How to Automate Social Media Scheduling Across Platforms

I built this system to schedule posts across linkedin, facebook, instagram, and x from one system. This automate social media scheduling multi-platform setup automates the repetitive work so you can focus on strategy.

Social media at scale needs systems. Manual posting and tracking breaks past a few accounts.

What You Need Before Starting

• Python 3.8+ with requests
• Anthropic API key for content generation
• Platform API credentials
• SQLite for tracking

Step 1: Set Up Data Storage

import sqlite3
from datetime import datetime

db = sqlite3.connect("social_system.db")
db.execute('''CREATE TABLE IF NOT EXISTS social_data (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    platform TEXT, content TEXT, engagement INTEGER,
    created_at TEXT, status TEXT
)''')
db.commit()

Step 2: Build the AI Engine

import anthropic
from dotenv import load_dotenv

load_dotenv()
client = anthropic.Anthropic()

def generate_content(platform, topic, voice):
    message = client.messages.create(
        model="claude-sonnet-4-20250514",
        max_tokens=1024,
        system=f"Create {platform}-native content. Voice: {voice}. Drive engagement.",
        messages=[{"role": "user", "content": f"Platform: {platform}. Topic: {topic}. Generate post."}]
    )
    return message.content[0].text

Step 3: Connect to Platform APIs

import requests
import os

def post_to_platform(platform, content):
    if platform == "linkedin":
        return requests.post(
            "https://api.linkedin.com/v2/ugcPosts",
            headers={"Authorization": f"Bearer {os.getenv('LINKEDIN_TOKEN')}"},
            json={"content": content}
        )
    elif platform == "facebook":
        return requests.post(
            f"https://graph.facebook.com/v18.0/me/feed",
            params={"access_token": os.getenv("META_TOKEN"), "message": content}
        )

Step 4: Track Performance

def log_performance(platform, post_id, metrics):
    db.execute("INSERT INTO social_data (platform, content, engagement, created_at, status) VALUES (?,?,?,?,?)",
        (platform, post_id, metrics.get("engagement", 0), datetime.now().isoformat(), "tracked"))
    db.commit()

# Pull metrics daily
0 8 * * * cd /app && python pull_social_metrics.py

What to Build Next

Add AI analysis that identifies your top content patterns and generates more of what performs best.

Related Reading

• AI for Social Media Management - AI-powered social media management
• Building an Automated Social Media Calendar - framework for deciding what to automate first
• Setting Up Automated Social Media Responses - framework for deciding what to automate first