğiniz transkript tabanlı düzenleme için.
• Opus Clip video podcast\'lerden AI destekli öne çıkan tespit için.

Here is an FFmpeg command that creates a 1080x1920 audiogram with a waveform overlay from a podcast audio clip:

curl -X POST https://api.upload-post.com/api/uploadposts/ffmpeg/jobs/upload \
  -H "Yetkilendirme: Apikey your-api-key-here" \
  -F "[email protected]" \
  -F 'full_command=ffmpeg -i {input} -filter_complex "[0:a]showwaves=s=1080x200:mode=cline:colors=white[wave];color=c=#1a1a2e:s=1080x1920:d=60[bg];[bg][wave]overlay=0:860" -c:v libx264 -preset medium -pix_fmt yuv420p -c:a aac -shortest {output}' \
  -F "output_extension=mp4"

This produces a vertical video with a dark background and centered waveform. You can overlay podcast artwork, speaker photos or subtitle tracks for a more polished result. Check the video repurposing guide for more FFmpeg patterns.

Platforma özgü başlıklar

Each social platform has its own culture. A caption that works on TikTok reads wrong on LinkedIn. Upload-Post lets you set different text for each platform in the same request:

curl -X POST https://api.upload-post.com/api/upload \
  -H "Yetkilendirme: Apikey your-api-key-here" \
  -F "[email protected]" \
  -F "user=mypodcast" \
  -F "title=The biggest mistake new founders make #startups #podcast" \
  -F "youtube_description=In this clip from Episode 42, we discuss the single biggest mistake that kills most startups in year one. Full episode: https://podcast.example.com/ep42" \
  -F "youtube_tags=startups,founders,podcast clips,entrepreneurship" \
  -F "linkedin_description=After interviewing 200+ founders, this is the pattern I see over and over. The biggest mistake is not validating demand before building. Full conversation on the podcast." \
  -F "instagram_first_comment=#podcast #startups #founderstory #entrepreneurship #businesstips" \
  -F "media_type=REELS" \
  -F "platform[]=tiktok" \
  -F "platform[]=youtube" \
  -F "platform[]=linkedin" \
  -F "platform[]=instagram" \
  -F "platform[]=x"

The title field serves as the default caption for platforms without a specific override. TikTok and X use the title value. YouTube gets its own SEO-friendly description and tags. LinkedIn gets a professional tone. Instagram hashtags go in the instagram_first_comment to keep the main caption clean.

Bir haftalık klipleri planla

One episode, five clips, five different days. Use the scheduled_date parameter to schedule each clip for a specific date and time:

curl -X POST https://api.upload-post.com/api/upload \
  -H "Yetkilendirme: Apikey your-api-key-here" \
  -F "[email protected]" \
  -F "user=mypodcast" \
  -F "title=Why most podcast growth advice is wrong" \
  -F "platform[]=tiktok" \
  -F "platform[]=instagram" \
  -F "platform[]=linkedin" \
  -F "media_type=REELS" \
  -F "scheduled_date=2025-07-21T09:00:00Z" \
  -F "timezone=America/New_York"

Or skip the manual date math and use add_to_queue=true to let Upload-Post place each clip in the next available slot based on your queue configuration. The queue respects platform daily limits and distributes content evenly. See the TikTok planlama kılavuzu and Instagram otomasyon kılavuzu for platform-specific tips.

Python ile otomatikleştir

This Python betiği reads clip files from a folder, posts each one to multiple platforms, and staggers them across the week. Install the SDK first:

import os
import glob
from datetime import datetime, timedelta
from upload_post import UploadPostClient

client = UploadPostClient(api_key="your-api-key-here")

clip_folder = "/path/to/podcast-clips"
clips = sorted(glob.glob(os.path.join(clip_folder, "*.mp4")))

platforms = ["tiktok", "instagram", "youtube", "linkedin"]
base_date = datetime(2025, 7, 21, 9, 0, 0)  # Next Monday at 9 AM

print(f"Found {len(clips)} clips to schedule")

for i, clip_path in enumerate(clips):
    filename = os.path.basename(clip_path)
    title = filename.replace(".mp4", "").replace("-", " ").replace("_", " ")
    schedule_date = base_date + timedelta(days=i)

    try:
        response = client.upload_video(
            video_path=clip_path,
            title=title,
            user="mypodcast",
            platforms=platforms,
            media_type="REELS",
            scheduled_date=schedule_date.isoformat() + "Z",
            timezone="Amerika/New_York",
            async_upload=True
        )
        job_id = response.get("request_id", "async")
        print(f"[{i+1}/{len(clips)}] Scheduled {filename} for {schedule_date.strftime('%A %B %d')} ({job_id})")
    except Exception as e:
        print(f"[{i+1}/{len(clips)}] Failed: {filename} - {e}")

print("Tüm klipler planlandı!")

Each clip gets published one day after the previous one. Monday through Friday, your audience sees a new clip from the same episode. By the time you record the next episode, the pipeline refills itself. For bulk upload operations with larger batches, use add_to_queue=True instead of manual date math.

n8n ile kodsuz

If you prefer a visual workflow over scripts, n8n can automate the full podcast-to-social pipeline. The idea: combine Whisper for transcription, Gemini for highlight detection, FFmpeg for clip creation, and Upload-Post for distribution. All connected in a drag and drop canvas.

A typical n8n podcast workflow looks like this:

1. Tetikleyici: New file appears in Google Drive or Dropbox (your raw episode audio).
2. Transkribe et: Send the audio to OpenAI Whisper to get a timestamped transcript.
3. Öne çıkanları tespit et: Pass the transcript to Gemini or GPT with a prompt like "En ilgi çekici 60 saniyelik 5 segmenti bulun ve zaman damgalarını döndürün."
4. Klipler oluştur: For each highlight, call the Upload-Post FFmpeg API to extract the segment and add a waveform overlay.
5. Dağıt: Send each processed clip to all platforms via the Upload-Post upload endpoint with staggered scheduling.

You can also use Make.com for a similar setup if that is your preferred automation tool.

Podcast\'ler için hazır n8n şablonları

Instead of building from scratch, start with one of these templates on the n8n templates page:

• Podcast\'leri Gemini AI ile viral TikTok kliplerine dönüştür: Uses Gemini to identify the best moments, creates captioned clips, and auto-posts to TikTok.
• Tam otomatik podcast klipleri ile düzenleme ve altyazılar: End-to-end pipeline from raw audio to published TikTok clips with burned-in subtitles.
• Whisper ve Gemini ile uzun videoları Shorts\'a: Works for video podcasts. Transcribes with Whisper, picks highlights with Gemini, and schedules Shorts across platforms.
• AI ile toplu otomatik yayınlama videoları: Batch process multiple clips with AI-generated captions and publish across all connected networks.
• Tamamen otomatikleştirilmiş AI video üretimi: Generate video content from scratch using AI, useful for creating visual assets from podcast transcripts.

Each template can be imported into your self-hosted or cloud n8n instance with one click. Use the social media holiday calendar to time your clips around trending topics and awareness days.

Platform başına en iyi klip uzunluğu

Not every platform rewards the same clip length. Here\'s what works best for podcast clips based on platform behavior:

The safe zone for cross-platform clips is 45 to 58 seconds in 9:16 vertical format. A clip that length works everywhere, including YouTube Shorts with its strict 60 second limit. For longer LinkedIn content, create a separate cut. See the LinkedIn API kılavuzu for details on LinkedIn-specific parameters. You can also check the YouTube Shorts kılavuzu for more on Shorts optimization.

Sıkça sorulan sorular

Podcast klipleri için en iyi video formatı hangisidir?

H.264 MP4 in 1080x1920 (9:16 vertical). This is universally accepted across TikTok, Instagram, YouTube, LinkedIn and X. Keep the file under 300 MB to stay within Instagram\'s limit. Use -c:v libx264 -pix_fmt yuv420p -movflags +faststart in FFmpeg for maximum compatibility.

Sadece ses içeriği paylaşabilir miyim?

Social platforms require video files. You cannot upload raw MP3 or WAV files. Convert your audio to a video first by adding a static image, waveform animation or caption overlay. The FFmpeg API makes this easy with a single command. Tools like Headliner and Descript also handle this conversion.

Kliplerime altyazı ve açıklama nasıl eklerim?

Three options. First, use Descript or Opus Clip to generate captions and export the video with burned-in text. Second, use Whisper for transcription and FFmpeg\'s subtitles filter to overlay an SRT file. Third, use the n8n templates mentioned above, which combine Whisper transcription with automatic caption rendering. Burned-in captions consistently boost engagement by 30 to 40 percent since most social media is consumed with sound off.

Audiogram tarzı videolar hakkında ne olacak?

Audiograms (waveform plus background plus captions) are the simplest way to turn audio into video. Headliner is the most popular dedicated tool. For more control, build audiograms with FFmpeg using the showwaves filter as shown earlier in this guide. The Upload-Post FFmpeg API lets you run these commands in the cloud without local processing.

Her bölüm için kaç klip oluşturmalıyım?

Aim for 5 to 10 clips per episode. That gives you a full week of content if you post once or twice per day. Start with the strongest moments: controversial takes, surprising facts, emotional stories and actionable advice. Quality matters more than quantity. A Hootsuite alternatifi or Buffer alternatifi like Upload-Post makes the distribution effortless once your clips are ready.